Big Data, bigger challenges

Transcription

Page
Vol. 17 No. 5
Classified Intelligence Report
Consulting Services for Interactive Media and Classified Advertising
Vol. 17 No. 5 March 21, 2016
Big Data and Programmatic Ad Buying
Big Data,
bigger challenges
Frontier markets in Southeast Asia face major obstacles, Page 41
© 2015 Advanced Interactive Media Group LLC
info@aimgroup.com +1-407-788-2780
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Vol. 17 No. 5
Executive Summary
Big Data making a big difference
It is safe to say that “Big Data” and its ability to transform the way a business operates
may have been one of the most over-hyped trends over the past five years. For some time, it
appeared the only people doing well out of it were those presenting at any conference around
the world. However, with Facebook as the leading example it is clear that the effective use of
data can be a route to riches. Norway’s Schibsted and the U.K.’s Haymarket are already seeing Facebook as a direct competitor for their data-driven ad services.
It is time to look beyond the hype and figure out how the billions of data points collected on classified sites can be used to drive revenue and improve the customer
experience. After all, we are already seeing the faith being placed in data:
Spain’s Adoos is wholly relying on data to restore its market position while
U.S. major Trulia is preparing for a classified world of virtual reality and artificial intelligence.
Rob Paterson
Currently, the use of data is concentrated in two areas. The first is to
better serve advertising to visitors. European players like Tamedia, Ringier
and Schibsted in particular are at the forefront of initiatives to gain more value from their audience. Programmatic advertising thrives on data. If classified sites can provide more then maybe CPMs can be driven up again.
The second concentration of activity around data use is the development of tools for
business advertisers. Car dealers and real estate agents are starting to benefit from classified
sites presenting them with information that could help them drive sales. The issue here may
be the need to educate the dealer in how they can use the information. Malaysia-based IProperty, France’s SeLoger and Pakistan’s Zameen are doing exactly that.
We anticipate an increased use of data as a competitive factor in classified businesses.
It used to be the case that to win and dominate a classified market you just needed lots of
listings and a good search. Now, we are moving into an era where the user experience should
be transformed by data. In recent years, most of the innovation in classifieds has been incremental — we believe that in the near future the smart use of data will transform classified
marketplaces. The challenge will be for the existing dominant players to make sure they are
leading the transformation.
There are more insights inside, covering nearly 100 companies from 25 countries. We
hope you find it informative and inspirational.
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Vol. 17 No. 5
classifiedintelligence report
Peter M. Zollman, Founder, Executive Editor
peterz@aimgroup.com
Katja Riefler, Principal, Managing Director
katjar@aimgroup.com
Rob Paterson, Principal, Director-Consulting,
Contributing Editor
robp@aimgroup.com
Jim Townsend, Principal, Editorial Director
jimt@aimgroup.com
Pavel Marceux, Managing Editor
pavelm@aimgroup.com
Léo Siqueira, Director, Latin America
leos@aimgroup.com
Christoffel Volschenk, Editor EMEA
christov@aimgroup.com
Senior Consultants
Konstantin Kalabin
Gareth Lloyd
Lars Herlin (Scandinavia)
Kenny Kinako (Africa)
Brian Blum (U.S., Canada,
Israel)
Senior Analysts
Western Europe
Alessandra Ritondo
Cila Warncke
Cristina Costa
Anastasia Gnezditskaia
Lisa Walls-Hester
Eastern Europe
Andrzej Sowula
India
Radhika Sachdev
Shilpa Shree
Africa
Mamello Masote
Adegoke Seun
Contents
Page 5. Established auto major Haymarket and rising
startup Carsnip are making waves.
Page 9. ICar Asia using Big Data to help mature the
dealership market.
Page 12. Auto classifieds in India embrace Big Data.
Page 15. Data guru at U.S. real estate leader Trulia
talks challenges, opportunities.
Page 18. LiveYield seeks to turn real estate classified users into institutional investors.
Page 20. AirBnB uses machine learning to detect host
preferences and predict rebooking.
Page 23. Malaysia’s IProperty and Singapore’s PropertyGuru use data to dominate market.
Page 25. French classified sites increasingly using Big
Data in retargeting.
Page 31. Zhaopin connects workers with opportunities throughout their career life cycle.
Turkey
Emre Dalkilic
Asia
Marco Bouwer
Southeast Asia
Marian Jacob
Middle East
Ayman Yasser Hilal
Australia
Kate Lyons
Page 36. Schibsted building a network of display ads,
geo-fencing and e-payment solutions.
Pakistan
Tariq Ahmed Saeedi
Page 39. Spain’s Adoos debuts data-centric app.
China
Don Gasper
Mary Biddle, sales— Americas, Australia, Asia
maryb@aimgroup.com
Diana Neatu, sales / marketing EMEA
dianan@aimgroup.com
Suzanne Lander, finance director
suzannel@aimgroup.com
Robin Monti, client services manager
robinm@aimgroup.com
Luke J. Smith, marketing
lukes@aimgroup.com
Michael T. Gaffey, production editor
Published twice monthly, except once in December, by Advanced Interactive
Media Group LLC. This publication may not be reproduced in any form, in
whole or in part, except by licensed clients.
Classified Intelligence Report occasionally covers companies that are clients
of the AIM Group. We make every effort to ensure that our editorial content is
objective and is not compromised by any client relationship.
402 Spring Valley Road
Altamonte Springs, Florida, USA 32714
+1 407-788-2780 Fax +1 866-611-6551
Page 33. Grupa Pracuj, GoldenLine bet on data analysis to win market supremacy.
Page 41. S.E. Asia frontier markets face obstacles.
Page 45. Two Swiss majors integrating programmatic
ads into Europe’s classifieds.
Page 49. Job verticals start to use data and sophisticated software to enhance ad placement.
Page 51. Dutch platforms try programmatic ads.
Pages 53-57. Big Data vendors.
Page 58. RealMassive settles lawsuit fior $1 million.
Page 61. Renrenche benefits from China’s used car
market.
Page 64. QuickrJobs faces competition in India.
Page 67. More news, analysis from AIMGroup.com.
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Vol. 17 No. 5
Auto
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Vol. 17 No. 5
Data drives Haymarket, Carsnip
Veteran, startup offer innovative tools for U.K. autos
An established auto major and a burgeoning startup are making waves beyond the
local market.
BY LISA WALLS-HESTER
At first sight, the huge Haymarket brand and the relatively unknown startup Carsnip
have little in common apart from their interest in auto classifieds. However, both companies
have a complete commitment to becoming fully data-driven and pursuing a global strategy.
Haymarket readying for an era of competing against Facebook, Google
Haymarket Automotive Group, which publishes more than 100 consumer, professional,
trade, and customer publications in
some 20 languages, transformed its digital strategy after it tried some discrete
data initiatives in 2014 with its U.K. auto
vertical Pistonheads (the second player
by web traffic).
Patrick Fuller, Group Director of
Haymarket Automotive, has attributed
the “transformation of commercial digital thinking” to Lee Williams, who
joined Haymarket in 2013 as Director of
Pistonheads.
Williams is a digital specialist who
took Auto Trader U.K. online almost two
decades ago. He said the future is media
that is purchased and consumed in a
personalized, targeted way. In early 2015, Williams was appointed Director of Digital Revenues, with responsibility for online revenue streams across the Haymarket group.
The data investment strategy was implemented swiftly, from a board approval in late
2014, to procurement and re-organization in spring 2015.
However, as Haymarket started down the path of data analysis Williams recognized
that his biggest competitors were not the historic print companies who are also aiming to
transform, but the Facebook and Google duopoly.
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“In U.K. auto classifieds a dealer has five quality choices to make in digital platforms:
Auto Trader, Haymarket (PistonHeads), Ebay (Gumtree), Google Ad Words (often their major
investment) and Facebook Ads. The common denominator is they are all geared up or gearing
up to leverage data to build great experiences,” Williams said.
Leveraging huge data network to maximize advertising efficiency
The Haymarket Group, with its diverse range of auto publications and sites, has the potential to collect more data about the auto-buying journey than anyone else.
Haymarket said there is currently wastage in targeting auto buyers and has developed a
data-driven advertising
concept that it calls Laser Targeting. The company believes its ads
can out-perform direct
competitors by targeting a segment to pinpoint accuracy, improving an advertiser’s ROI.
Real-time insights are the holy grail
for advertisers and Haymarket said its marketleading data is not only
Haymarket Automotive Group publishes more than 100 consumer, accurate but timely,
professional, trade, and customer publications in 20 languages.
too. It can forecast
when a buyer is likely
to make a purchase. By encouraging users to login to its sites, Haymarket is able to identify
and track every individual, learning the vehicles of interest (to brand and model level), motivations in selection criteria and the buyers’ propensity to purchase. This allows advertisers to
target the right commercial opportunity at the right time and enables them to tailor content
to an individual buyer.
The total investment in Big Data initiatives is undisclosed, but Williams believes the
company is on track to exceed the return on the initial investment.
Haymarket expects to further expand its data position and analytics in the short-term
through:

Investing in personalized insight platforms.
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Building media and off-website channel partnerships to reach more audiences.


Vol. 17 No. 5
Looking at products and useful tools delivered classically, by a widget, or by APIs to improve customer experiences by collecting data.
“The brand talent in Haymarket is extraordinary, by removing the silo approach and
looking at the big picture, we can deliver collective scale to market in a personalized way,”
Williams said.
Carsnip looks to deliver a global Google for autos
Also focusing on premium personalization is Carsnip, the new auto search engine that
uses natural language search to enable buyers to search for vehicles. The company believes it
has the Big Data edge to challenge
established classified players in
the UK and perhaps the world.
The enterprise grew out of
a frustrated search for a “seven
seater auto, in Nottingham” by entrepreneur Alastair Campbell.
When Campbell realized classified
sites were not configured to handle natural language queries he
decided to build his own search
engine. The site is currently running in Beta and is expected to
have an official launch at an upcoming U.K. auto trade show.
New auto search engine Carsnip believes it has the Big
Data edge to challenge established classified players in
the UK and perhaps the world.
Carsnip has not yet finished
its U.K. crawl, but already hosts
over 500,000 autos. Campbell said
it will reach 650,000 by the sum-
mer.
Auto Trader has dominated the U.K.’s automotive classified industry for years, but
Campbell said it hosts only about half of all the autos available for sale. Auto Trader has
about 420,000 autos listed and claims to have a 65 percent share of the U.K.’s used auto market.
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Campbell told the AIM Group there are thousands of autos out there that are just not
advertised because dealers cannot afford to put all of their stock on classified sites. A typical
dealer will only advertise around 40 percent of its stock.
Carsnip can give auto buyers any ad from a dealer’s website, which will open up the
market to give dealers a comprehensive online shop window and buyers a comprehensive market search.
The Carsnip model is currently free to dealers and its search has been built to have no
impact on the websites it looks at.
“This type of search is not new to consumers. It is already done on Google, but Carsnip
is the first auto search that will return fast and relevant results to auto buyers,” Campbell
said.
Carsnip has received backing from some leading tech angels that have previously
backed companies such as Pinterest, Square, Wavii and Wish.
Dealers set to benefit from cheaper listings
Campbell is focused on building scale and awareness rather than a fast route to payback but said the site will eventually implement a pay-per-click advertising model, similar to
Google Adwords, allowing dealers to highlight specific vehicles.
The amount is yet to be determined but Campbell expects to charge dealers around 10
pence per click, which means dealers will still save thousands of pounds compared to existing
classified sites. As a search will only return ‘relevant’ listings, it is envisioned that only a
handful of the first few or ‘most relevant’ ads displayed will incur a charge for the dealer.
The site integrates vehicle information and data from auto industry product providers, which include insurers, finance companies, service centers and tyre sellers to deliver the
total cost of motoring to auto buyers. Buyers will be able to see how much each vehicle will
cost them over its lifetime and not just the upfront capital outlay, and can even compare this
cost to an existing vehicle by keying their vehicle registration.
Search results update in real time and only information specific to buyers is displayed.
Campbell said the technology is scalable, and he already has plans to expand into new
countries, either as a standalone platform, or licensed “white label” solutions for auto industry partners.
Carsnip already has a couple of U.K. partners lined up, and a publisher in Ireland with a
massive media reach.
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Vol. 17 No. 5
ICar Asia system bolsters business
RMS gathers data to enhance dealers’ expertise
The leading Southeast Asian auto vertical group is using Big Data to help mature the
dealership market.
BY MARIAN JACOB
For ICar CEO Damon Reilly, Big Data is all about “understanding and controlling the
lead market.” It is a strategy that enables the company to deliver competitive value to dealers and agents that use its car portals.
ICar Asia owns and operates Southeast
Asia’s leading network of auto verticals. Headquartered in Kuala Lumpur, Malaysia, the company is focused on developing and operating leading automotive portals in Malaysia, Indonesia and
Thailand. ICar Asia’s online platforms currently
reach more than 4.8 million car buyers and
sellers in the region every month.
Disruptive tech for dealers
ICar’s Big Data solution is the Response
Management System (RMS), which pulls in data
and analysis that enables dealers to gain insights
into the car-buying experience.
“The RMS runs on core metrics that enable dealers to run a successful business on their
own,” Reilly said.
Damon Reilly is CEO of ICar, whose
online platforms reach more than
4.8 million car buyers and sellers in
Southeast Asia.
“There was a broken car industry in
Southeast Asia. Lots of trust issues and difficulties associated with buying and selling cars.
People in our part of the world are frustrated with the experience of buying and selling cars.
Our aim was to sharply define the customer and be brutally focused on three countries — Malaysia, Thailand and Indonesia, and to be the most trusted independent source,” he said.
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The RMS currently serves 6,500 dealers in these three markets. Launched in June 2014,
there was a broad dealer education program, focused on making them perceptive users of
the system.
“We have full-time trainers out there who are constantly training our audience. It’s
quite an effort we take on our part, we want to get dealers out from an old-school mentality
and embrace the digital revolution,” Reilly said.
The RMS provides analytics across a range of values
like model variants, pricing,
searches and real time demand. ICar Asia works on a
partnership basis with
Redbook, which is essentially
a large database of manufacturer and OEM data and is the Australian version of the Kelley Blue Book from the U.S.
Redbook is powered by Carsales.com, which owns 20 percent of ICar Asia.
Redbook contains information on vehicles’ specifications and ties in with financing and
insurance companies. Forecasting and valuation is possible. The model is similarly executed
elsewhere. Autogate does the same thing, as does BeAuto, which was acquired by Auto Trader.
The focus is on enhancing the marketplace as a whole
In each of its markets, ICar Asia records 1,600-1,800 unique dealers logging in and
making one change or lead action every month. The system is able to help dealers track the
velocity of movement — how many cars are at any one time on the market, changes in demand and supply and price movements.
Reilly has more plans for the future of the company.
“The online business in Southeast Asia is very fragmented and this makes it easy for
disruption. We want to win not just the classifieds piece, but also the evolving piece around
the marketplace as a whole,” he said.
Despite an initial focus on having a mobile-optimized site, the company has recently
embraced app development by launching mobile apps in Malaysia and Indonesia.
“We find that we have very engaged car buyers on apps. There are three times more
conversions on apps via desktop usage alone,” Reilly said.
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ICar Asia owns and operates Southeast Asia’s leading network of auto verticals. Headquartered in Kuala Lumpur, Malaysia, the company is focused on developing and operating
leading automotive portals in Malaysia, Indonesia and Thailand.
In Jan. 2016, 80,000 downloads of the app were recorded in Malaysia and 15,000 in Indonesia.
All the usage information from the apps feeds the RMS system, which dealers can then
use.
However, the Asian market is not without major obstacles.
“In Thailand and Indonesia, we have seen a slowdown in new car sales. In Malaysia, the
introduction of the goods and services tax, and the ringgit dropping in value is potentially difficult. Nonetheless, it is during the tough times that we have found new and innovative ways
of bolstering the business,” Reilly said.
He said that the digital revolution was borne out of having to use more cost effective
media that was trackable and hence accountable. This possibly could mean the RMS is more
recession-proof than other products.
“We have the data in our hands, and now it’s a key strategy on how we can use data to
support our business and those associated with us,” Reilly said.
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India’s auto players dive into data
Verticals follow carmakers’ lead to assist customers
Verticals have learned from carmakers to make data go further.
BY RADHIKA SACHDEV
In April 2015, one of India's largest automotive classifieds sites, Sequoia-backed
Cardekho.com, acquired BuyingIQ.com, an intelligent shopping engine, for an undisclosed
price.
The purchase signaled a major effort to bring Big Data to online merchandising in India.
Founded by two IT graduates in 2012, BuyingIQ is a price comparison platform that
takes an analytical approach to helping car owners make informed, data-driven choices to sell
or buy new cars. The startup has worked with almost all e-commerce majors (Flipkart,
Snapdeal, Ebay and Amazon) and automotive classifieds, claiming traffic of 1.2 million visits
each month on its website and Android app.
Local carmakers were the first to pioneer auto data techniques
Although Big Data tools have been in India since 2008, they were almost exclusively
used by carmakers to re-engineer their products or improve services and predict sales in certain markets.
These days, auto classifieds — such as Girnar Soft's flagship, Cardekho.com; Temasekbacked CarTrade.com; Tiger Global and Carwale.com (acquired last year by CarTrade.com);
and general classified Quikr's dedicated auto vertical, QuikrCars — have also begun to consume oceans of data from multiple sources, not just to improve sales but also to enhance the
buying experience.
"We use data to transform our visitor's digital buying journeys, make them more intuitive and, accordingly, tweak our internal algorithms to make appropriate suggestions to customers about what car choice is best suited to their needs," said Dhruv Chopra, Chief Marketing Officer for CarTrade.com and Carwale.com.
India’s classifieds now use data (both structured and unstructured) to build their inhouse capabilities in order to be able to communicate targeted offers to potential buyers,
help them compare prices, make recommendations from various data sources, identify dealer
issues, and address financing, warranty and service requests.
"We also assist car brands and dealers in streamlining their internal sales processes,
score buying propensity of prospects, predict market interest (and likely sales volumes), opti© 2015 Advanced Interactive Media Group LLC
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mize marketing campaigns and improve customer acquisition programs with our in-house data
warehouse and analytics teams," Chopra said.
CarTrade's data warehouse uses multiple, industry-standard, customized modules for
intelligence gathering and business reporting, depending on the best-fit scenario, rather than
outsourcing the capability to an external technology partner.
Used car market offers more analytical challenges
In the used car space that is growing at double the rate of the new car market in India,
analyzing buyer behavior with data carries an additional benefit — price transparency. Two
examples are Girnar's price comparison site, Pricedekho.com, and Quikr's Maximum Selling
Price (MSP) calculator.
"We have algorithms in place that use various data points to arrive at a resale price for
pre-owned cars and make targeted purchase recommendations, resulting in higher conversions," said Atul Tewari, COO at Quikr and the Head of QuikrCars.
Additionally, platforms like Quikr are also able to use data to cross-sell and upsell by
making recommendations from their other verticals. For instance, QuikrServices takes care of
insurance, maintenance and repairs.
Although the platform and data-gathering techniques are similar for new and used cars,
the analysis and ultimate implementation of data differs.
In the new car segment, once a platform is able to help a visitor select a particular car,
that same car is available across all markets and dealers.
However, in used car markets the decision-making is more complex.
"Buying decisions are more value-driven, where multiple factors come into play in arriving at the perceived value of a car, such as the car model, the number of owners, mileage,
condition, service history, etc. Such parameters can also differ from city to city and buyer to
buyer, based on their individual preferences," Chopra said.
So, while a new car buyer is choosing from multiple cars in the same price range, a
used car buyer may well be choosing between a three-year-old Honda City and a five-year-old
Toyota Camry, available at the same price, even though these models may be vastly different.
Although auto buyers in India have yet to experience real application of Big Data, autonomous software industry watchdog NASSCOM predicts that the local analytics market is set
to double to $2.3 billion U.S. by 2018, up from $1.5 billion U.S. in 2015.
Local auto verticals are readying to take advantage of both the Big Data boom and the
growing demand for cars among India’s urban middle class.
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Real estate
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Trulia exec breaks down Big Data
Varma expects virtual reality will help home buyers
The data guru at the U.S. real estate leader talks challenges and opportunities.
BY BRIAN BLUM
Deep Varma knows Big Data. As VP of data engineering at U.S. real estate classified
company Trulia, the Silicon Valley veteran computer scientist oversees the management of
1.5 terabytes of data every single day.
The term Big Data is popping up everywhere these days, Varma told the AIM Group, but
to understand what it means in a tangible way, one need only look at a site like Trulia.
For Trulia, challenge lies in collecting huge scope of data
When Trulia recommends “similar properties,”
that is Big Data at play.
Generating a specific
set of suggestions involves
combining what Trulia has
tagged about a property —
everything from the “easy”
data like number of bedrooms and bathrooms down
to the nitty-gritty tech specs
such as the type of marble on
the kitchen island or faucet
design — with user behavior
on the site.
Deep Varma and his team of 50 Big Data specialists at Trulia
have built an in-house “personalization hub” to serve up the
right content to visitors.
Trulia tracks what it
calls consumer “intent,” Varma said. In just a few minutes of engagement on Trulia.com, a
visitor will “generate an average of 18-20 events — or signals — about their intent.” This includes what images they’ve looked at — did they poke around the closets or inspect the size
of the kitchen cabinets? — as well as data external to the property itself, such as neighborhood crime scores or local school ratings.
Varma and his team of 50 Big Data specialists at Trulia have built an in-house
“personalization hub” to serve up the right content to visitors.
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“Personalization is when we show you similar properties in your price range in the particular neighborhood you’re looking at,” Varma said. “Individualization takes a broader look —
if you’re looking for certain types of schools, we can show you similar properties but in different neighborhoods.”
All that sounds simple enough, but when you have millions of monthly visitors all generating dozens of “events,” coupled with the 4 million listings that Trulia processes every day
plus another 10 million public records, it is easy to see why Big Data is big business.
External data, such as public records, is just as valuable
Data at Trulia falls into two core sets, Varma said, with separate teams processing the
information (the
Trulia and Zillow
brands remain
completely silo’d
within the Zillow
Group corporate
umbrella).
The first dataset comprises
listings and public
records. Varma
called listings a
“commodity item”
— most are provided to Trulia via
feeds from MLSs,
brokers and
agents.
Public records are trickier.
These are the
deeds, taxes and
assessment data that give visitors to Trulia the historical perspective it needs to understand a
property’s true value. There are 3,000 counties in the U.S. but no standards across counties or
even between different types of public records. So data schema, format and accessibility can
be wildly different.
Trulia processes 4 million listings every day, plus another 10 million
public records.
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Standardizing addresses is undoubtedly “the biggest problem we face,” Varma said.
One mis-assignment “can screw up all our unique insights.” Trulia built its own tools for address standardization — it’s definitely not something off-the-shelf, Varma said proudly. (For
techies, it involves using an open standard format called JSON, derived from JavaScript.)
Into this mix of text listings and records, Trulia adds pictures (“we’ve built our own image recognition technology that can tag a kitchen, bathroom or front yard as such, as well as
an object recognition technology that can do the same for dishwashers and stainless steel
stoves,” Varma said) and “location aware data” from external sources, such as local amenities
and school rankings.
Using the standardized addresses, everything is linked together before it’s merged, indexed and run through Trulia’s Data Service API, which makes the resulting content searchable by visitors to Trulia.com. And of course, it all has to happen in near real time.
On the consumer behavior side, Trulia uses “deep data science and machine learning”
in order to build “a digital signature.” Providing the same experience whether a visitor is registered and logged in or not is critical to Varma.
“Our goal is to help consumers make the best decisions. We don’t need their names for
that. In fact, the majority of our users are anonymous. We’re not on a path of pushing a person into a funnel towards an agent. It’s up to the consumer. They can do that when they’re
ready,” Varma said.
The future is virtual reality and AI
What is the future for Big Data at Trulia? Varma expects virtual reality to catch on and
become another, even more valuable source of Big Data to be processed. If today Trulia can
track user “events” generated by a click on an image of a refrigerator or the en-suite bathroom, imagine what happens when that same user straps on a pair of VR goggles at home and
virtually walks around a home for sale. Every touch, every linger and glance can — and will —
be added to the shopper’s digital signature, Varma said.
Before virtual reality goes mainstream, though, the term Big Data may fall out of use.
“Today, people think, oh my God, it must be a big thing, since the name starts with
big. But in the next 2-3 years, it will become an integral part of every consumer business,”
Varma said.
In the future, we may be talking more about the Internet of Things, which is basically
the same as Big Data, Or we may simply call it “artificial intelligence.”
Whatever name is used, Big Data is here to stay, and so is Deep Varma, Trulia’s Big Data daddy.
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LiveYield can empower investors
Startup can determine yields on all property types
The U.K. startup has developed an algorithm that calculates yield across all residential
property types.
Intelligent startups are using Big Data to create massive disruption in the classified
space. Some are providing increased market data for the masses and changing the property
investment market entirely.
One such startup is LiveYield, a U.K.-based property investment search and analysis
website, founded by property investment analyst James Bailey. The LiveYield site gives investors the ability to search for property investments by risk-and-return fundamentals. It highlights high-yield investments and undervalued properties, and can calculate yield across all
residential property types, from studio flats to large houses.
The site, while still in beta, has developed an algorithm that analyses rental yields
across different areas of the U.K. LiveYield is powered by sales from local real estate vertical
major Zoopla’s API and combines this information with data from the Valuation Office Agency
and Land Registry House Price Index to create a total return index.
The Zoopla API database contains data on 27 million homes, more than 1 million sale
and rental listings, and 15 years of sold price data.
Big Data is empowering individuals to a level of an industry insider
Bailey, who spent some time exploring property crowdfunding and peer-to-peer lending
solutions, had the idea to provide enhanced market intelligence and decision-making tools for
independent property investors.
“I was working as a freelance property investment consultant and using Big Data business intelligence tools that used interactive mapping technologies when the idea of a heatmap and graphical analysis to search for buy-to-let property from an investment perspective
stuck me. We took the framework of a website we’d been developing for a crowdfunding model and applied it to something that would be immediately useful for property investors,” Bailey said.
The LiveYield platform hosts an interactive map, which reveals the hottest buy-to-let
locations across the country. This real-time graphic allows investors an alternative way to
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Vol. 17 No. 5
search for buy-to-let hotspots. The heat-map is accurate to post-code level as is the index
which can be used to compare investment returns at a town, city and regional level.
It is features like this that Bailey is keen to develop further.
“Being able to understand how this investment class is performing versus alternative
options is of huge importance, yet most reports focus solely on capital growth and ignore total
return. The buy-to-let or PRS (private rented sector) as institutional investors call it is a huge
asset class valued at circa 1.2 trillion U.S.. To put this into context, it is 1.3 times the size of
the commercial property market, yet is dominated by private individuals. We hope to develop
a platform offering institutional level insight of this sector to the individual,” Bailey said.
Both Zoopla and Rightmove jumping on Big Data bandwagon
The major property portals in the U.K. are steadily increasing their data resources for
home buyers. Vertical leader Rightmove recently extended its indexing work to the letting
sector and a Rental Trends Tracker to its quarterly publications. Second-placed Zoopla is proactive in terms of using its data and providing tools to help people understand the value of
their home and their local area.
LiveYield aims to fill the niche area of buyers seeking properties specifically for investments.
“Owner occupiers and investors are driven by different factors; the former is more subjective and emotive, whereas investors should focus on financial performance,” Bailey said.
The site is free for end users as the business model is based on lead generation for Zoopla and affiliate marketing. It currently partners with London & Country, one of the U.K.'s
largest independent mortgage brokers and is exploring other ways in which it can generate
revenue from its market intelligence.
As information becomes cheaper to provide and Big Data solutions create an opportunity for instant and increased market data for the masses, Big Data will change the property investment market. Great investment deals will no longer be the preserve of specialist industry
insiders with large budgets for researchers and analysts.
Bailey said he does not see a single moment but a gradual shift that will allow more investors and operators to benefit from the information available.
“One of the key features of the property market is that each asset is unique –- there
are no shortcuts in due diligence once an investment is found. However, additional transparency in the marketplace can help build understanding, confidence and enhanced decisionmaking in finding a property investment,” Bailey said.
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Vol. 17 No. 5
Science helps AirBnB take flight
Pesonalized search aids in rental site’s rapid growth
The travel accommodation major uses machine learning to detect host preferences and predict rebooking.
Consumer-friendly technology has been at the heart of AirBnB’s business model. With
more than 40 million monthly visits according to SimilarWeb, the apartment rental site has
many valuable lessons for real estate verticals.
One valuable example is that AirBnB embeds data
science into all of its business functions.
Data is more than numbers, it is people
“Defining how we think about data is a prerequisite to ingraining data science in business functions. Data
isn’t numbers, it’s people,” said Riley Newman, Head of
Data Science at the company.
Newman joined AirBnB in May 2010, as one of its
first 10 employees and has helped the company scale to
its current size.
“In the past, data was often referenced in cold, numeric terms. It was construed purely
as a measurement tool, and requests would come in the form of a request for a fact: how
many listings do we have in Paris? What are the top 10 destinations in Italy? But now data scientists at AirBnB collect and use data to optimize products, identify problem areas, and inform business decisions,” Newman said.
While measuring things is certainly part of the data scientist’s job, at AirBnB they characterize data in a more human light.
“It’s the voice of our customers” Newman said. “A datum is a record of an action or
event, which in most cases reflects a decision made by a person, if you can recreate the sequence of events leading up to that decision, you can learn from it.”
This view of data is what has delivered AirBnB to its colossal position as the World’s
largest marketplace for accommodation in only six years.
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Vol. 17 No. 5
AirBnB exists to match people looking for accommodation with people looking to rent
accommodation. A match only happens if a host is willing to accommodate a guest. Knowing
which guests are most likely to accept a booking and presenting that information first makes
the search more efficient and increases the likelihood of a booking.
Predicting a host’s preferences started out as a small research project but ended up as
the development of a machine learning model. Every time a guest enters a search query on
AirBnB’s search engine, a model computes which hosts will most want to accommodate the
guest’s request. Early testing of the predictive data model resulted in a four percent increase
in booking conversion.
AirBnB started to personalize its search, but in a two-sided marketplace, it also had to
personalize the search by the preference of the hosts.
It set out to associate a host’s prior acceptance and decline decisions by the following characteristics of the trip: check-in date, check-out date, and number of guests. By
adding host preferences to a ranking model that captures guest preferences, it hoped to get
more and better matches.
The result was a first fully fledged personalization search signal that proved to
be a sizable contributor to AirBnB’s growth and success.
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Vol. 17 No. 5
Can a data scientist predict if a guest will re-book?
AirBnB also uses data to predict if a guest will rebook. It looks at guest ratings and in
particular how the Net Promoter Score (NPS) adds value. By measuring customer loyalty, as
opposed to satisfaction with a single stay, an NPS surveys aims to be a more effective method
to determine the likelihood that the customer will return to book again, spread the word to
their friends, and resist market pressure to defect to a competitor.
NPS is a widely used customer loyalty metric and data
gathered from this rating along
with guest reviews such as cleanliness, check-in, communication,
location and value can measure
customer loyalty with a single
stay. AirBnB said the NPS metric
to its guest review form in 2013.
AirBnB looked at its data
and found that a higher NPS does
correspond to more referrals and
re-bookings. It then tried to predict if a guest will make another booking with AirBnB, up to one year after the end of the first
trip and what other factors might influence rebooking rates.
From the analysis of 10 weeks of data, it found that that rebooking rates are seasonal. This is likely because more off-season travelers tend to be loyal customers and frequent
travelers.
The travel major also studied which subcategories of questions are most predictive of
rebooking. Adding any one of the subcategories improved its model. By repeating the process,
incrementally adding review categories to the model, AirBnB can accurately predict if a guest
will rebook again in the next 12 months 56 percent of the time.
Given just basic information about the guest, host and trip, it improves predictive accuracy to 63.5 percent.
Surveys and machine learning tools have not yet become a staple of the classified business, but companies that are able to predict consumer actions and use this information correctly are likely to be in a stronger position than their competitors.
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Vol. 17 No. 5
IProperty, PropertyGuru vie for No. 1
Data drums up dollars for Southeast Asia companies
The two Southeast Asian heavyweights explain their number-crunching processes.
Southeast Asia is witnessing two Big Data pioneers square off for regional dominance in
the dynamic local real estate market.
Malaysia-based IProperty (recently acquired by REA Group) is pitting its PropertyIQ system against Singapore’s PropertyGuru and its EPropertyTrack database.
IProperty owns real estate verticals that are market leaders in Malaysia, Thailand, Indonesia and Hong Kong, as well as a leading platform in Singapore. The company has dedicated six people to its Big Data department and is focusing on rapid delivery of information to
users via its PropertyIQ offering.
“We are using data for three primary reasons, for developers to sell faster, for advertisers to sell faster and for agents and homeowners to sell faster,” IProperty CEO Georg
Chmiel said.
Chmiel believes that his company is providing a Big Data offering based on live information that the users really want, and not “highly unreliable” historical transacted data.
Meeting the needs of developers has driven data development
In Malaysia, IProperty records more than 1 million live searches every day. The company combines this information with demographic and transacted data to drive insights. The service is highly customized to what the developer wants, which phase the developer wishes the
service to perform and the required data they need.
“The inspiration for our Big Data piece was that we noticed developers were coming in
at a late phase, and asking to buy a banner. We wanted to serve them at earlier phases, and
to come in earlier we needed to provide a different service,” Chmiel said.
For e-mails and newsletters, the company uses data to segment receivers, resulting in
a five-time increase in the quality of response rates and leads. “This makes the ROI a much
better proposition for the developer as they can attribute source and value-added accordingly,” Chmiel said.
IProperty considers Big Data an intelligent way of building opportunities and is embedded in every part of their business. Initial implementation took approximately one month, requiring an upgrade of servers to handle the data that was coming in, while data analysis has
always been done in-house.
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Vol. 17 No. 5
There are currently more than 1 trillion data sets already in their database. The company has more than 1.2 million contact details of consumers with demographic information for
marketing activities. Mobile has become a major part of this data network.
“The great thing about mobile is that it generates lots of data and is always with you
and always online. With location services, we can even do live interaction with the developer.
With more and more data, the portal can suggest options to the user. The days of spamming
and mass marketing are over. We now understand the consumer much better and can provide
a useful platform for all parties,” Chmiel said.
Behind its competitor, but as progressive in data usage
PropertyGuru has a similar Big Data approach to IProperty, perhaps learning from the
regional leader in an attempt to narrow its lead in Thailand and Indonesia.
“We do lots and lots of back-end data crunching. We have 125 million monthly page
views, tens of millions of searches and 500,000 enquiries generated via the platform every
month — resulting in over $12 billion U.S. of property transactions per annum. Our data science team supports internal business intelligence, product performance, marketing performance and product development,” PropertyGuru CEO Steve Melhuish said.
Supporting data mining efforts, PropertyGuru has developed and launched 15 mobile
applications in four countries and three languages. At present, the company has recorded over
2.8 million app downloads. In the past two years, PropertyGuru has launched more than 10
products and enhancements to help consumers make better property decisions. These include
FloorPlans, a listing quality ranking algorithm; SmartSelect, a research engine for easier property comparison; Agent Insights, a system that delivers personalized insights to customers
through automated program; and a suite of financing tools and calculators.
“Data and analytics is a key area of focus and constant innovation for us. We currently
have roughly 500 new projects from more than 100 property developers and more than 25,000
real estate agents using our EPropertyTrack solution in Singapore, Malaysia, Thailand, Indonesia and India,” Melhuish said.
Real estate developers collaborate in real time with all sales staff, instantly sharing
new marketing materials, videos, floorplans, site plans, virtual tours, pricing and so on.
Both PropertyGuru and IProperty are indicative of the Big Data buzz in Southeast Asia,
which is becoming one of the leading classified data hubs among emerging markets.
Real estate in particular has benefited from booming property markets in Singapore and
Hong Kong — city-states that are also home to tech hubs and specialists key to building Big Data expertise.
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Vol. 17 No. 5
French sites say ‘Oui’ to retargeting
Service provides realty platforms with better leads
Local majors such as Vivastreet and SeLoger focus on quality leads.
BY ANASTASIA GNEZDITSKAIA
French classified sites are increasingly using Big Data in retargeting.
As the online real estate business becomes more about quality, not quantity of leads,
data-driven retargeting services are highly sought-after by property sites.
France’s No. 3 property site Logic-Immo.com has established a special partnership with
Paris-based
retargeting
vendor Criteo
recently to
take advantage of its
algorithm for
ads. When a
Logic-Immo
user visits a
portal, it establishes a
cookie, thus
offering this
particular user certain ads
from partner
sites, particFor Logic-Immo, 23 percent of traffic currently arrives through retargeting. ularly platforms of real
estate professionals.
Based on this partnership, retargeting technology sets Logic-Immo apart since real estate professionals could not use it individually on their sites as they do not generate enough
traffic (which should be at a minimum of 50,000 unique monthly visitors). For Logic-Immo, 23
percent of traffic currently arrives through retargeting.
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Vol. 17 No. 5
Cyril Janin, the GM of Logic-Immo, has said in a statement that the company identified
the potential of this technology in the property sector, which was an undertapped segment
previously.
According to Antoine Krier, the CEO of French technology company Ubiflow, this
choice was quite fruitful for Logic-Immo as it sold 800 properties in first six months of using
Criteo’s retargeting technology (his full analysis available here in French).
Email targeting also entering the French classified scene
Apart from ad retargeting, Logic-Immo has recently adopted an email retargeting service, also provided by Criteo. Depending on the behavior of a user, he or she receives a property-related promotional email. Only around 30 percent of property platform users in France
usually allow the option of receiving emails.
The new product, called Pushimmo, has just been launched by Logic-Immo.
“We have exclusivity with Criteo for Pushimmo, which means that other French property sites can use email retargeting as well, but only for their site, while we can use it for other
client sites, such as for sites of real estate agencies that work with us,” Eric Sarim Director of
Telesales at Logic-Immo, told the AIM Group.
Vivastreet France, the second largest generalist classified site in the country, is also
relying on retargeting services provided by Criteo,
“Criteo delivers targeted ads based on an individual's previous engagement with Vivastreet, such as a jobseeker appliying or consulting job offers on Vivastreet, and once he
leaves the website, we show him similar ads on other websites,” Julien Andre, the Head of
Vivastreet Jobs, said.
Apart from retargeting, French property platforms have other applications of datadriven monitoring of user navigation.
France’s second largest property site SeLoger uses Big Data to analyze leads as a special service to real estate agents. It scores leads based on how likely they are to buy a property, while also combining user information based on their historic actions, such as whether a
user has signed up to the email alert system or not.
For some of this analysis, SeLoger uses a Paris-based data agency called ‘55’.
“They have worked for us mainly on two topics. The optimization of user interfaces via
dedicated multi-variant testing methodologies, essentially AB testing with multiple combinations. And secondly, the enrichment of our end users’ CRM data. We were satisfied with the
results,” Roland Tripard, CEO of SeLoger, told the AIM Group.
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Vol. 17 No. 5
Recruitment
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Vol. 17 No. 5
Checkr adds background checks
Technology allows screening before resume arrives
The San Francisco-based vendor has raised $30 million U.S. on the back of its screening
technology.
BY BRIAN BLUM
For a number of job types, background checks have become an integral part of the recruitment and hiring process. San Francisco-based Checkr is hoping its screening technology
can be adopted across the classified space.
Usually these checks conducted by a company’s HR department once an application has
been received and includes reviewing DMV and criminal records. It is a time-consuming and
expensive process, especially if a local county clerk hasn’t fully automated the records database. If the applicant fails the background check, it amounts to considerable wasted time for
the recruiter.
What if the screening could take place before a resume ever arrived at the hiring company, say, as part of the pre-submission workflow of an online classified job board? During the
past six months, Checkr has been having discussions with several classified companies to
achieve exactly that, according to the company’s Head of Business Operations Pascal LevyGarboua.
Breaking new ground in classifieds
Working with classified sites is a bit of a stretch from Checkr’s current business model,
which involves offering background checks to hiring companies through an API or standalone
dashboard for between $25-$35 U.S. per applicant.
Still, if Checkr succeeds in cracking the classified job space, even with a few small sites
to start, it would be a telling example of how using Big Data smarts can save hiring companies
money and provide additional revenues to classified publishers who could take a cut of Checkr’s processing fee.
Kathryn Rudnay, whose company operates a third-party food delivery service that sent
more than 5,000 drivers through Checkr’s screening system in 2015, was enthusiastic about
the classified possibility.
“We love Checkr,” she told the AIM Group. “We’ll get a response back from them in one
to two days for most of the drivers we put into the system. With some slower county clerks, in
can be up to three to five days. If we could get all this done before a driver submitted an ap© 2015 Advanced Interactive Media Group LLC
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Vol. 17 No. 5
San Francisco-based Checkr is hoping its screening technology can be adopted across the
classified space.
plication, it could save a lot of potentially wasted time. And as a small company, time is not
something we have a lot of!”
Checkr scans thousands of data sources to check applicants’ backgrounds, including motor vehicle and driving reports, the terrorist watch list, the sex offender database, social security reports, eviction notices, and relevant criminal records, all based on an applicant’s location.
Much of the data arrives through public feeds, but for certain localities Checkr actually
has to send a staff person to the county clerk’s office to manually secure the required information.
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Vol. 17 No. 5
Screening is a huge industry with existing majors
Background screening is a $4 billion U.S. industry, according to Levy-Garboua, and
Checkr knows it can’t compete directly against majors such as HireRight (45 million applicants screened), or First Advantage (9 million).
“A huge company like Penske [which sells and rents trucks] will build its own Applicant
Tracking System (or ATS),” Levy-Garboua said. That ATS will include hooks into one of the big
screening companies.
Checkr, on the other hand, is aiming at mid-tier companies that don’t have their own
systems in place or “that are building a mini, light-weight ATS.” he said. Checkr’s API is intended to make integration with these kinds of systems easy.
Levy-Garboua estimated that it would take a classified publisher “more than a week of
engineering time” to integrate the Checkr system.
Canada’s recruitment vertical Workopolis already offers a white labeled ATS system to
employers through its partnership with vendor iCIMS. It does not include background screening yet.
“We are seeing more and more classified companies starting to realize they need to
provide more added value to stand out,” Levy-Garboua emphasized.
Checkr is exploring a second pathway into the classified industry, offering what LevyGarboua calls “affordable lightweight safety checks for P2P in-person transactions.”
He’s thinking of mobile marketplaces like Letgo or Close5, which stress user safety as
part of how they differentiate themselves from Craigslist. Conversations with such companies
are also going on, Levy-Garboua said.
Investments of almost $40 million U.S. provide a strong base for growth
Checkr had already raised a Series A round of $9 million U.S. in venture funding led by
Accel Partners shortly after its launch, and in Oct. 2016 became the first investment for Y
Combinator’s new Continuity Fund with a $30 million U.S. Series B round.
Checkr has 3,000 customers and has run background checks on more than 2 million applicants since the company started. Their largest non-classified customer is taxi upstart Uber,
while also working with companies like Wonolo, which places hourly workers into last minute
and seasonal e-commerce jobs such as data entry, customer service and packaging.
Can classified companies and mobile marketplaces integrate background screening into
their application workflow and help their customers bypass that part of the hiring nightmare?
We’ll check back with Checkr in a few months.
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Vol. 17 No. 5
Job seekers turn to a hire power
Zhaopin mines data to measure career life cycle
Zhaopin is breaking ground in a market still heavily reliant on traditional resumes.
BY DONALD GASPER
International experts are split on whether the specialization required for executive recruitment lends itself to Big Data.
Some recruiters say there is enough volume of data for it to be usable. Others believe
that over time the dataset an organization holds on senior management hires would become
statistically valid.
In China, however, Big Data has already emerged as a crucial tool used in recruitment,
including executive recruitment.
Data in recruitment is key for a nation obsessed with reputation
“Data is everywhere,” said Robin Young, founder and CEO of Seedlink Technology
Holdings, a Shanghai-based startup.
“What really matters is how you analyze the data.”
Young said that most recruiters in China still rely on resumes and
cannot predict performance at all.
His own firm aims to replace
traditional resumes by providing recruiters with smart technology with
which they can interview job applicants through their mobile phones.
The firm uses a custom algorithm
that analyzes the answers given in
the interview and predicts which candidates are best suited for the job.
While Seedlink does away with resumes altogether, one Chinese job site is relying on its
database of resumes to steal a march on its competitors.
Zhaopin, a leading recruitment vertical in China focusing on connecting users with job
opportunities throughout their career life cycle, said it is now the No. 1 company in China in
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Vol. 17 No. 5
the recruitment space in terms of the number of registered users, unique customers and daily
unique visitors to its website.
“The quality and quantity of Zhaopin's users and the resumes in the company's database
attract an increasing number of customers,” said Daisy Wang Xingyu, the company's Director
of Investor Relations. “This in turn leads to more users turning to Zhaopin as their primary recruitment and career-related services provider, creating strong network effects and significant entry barriers for potential competitors.”
She said that the company's database holds the details of 110 million registered users
and 33 million active users.
Big Data helps Zhaopin clinch key partnership deal
Last September, Zhaopin inaugurated its annual National Employability Test (NET), developed by the company in conjunction with academic authorities from a number of universities. NET uses research based on its Big Data analysis that sampled tens of thousands of employers in order to build a model of how they use people with different skillsets.
When in Dec. 2015 Zhaopin announced a strategic co-operation agreement with insurer
Zhong An Online P&C Insurance, the company’s Big Data management capabilities and large
data pool were said to be factors that clinched the deal.
"This is a great example of how our Big Data analysis capabilities can expand business
horizons and better fulfill the needs of our job seekers throughout the different stages of their
career lifecycle,” said Evan Guo Sheng, Zhaopin's CEO.
The two companies said they would explore Internet financing opportunities that supported students and job seekers throughout their career life cycle, including an innovative
student loan initiative and a loan program for white-collar employees. This will help Zhaopin
further differentiate itself from its competition as it continues to evolve into a career development platform.
The company is looking to capitalize on Big Data to help accelerate its growth and will
leverage the data to create new solutions for employers, such as precision marketing. Part of
the strategy is to leverage its data pool to establish virtual assets for users, such as creditability and reputation.
“Our career-related data can be leveraged to reshape the transaction value chain for
other business categories,” Wang said.
Zhaopin is one of China’s brightest examples of a company evolving its service offerings
to deliver more value, which then open up opportunities across the country’s large human
capital management industry.
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Vol. 17 No. 5
Polish job boards unveil latest tools
Grupa Pracuj, GoldenLine vie for market dominance
Two players are betting on their data analysis to fight for market supremacy.
BY ANDRZEJ SOWULA
Poland’s leading recruitment verticals are implementing advanced recommendation
tools to stand out from the competition.
Grupa Pracuj, the owner of Poland’s leading job site Pracuj.pl and Ukraine’s leading
job site Rabota.ua, has launched its recommendation tool under the name of Pracuj Select.
Recruiters who use it receive recommended profiles of people who
have not responded to their job offers, but fit the requirements.
Grupa Pracuj is the owner of Poland’s leading job site
Pracuj.pl and Ukraine’s leading job site Rabota.ua.
Pracuj’s users can switch the
option to have their profiles recommended to employers on or off.
They can also mark companies to
which they do not want to be recommended (like their current employer). In their profiles, users can
also see how many recruiters on
Pracuj.pl are looking for candidates
with their competences, which encourages them to stay up to date
with job offers.
“Pracuj Select is based on matching algorithms and is available free of charge to any customer who has published a job offer
on Pracuj.pl. The customer has access to it in the Pracuj Zone, which also aggregates all resumes sent to a particular new job offering,” said Rafał Nachyna, Managing Director at
Pracuj.pl.
Grupa Pracuj developed its new recommendation system using its own Product Development department, taking advantage of its three-year experience in the development of
recommendation tools. According to Nachyna, it is currently the most advanced system of its
kind on the Polish market.
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Vol. 17 No. 5
Nachyna revealed that only a few months after launching Pracuj Select and conducting
educational activities regarding this tool, 1.3 million Pracuj users have completed their professional profiles and 70 percent of their customers have used the tool.
Not all recruiters desire direct contact with passive profiles
However, Pracuj was not the first site that launched this type of solution locally.
GoldenLine (a Polish version of LinkedIn with around 2 million users) introduced its automatic system to recommend candidates to
companies in 2014. Yet employers wishing to
reach passive candidates are not so keen on using the site’s recommendations, according to
the company’s CEO Karol Traczykowski. They
prefer the candidate search engines.
“The mechanism of the search engine is
also based, among others, on the analysis of user behavior and suggests in the first place those
candidates who, in addition to meeting the required criteria, will most likely respond to the
job offers,” Traczykowski said.
GoldenLine has had this recommendation
system since 2014. Through it, the company obtains about 35-40 percent of all applications
sent in response to announcements published on the site.
In January, GoldenLine was acquired by
the Polish media group Agora.
“Thanks to the data contained in the profiles of over 2 million users and by statistical
analysis of their behavior and the similarities between them, we are able to adjust a job offer
to a specific candidate very well. Most beneficial is the analysis of user skill set and his/her
professional experience. We also verify a tendency to relocate — this option was introduced
by the end of 2015,” Traczykowski said.
In Jan. 2016, GoldenLine was acquired by the Polish media group Agora, which plans to
move its recruitment center to it, including its job board GazetaPracuj. The joint potential of
both sites allows Agora to think realistically about dethroning Pracuj.pl as the recruitment
leader in Poland. GoldenLine’s recommendation tools can prove to be a significant asset in
this venture.
“Thanks to the enormous reach of Agora's Internet sites we will expand the information
about users, especially in the field of behavioral analysis,” Traczykowski said.
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Vol. 17 No. 5
General
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Vol. 17 No. 5
Schibsted aims for ‘mini-Facebook’
Norwegian firm creating a single advertising network
The Norwegian giant is building a network of display ads, geo-fencing and e-payment
solutions.
BY LARS HERLIN
Schibsted has ambitions of building an international business system that uses Big Data
to group customers by category and sell those categories to advertisers.
Schibsted Media Group is a Norwegian communications giant that operates in 29 countries and has 6,900 employees.
Later this year, the company plans to offer worldwide buys on the Schibsted Ad Exchange, which will reach more than 200 million potential customers. Many of Schibsted’s publishers and classified sites are already available on the Ad Exchange.
Schibsted is using the private marketplace Appnexus Member 1860, so media buyers
must register at its partner company Appnexus to see the options.
Uniting its network to create one huge advertising offering
The head of Schibsted Sales in Sweden has talked of building a “mini Facebook” for the
Nordic countries, and Schibsted Chairman Jacob Sunde has declared Facebook and Google to
be the company’s main competitors.
Schibsted certainly looks like more of an international player after spending around $35
million U.S. in 2015 on new online products and technology development, including major recruitments from Twitter, Google and other international players.
At the same time, Schibsted has gone through an enormous consolidation. Many of its
companies were independent and handled their own data technology. Now, data is moving to
the cloud and both the publishing and classified divisions will use the same platform.
This also means centralizing the businesses. Local bosses do not know when the new
technology will be implemented, but all the Schibsted companies in Sweden have seen a huge
change this year in their advertising organization. All sellers now represent all of Schibsted
and work for Schibsted Sales & Inventory.
“It is now one customer and one seller contact from Schibsted who sells all our products,” the company’s Product Director Johan Åsen said. “All the site-specific departments
have ended, including Webtrafic, which was a leading programmatic sales organisation also
for companies outside the Schibsted sphere.”
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Vol. 17 No. 5
Several packages aim to maximize reach
The company has created a package called Schibsted Cross for display advertising while
Schibsted Premium is its main product that sells ad space on its 10 premium Schibsted sites:
Blocket, Bytbil.com, Prisjakt, Hitta, Aftonbladet, SvD, Klart.se, Omni, Alltomstockholm.se
and TV.nu.
But Schibsted in Sweden also uses the network that Webtrafic created.
“We continue to have the ability to offer exposure on sites and apps outside Schibsted
via a package called Schibsted Reach,” Åsen said.
In Schibsted Reach, the ads are also published on 40 sites outside the Schibsted empire.
Schibsted in Sweden is moving fast to sell audiences instead of specific sites. The ads
are targeted by geography, time, weather, retargeting and data driven audiences. A site like
Schibsted has ambitions of building an international business system that uses Big Data to
group customers by category and sell those categories to advertisers.
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Vol. 17 No. 5
Blocket (general classified leader in Sweden) is a valuable resource in giving the advertiser a
chance to meet the right customer.
Blocket uses outside sales companies like HiMedia and InternetBroker to sell specific
digital ads to small and medium-sized companies.
In Norway, Schibsted has kept its separate sales organisations.
“We have $117 million U.S. at stake in print advertising, something we have to guard
and therefore we cannot act as fast as in Sweden, where they do not have regional newspapers and less print money to worry about,” said Per Håkon Fasting, Executive VP of Advertising at Schibsted Norway.
Geo-targeting using all Schibsted resources
Geo-targeting in Norway is already advanced. Schibsted also uses software for geofencing, making it possible to reach people who are or have been in a certain area. This is
very interesting for retail advertisers.
“We have come pretty far in getting hold of users’ geo-location and can reach users
with ads from our digital inventory of display ads across all Schibsted sites. Doing this we can
reach up to 85 percent of people in certain parts of southern Norway,” Fasting said.
Schibsted is still far from having the simple advertising tools that Facebook and Google
publicly offer to businesses. However, self-service tools for display advertising are in the
pipeline. The plan is to implement the self-service first in Norway at Finn.no and then in Sweden at Blocket this year.
Schibsted has attained an EU e-money license
Google, Facebook and Apple all work with different payment solutions of their own.
Schibsted has worked hard to create its own log-in system, called SPiD. Now the company has
taken it one step further. The SPiD system now includes a digital wallet for peer-to-peer payments, including a secure escrow account.
Schibsted has been granted an e-money licence in Norway, which permits the company
to use the solution in all countries of the European Union.
Apart from the benefit of another online offering, a Schibsted-run payment system will
provide huge insight into user activity.
At this rate, Schibsted may emerge as Europe’s biggest competitor to Silicon Valley’s
digital giants.
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Vol. 17 No. 5
Adoos battles back from setback
Spanish classified firm rolling out data-centric app
The general classified is using user tracking data to challenge the market leader.
BY CILA WARNCKE
Big Data promises to create streamlined, intelligent and reactive companies. But can it
turn a moribund online classified into a profitable mobile-only brand? This is the question
Spanish company
Adoos is hoping to
answer in the affirmative.
A Google algorithm update caused a major loss of traffic and revenue at
Spain’s Adoos site.
Adoos began life in Spain in
2003 as a free
general classified.
Its founders bootstrapped Adoos
into a successful
business with sites
in Spain, Italy,
Mexico, Argentina
and Peru, using
AdSense revenue
and SEO search.
Then a Google algorithm update
caused a major
loss of traffic and
revenue.
"At one point we had 30 million users," co-founder and CEO Julian Martinez said.
"But we're back to a startup level."
Adoos had nothing to lose by trying something new.
"Wallapop (the Spain-based mobile-only marketplace) became No. 1 without a website," Martinez said. "Milanuncios.com was at the top of Google for every search and then
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Vol. 17 No. 5
Wallapop came in with just TV advertising, no SEO, and beat them. That convinced us: forget
about the web, let's go mobile."
This was an option thanks to Big Data. Adoos tracks every event that happens in its app,
learning the patterns of the people who spend the most time on it.
"We identify the patterns of our power-users," Martinez said. "Then we optimize the
whole site to encourage that behavior."
Adoos uses Amazon Kinesis to track events including searches, clicks and favorites. It
moves the data to another Amazon tool, Redshift, for analysis. Open-source software Hadoop
is used to process the data, which is then visualized in Looker.
"We don't operate on intuition anymore," Martinez noted. "We do an A/B test, run the
results and get real answers."
Adoos now caters to each user as a separate audience.
"If the user has done this, but not that, they will see a different app compared to someone who has done a different set of steps," according to Martinez.
The company's goal is to build a profitable relationship with its best users, and to turn
everyone into a "best" user. Adoos plans to focus on a single European market before commercializing the app in other countries. Its revenue model will be in-app purchase, with Adoos insuring the transaction.
"We're in the process getting funding to rollout the revenue model," noted Martinez.
Big Data analysis is a powerful tool and Adoos has a strong brand on which to build on,
but it faces an uphill battle against Wallapop, which has captured the imagination of consumers and investors alike.
A reported $140 million in funding makes it a formidable adversary.
Javier Ortiz, Head of Sales at major Madrid-based general classified Mitula, saw the
rise and fall of Adoos online.
"It was one of the best," he said. "The problem is they're coming in on a space that was
empty when Wallapop was launched. The mobile market is still growing, so if they find a solution that fits people’s needs they have a chance. But Wallapop is so strong that it may cost a
lot of money," he said
Martinez, however, is confident that Adoos has a strategy for success.
"We look at the data," he said. "We don't care about politics, we care about the right
answer."
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Vol. 17 No. 5
Big Data, bigger challenges
Frontier markets in South Asia face major obstacles
Industry insiders discuss the opportunities and challenges in Pakistan and the region.
BY TARIQ AHMED SAEEDI
Petabytes, exabytes and zettabytes — global data growth is exploding and soon we will
enter into an era of the yottabytes. How intelligently are classifieds in Pakistan and the wider
South Asian region approaching the Big Data revolution?
We talked to a number of data specialists and industry professionals observing the
trends to find out.
“When it comes to business intelligence, data-driven marketing and data-warehousing,
we can certainly say we are on the same level as developed markets such as Germany and the
U.S.,” said Philipp Loringhoven, Head of Data and Marketing Technology at Lamudi, a property listings site currently active in nine countries across Asia and Latin America.
Backed by global tech dynamo Rocket Internet, Lamudi has the advantage of sharing
technology with its headquarters in Berlin.
“However, every emerging market has its idiosyncrasies that require tailor-made solutions — we always develop these in cooperation with local experts,” Loringhoven said.
Lamudi’s user engagement activities are quite innovative. The site uses push notifications and extensive A/B testing to meet customer needs at the touch-point.
“We use many kinds of ‘heat mapping’ to understand how users interact with our product. We track bounces and time on pages, as well as site speed to ensure that users find their
way around the site easily,” Loringhoven said.
Data-driven initiatives help launch Pakistan’s first real estate price index
Some companies prefer to keep their solutions in-house.
“We were being persuaded by the businesses in the developed and emerging markets
to license out our marketing technologies and management tools,” said Imran Ali Khan, CoFounder and CEO at Emerging Markets Property Group, which runs leading real estate verticals Bayut in the UAE and Zameen in Pakistan.
However, Khan wants his company to focus on its core business and does not believe in
wasting time on customization for each of their businesses.
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Vol. 17 No. 5
Emerging Markets Property Group runs leading real estate vertical Zameen in Pakistan.
Zameen claims to have the biggest database of properties in Pakistan and it integrated
the country’s first Real Estate Price Index in Feb. 2016.
“Everything is data-driven. Maps are digitized. For example, if a customer looks for a
property in a location that has similar names in other cities then the results are based on their
IP address,” Khan said.
The philosophy behind the site’s CRM system is “everything should be measured.”
Another Pakistani player helping the market to mature is Mustakbil, the country’s oldest jobs vertical. The company is leveraging historical data to move content to the customer.
“When an employer searches our database for talent, we suggest candidates according
to their previous history. Likewise, when a job seeker looks for a software engineering job, we
show them other positions related to their skills and qualifications,” Mustakbil spokesman Waheed Ahmed said.
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Vol. 17 No. 5
Ahmed said that employers are provided with a dashboard where they can view stats,
graphs and other indicators. Resume uploads are not permitted; instead candidates must feed
inputs.
But Internet penetration remains a major roadblock
Personalization, semantic matching and programmatic advertising technologies are
gradually being integrated into the industry to augment the user experience and ramp up revenues.
However, classifieds in emerging markets are still far from cognitive computing to
mine insights from both structured and unstructured data.
Google Analytics, DoubleClick, Hootsuite and in-house tools are the main sources
of data collection.
Local classified executives say the cost
factor and broadband speed are barriers to
technology adaptation in emerging markets.
“One of the most important factors
for emerging markets lagging in this
space is the rate of Internet penetration.
Another factor hampering Pakistan and
Afghanistan’s growth in the Internet
business space is low literacy rates.”
— Khuram Rahat,
Managing Director, Teradata
“One of the most important factors for emerging markets lagging in this space is the
rate of Internet penetration,” said Khuram Rahat, Managing Director at international data analytics provider Teradata.
Rahat said that businesses like EBay and Amazon have based their complete business on
data warehousing using the customer profiles, contextual marketing, shipping preference and
product affinity analysis. Copying that model in emerging markets is a challenge since in countries such as Pakistan and Afghanistan the majority of the population remains offline.
“Another factor hampering Pakistan and Afghanistan’s growth in the Internet business
space is low literacy rates,” Rahat said.
Many of the smaller classified players do not feel the need to use business intelligence
tools or data warehousing, as the markets are simply not mature enough and finding adequate
IT personnel is a challenge.
For some, simply marketing aimed at encouraging consumers to come online is sufficient investment. In frontier markets like Pakistan, Afghanistan and Bangladesh, Big Data is
reserved for major international holdings and market leaders.
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Programmatic ad buying
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Vol. 17 No. 5
Swiss sites integrate targeted ads
Tamedia, Ringier adapt to spread clients’ message
Tamedia and Ringier employ contrasting but data-centric approaches to their ad networks.
BY CRISTINA COSTA
The rapid evolution of Big Data technology is disrupting the digital advertising world,
while boosting industry growth. Programmatic — the real-time automation of buying, placing
and optimizing media inventory in online advertising — is part of a coming transformation.
Instead of sending a message into the atmosphere, advertisers will be able to direct an
ad straight to their preferred customers, whose digital addresses are cataloged and analyzed.
Programmatic ad buying in Europe is not a niche segment anymore. Questions remain
about where this development will take the industry, but data on Europe released in Sept.
2015 by IAB show a 70.5 percent revenue jump on the year before for programmatic to a market volume of 3.6 billion Euros.
Ringier launches new platforms to improve digital sales
Switzerland has a consolidated classified situation, with
only two strong players, Ringier
and Tamedia. Both regional majors have invested large sums in
online classifieds and are adapting their strategy to put their ad
buyers’ messages in front of
customers most efficiently.
Ringier Digital launched in July 2015 with Scout24 Mediaimpact, a new company for its subsidiary Scout24
Switzerland.
Ringier Digital launched
in July 2015 with Scout24 Mediaimpact, a new company for
its subsidiary Scout24 Switzerland (which operates several
classified verticals), to improve
digital sales on its classified sites.
Scout24 Mediaimpact Director Andreas Gran is aware of the influence of data-based
programmatic ads on classifieds.
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Vol. 17 No. 5
“Programmatic buying of display ads is for us currently an additional revenue source,
which we are handling with caution, since it has to match our users and our classified needs,”
he said.
Scout24 partnered up with U.S.-based Sell-Side-Platform (SSP) provider PubMatic in
Feb. 2015.
“We opted to make a smooth entry into the programmatic buying and selling of digital
inventory on
classified sites
to avoid jeopardizing our
growth in direct sales,”
Gran said.
Scout24 partnered up with U.S.-based Sell-Side-Platform (SSP) provider
PubMatic in Feb. 2015.
Currently, more than
80 percent of
Scout24’s ad
sales are made
by one-to-one
sales to advertising custom-
ers.
“It was important for us at the start to maintain control over our advertising inventory.
That´s why we marketed automated deals first only exclusively for our IAB standard ad inventory, leaving on purpose premium placements out,” Gran said.
Pubmatic developed two channels for Scout24: a Private Marketplace (PMP) for the premium inventory on Scout24 portals and a separate Open-Auction Real-Time-Advertising (RTB)
platform, on which Scout24 makes the regular inventory available for auction buyers like Demand-Side-Platforms, Ad Networks and media agencies.
“Bidders do not know on which of our verticals or marketplaces their display ad will
pop-up, just that in real-time they are getting a maximum reach of the targeted audience,”
Gran said.
At present, around 20 percent of Scout24’s inventory, representing several million ad
impressions per month, is available on Open-Auction Real-Time-Advertising.
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“It’s a win-win-situation for our premium clients, and us, because it’s possible to fix a
reserved share for our premium clients of Scout24’s inventory,” Gran said.
To aggregate maximum reach, Scout24 enriches its audience by adding sites from Ringier’s portal network. As Scout24 uses the smart data management platform from nugg.ad, it
provides factual and predicted behavioral audience targeting data.
Pubmatic claims in a case study (BDVW Programmatic Kompass 2015/16) that Scout24
already is generating 25 percent of its total online advertising revenues through the provided
private marketplace.
Floor prices for programmatic advertising on Scout24’s classified portals range between
10 and 15 Swiss francs per CPM.
In its next move, Pubmatic intends to implement an “Automated Guaranteed-Channel”
and start later this year a mobile programmatic advertising solution for Scout24’s ad inventory.
Tamedia’s approach focuses on optimizing sale price
Fellow Swiss media group Tamedia (which owns a number of general and vertical classified brands in Switzerland and beyond) has followed a different approach. After dealing first ad inventory impressions one by one in
a waterfall principle to buyers,
Tamedia introduced Improve Digital’s 360 platform in July 2014,
with access to around 3,500 buying
partners for holistic ad inventory
optimization.
Tamedia introduced Improve Digital’s 360 platform in
July 2014.
With this step, Tamedia’s
programmatic media sales unit
aimed to improve their current set
-up to ensure the highest price per
impression and an increase in yield.
“Products are the same in direct sales and in real-time advertising, which means our
pricing strategy is similar to the one of our direct sales,” said Rui de Freitas, head of RealTime-Advertising & Yield Management at the company, responsible for the implementation at
Tamedia’s programmatic media subdivision.
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Differing from Scout24’s approach, Tamedia opted for competition between direct ad
inventory sales for large campaigns and programmatic budgets placed through Deal IDs and
Open RTB. Only high-priced direct sales campaigns with a granted volume are left out and
dealt through an Ad Server, while all other ad impressions are holistically optimized.
“With this strategy we could assure that each ad impression was dealt to the highest
possible price,” de Freitas said.
Media agencies have also an option to book low rates and broad reach Run-on-Sites
(ROS) and Run-of-Network (RON) advertising campaigns through Tamedia’s Open RTB platform.
“We started a separate RTA first only on our news sites, then we included step after
step non-news sites like classified site Tutti.ch,” de Freitas said.
Unlike Scout24 for any of its sites, Tamedia offers also Open RTB mobile programmatic
media buying on Tutti.ch, using Rubicon Project as its technology provider. Here, floor prices
for mobile ads range between 5 and 7.50 Swiss francs.
In Feb. 2015, Tamedia launched a new “Intent Targeting” solution for advertisers for its
Premium Publisher Network (PPN), that covers 30 Tamedia sites, and which allows user targeting and tracking from classifieds sites (autoricardo.ch, tutti.ch, homegate.ch and marketplace ricardo.ch,) similar to that of Scout24’s Live-Data-App.
Tamedia also offers programmatic buying solutions for its leading Swiss ad network
“Premium Publisher Network” (PPN), which comprises of around 30 websites of Tamedia and
its partner Ticino Online.
Programmatic and Big Data must be combined for maximum effect
Both Ringier and Tamedia are following a global media trend.
As industry analyst Ken Doctor concluded in his report on Axel Springer’s transformation challenges: “Data is the new ‘paper’ for media companies in the digital world. The
linkage among digital reader revenue, ad revenue and classifieds is valuable, actionable, previously collected smart data.”
Classified companies approach Big Data in the digital world as many actionable points
of information about millions of individuals. Programmatic media and Big Data are both intrinsically interconnected.
“Big Data is on our agenda as a top topic, since our clients are demanding more and
more actionable high value data on audiences and looking for placements of new rich media
ad forms,” Gran said.
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Recruitment ad revolution is near
Job verticals begin warming to data, technology
Job verticals are only just starting to use data and sophisticated software to enhance ad
placement.
Programmatic advertising delivers dramatically higher returns on investment and allows
a targeted and timely approach of ads placement, yet recruiters have thus far let this medium
of advertising pass them by.
According to Chris Forman, CEO of Appcast, a platform for programmatic recruitment
advertising, programmatic ad buying now represents 60 percent of the total online ad spend
outside of the job space, while in the job space programmatic ad buying accounts for zero
percent.
A report by MAGNA Global reveals that global programmatic media transactions will
reach $21 billion U.S. this year and growth will remain strong over the next four years, with
an average annual growth rate of 27 percent, reaching $53 billion U.S. by 2018.
Recruitment on the cusp of programmatic adoption
There are many reasons why the recruitment space has been slow to embrace technology and data learning, but it is primarily due to the lack of a technological framework in the
industry.
This is set to change, according to Foreman.
“The recruitment ad space is about to go through a revolution. If you look at what’s occurred in the online consumer space, you‘ve seen a radical shift in how ads are purchased and
deployed on the web. Organizations are starting to use data and sophisticated software to
make sure their job ads are at the right place at the right time to be in front of the best candidates,” he said.
The revolution will bring changes for job ads. Advertisers have until now been paying
large sums of money on cost-per-click advertising, but now companies like the Appcast platform enable employers and their recruiters to advertise open jobs on a pay-per-applicant basis across a network of thousands of career and consumer sites.
“It’s time for recruiters to follow the lead of professional marketers and allow software
and data to drive the best placement of their ads. If recruiters can leverage this technology
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just like marketers, it will deliver a dramatically higher return on investment, and will allow
for a more targeted approach to placing job ads,” Foreman said.
Forman sees the pay-per-applicant model as the next natural step in the industry evolution, believing the product has the potential to change the way employers purchase recruitment media. He cites Google AdWords as an example, the performance-based advertising medium that charges for results rather than upfront cost, and which has now become the norm
in most job search engines.
Ad data specialists are becoming visible in classifieds
Appcast bills itself as the first pay-per-applicant job ad exchange in the $5 billion U.S.
recruitment advertising space.
“In just 18 months of being in business, we have nearly 200 enterprise clients,” Forman
said.
Other players using Big Data in recruitment include Onrecruit, which has built a product for job aggregators and job boards that makes its technology available as a white label
solution for clients. It claims its Ad Manager Platform is the first self-service tool for corporate employers and recruitment agencies to manage pay-per-click campaigns in job search engines, with real-time conversion reporting per vacancy.
For large recruiters, the Netherlands-based company has developed a tailor-made spider script that automatically scrapes the vacancy content directly from a client’s corporate
website and shows it across specialized job search engines, such as Indeed, Jobrapido and
Simplyhired.
Groups of vacancies can be defined and recognized such as IT vacancies or financial vacancies and budgets can be allocated per vacancy group. New and expired vacancies are automatically recognized and will not be shown in the search engines.
Recruitics, a New York-based company, is pushing the Big Data recruitment frontier
with the introduction of its marketing analytics and automation platform.
The platform processes millions of analytics and leverages the latest generation of Big
Data technologies to drive optimal recruitment results. It claims to be able to track everything on a job site and build rules to optimize any marketing metric or job segment.
Big Data is coming to recruitment, as trends show more job seekers are turning to job
search engines and social media rather than opting for traditional job boards. Thus, it is more
important than ever that hiring managers understand search motivations and can effectively
target the best candidates by learning from performance-based campaigns.
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Dutch embrace programmatic ads
Classified platforms accepted new tool early on
Local classified businesses have built up strong partnerships with vendors and advertisers.
The Netherlands is among the most developed markets in Europe for programmatic ad
buying.
According to IAB, this is due to “a combination of early adoption with the working cooperation of buyers and sellers”
alongside “an openness and consistency towards innovation.”
The country is home to a
multitude of rich media vendors
and rich media exchanges, which
offer buyers and sellers opportunities to programmatically trade
ad formats previously restricted
to directly sold campaigns.
Accordingly, Dutch classified platforms have a possibility
to take full advantage of datadriven programmatic buying.
Media company Telegraaf Media Groep works actively
with programmatic ads for its classified sites such as real For example, local media compaestate platform Jaap.nl, one of the leading property ver- ny Telegraaf Media Groep (TMG)
ticals in the country.
works actively with programmatic
ads for its classified sites such as
real estate platform Jaap.nl, one of the leading property verticals in the country.
Arjaan Schilder, Online Marketing Manager at Jaap.nl, told the AIM Group that his company has many advertising opportunities with “huge” targeting possibilities.
“Basically, advertisers can target every specification home seekers can use on our website, such as geo-targeting, rent/buy, living space, and so on. Furthermore, they can buy traffic via a direct campaign or programmatic buying.
Jaap.nl has its own marketing team to support advertisers and we have partnerships
with a couple of programmatic systems,” he said.
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TMG launched automated trading for video ads in 2013, and more than 70 percent of
advertising at the company is currently done via real-time bidding.
In terms of specific vendors, JAAP uses the programmatic systems of TMG partners
Semilo and Platform 161, Schilder said.
Amsterdam-based Platform 161 provides
advertisers with a buying tool, which allows buying digital media and displaying ads in an automated and real-time way.
It enables classified sites to combine programmatic buying and the premium display of
ads. It operates large amounts of ad visibility data and offers a decision algorithm to help marketers make advertising decisions.
The company uses Big Data to see how and where users interact with its ad inventory.
According to Dutch publication Emerce, Platform 161 is “the first independent software
vendor that enables companies in the digital marketing arena to optimize the efficiency of all
inventory sources.”
It offers media companies ad serving, targeting and audience collection, access to inventories and a CRM tool. Through a special tool provided by Platform 161 called Jedads, TMG
offers players a service of buying an advertising space through an auction, on a cost-per-click
basis.
De Persgroep, a media company that owns leading classified platforms in the Netherlands and Belgium, is also using Platform 161. According to Jeroen Swiers, Digital Sales Development Director at De Persgroep,
Platform 161 enables users to
quickly switch among custom features, and can work with budgets
of various sizes.
Apart from programmatic, De Persgroep collects Big Data on content consumption, payment activity and contacts with the help of Oracle’s Big Data Appliance.
This vendor “incorporates the Cloudera distribution of Hadoop and was the most cost
effective by far, requiring less administration. As an engineered system, it was very easy to
install, enabling us to show value to the business in a very short time,” said Luc Verbist, CIO
of De Persgroep.
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Big Data vendors
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AIM Group’s supplier directory
Classified companies need to find the right partners to work with. Below you will find a
selection of Big Data vendors.
Advertising/Marketing
Adform, http://www.adform.com
Adform is a media agnostic tech vendor for media agencies, trading desks, advertisers and publishers that offers
the world’s only programmatic brand-led media platform
supporting all aspects of multi-screen brand advertising.
The Adform tech stack includes a demand side platform,
third party ad server, data management platform, private marketplace, programmatic publisher ad server and a robust creative suite.
Adwebster, http://adwebster.com/
Adwebster is the largest digital advertising network in Switzerland that uses RTB technology.
Known classified customers: Scout24.ch
AppNexus, www.appnexus.com
AppNexus is a technology company that provides trading solutions and powers marketplaces
for Internet advertising.
Known classified customers: Schibsted Media Group, mycareer.com.au
Criteo, www.criteo.com
Criteo is a listed company specialized in digital performance advertising. It works with Internet retailers to serve
personalized online display advertisements to consumers
that have previously visited the advertiser's website.
Known classified customers: Logic-Immo, VivaStreet
SmartAdServer, www.smartadserver.com
Fully-integrated ad server for managing RTB, Mobile, Video & Web display. Manage all your
campaigns in one interface.
Appcast, https://www.appcast.io/
Appcast is a platform for programmatic recruitment advertising.
Known classified customers: Indeed, myJobHelper.com, JobServe, Jobs2Careers, JuJu
Online Recruit Group BV-OnRecruit, http://onrecruit.eu/
OnRecruit optimizes a job board’s pay per click advertising for jobs in all job search engines
through programmatic job advertising.
Known classified customers: CareerJet, Glassdoor, Indeed, Jobrapido, SimplyHired, Trovit,
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Adzuna, Recruit.net, Jooble
Recruitics, http://recruitics.com/
Recruitics is a recruitment marketing analyticts and optimization platfom that combines an
automation platform with agency services.
Known classified customers: JobRapido, Indeed; Glassdoor, DirectEmployers, Careerbliss, Diversityjobs, StartWire
Data Analytics
55 The Data Agency, http://www.fifty-five.com/
Fifty-five helps collect and organize data to let customers monitor and optimize the performance of digital assets and acquire and retain customers more efficiently.
Known classified customers: SeLoger, VivaStreet
Amazon Kinesis, https://aws.amazon.com/kinesis/?hp=tile
Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Known classified customers: Adoos
Amazon Redshift, https://aws.amazon.com/redshift/?hp=tile
Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that makes it simple
and cost-effective to analyze data using existing business intelligence tools.
Known classified customers: Adoos
CGI, https://www.cgi.com/en/business-intelligence-services
Founded in 1976, CGI is one of the largest IT and business process services providers in the
world. In analytics it offers expertise, solutions and partnerships using its Data2Diamonds approach to simplifying data management and realizing value from analytics.
Cloudera, http://www.cloudera.com
Cloudera is offering a new approach to enterprise data
management by offering a unified platform for Big Data, an enterprise data hub built on Apache Hadoop™.
Known classified customers: Ebay, AutoScout24
HortonWorks, http://hortonworks.com
The Hortonworks Data Platform provides an open platform that deeply integrates with existing
IT investments and upon which enterprises can build and deploy Hadoop-based applications.
Known classified customers: TrueCars, Ebay
Lotame, https://www.lotame.com/
Lotame’s SaaS data management platform is used by marketers, agencies and publishers to
make audience data meaningful and actionable.
Known classified customers: Pistonhead, WhatCar, AutoCar
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MapR, https://www.mapr.com
MapR provides a Big Data platform that combines the processing power of the top-ranked Hadoop with web-scale enterprise storage and real-time database capabilities, enabling customers to harness the enormous power of their data.
Known classified customers: Recruit Technologies, Rocket Internet
Platfora, http://www.platfora.com
Complete, end-to-end analytics platform built natively on Hadoop and Spark, Platfora Big Data Analytics is creating data-driven competitive advantages in the areas of security, marketing, finance, operations and the Internet.
Known classified customers: Auto Trader
Platform 161, http://platform161.com/
Platform161 is a customizable digital marketing platform for programmatic buying. Its open
and programmable algorithm enables customers to add any custom data point to the automated decisioning logic, making decisions more accurate and effective.
Known classified customers: Jaap.nl, De Persgroep
PubMatic Inc, http://www.pubmatic.com
PubMatic is a marketing automation software company for
publishers. Through real-time analytics, yield management, and workflow automation, PubMatic enables publishers to make smarter inventory decisions and improve revenue performance.
Known classified customers: Scout24 Switzerland
Semilo, http://semilo.nl/
Semilo is a digital media operator and offers a network of over 120 premium (mobile) websites and apps that can be addressed with programmatic media buying.
Known classified customers: Jaap.nl
Teradata, http://www.teradata.com
Teradata is a global leader in analytic data platforms, marketing and analytic applications,
and consulting services. Teradata helps organizations collect, integrate, and analyze all of
their data so they can know more about their customers and business and do more of what’s
really important.
Known classified customers: Cars.com, Overstock.com
Checkr, https://checkr.com/
Checkr provides automatic background screening of applications as part of the pre-submission
workflow. It integrates with a company's ATS or an online classified job board.
Known classified customers: Wonolo
Arvato Bertelsmann, www.arvato-systems.de
For over 30 years arvato Systems has been building a solid reputation as a systems integrator
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with successful projects for major corporations in the most diverse industries.
Known classified customers: Axel Springer, Ringier
Personalization / Productivity
accengage, www.accengage.com
Accengage gives publishers and advertisers all the necessary tools to monitor the value of
their acquired customers, accelerate mobile engagement, and boost sales conversion.
Acxiom Deutschland GmbH, www.acxiom.com
For over 40 years, Acxiom performs as a service company that uniquely fuses trust, experience and scale to fuel data-driven results.
Known classified customers: Ebay
Digital Element, www.digitalelement.com
Digital Element has been providing global geolocation
solutions that bring anytime, anywhere relevance and
context to online initiatives ― from desktops to mobile
devices ― for more than 14 years.
Known classified customers: Ebay
Gravity R&D, http://www.gravityrd.com/
Gravity R&D is a technology expert serving omnichannel recommendations for major clients
on five continents.
Known classified customers: Allegro, OLX, Schibsted Classified Media, Jobseeker (Seek)
Maxymiser GmbH, www.maxymiser.de
Maxymiser is a leading provider of cloud-based software that enables marketers to test, target and personalize contents.
Known classified customers: Auto Trader, Haymarket, Totaljobs, Immowelt
Slamby, http://www.slamby.com/
Automated text categorization for classifieds.
Known classified customers: Agroinform.com, Quoka, Jofogas
Priori Data, https://prioridata.com/
Enables publishers, investors, advertisers, and brands make smarter decisions in the app
economy.
SimilarWeb, https://www.similarweb.com/
Get insights for any website or app.
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RealMassive settles lawsuit for $1M
CoStar claimed real estate rival copied its content
U.S. real estate vertical required to pay $1 million U.S. in compensation.
BY BRIAN BLUM
Real estate specialist CoStar has settled its copyright infringement lawsuit against commercial real estate classified competitor RealMassive, which agreed to stop copying listings
content from CoStar.
U.S.-based CoStar, which owns
Apartments.com, ApartmentFinder
and LoopNet, claimed in a suit filed
in May 2015 that RealMassive had
hired contractors to copy listings content — in particular photos — from its
commercial brokers’ sites and then
“reproduced those listings wholesale
on RealMassive,” CoStar founder and
CEO Andy Florance said.
RealMassive CEO Craig Hancock said the real estate
classified
company is “glad to have this lawsuit
resolved.”
“As the case went forward, it
became clear that RealMassive’s systematic theft of CoStar intellectual
property had been conducted on, for
lack of a better phrase, a real massive scale,” he said.
A bitter feud illustrated with internal emails
In an interview with the AIM Group, Florance said that during the discovery process,
CoStar had uncovered documents and emails that outlined RealMassive’s intentions.
In one snarky message responding to why RealMassive had incorporated in Panama,
which was included in CoStar’s release on the settlement, RealMassive founder Josh McClure
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Vol. 17 No. 5
reportedly wrote: “I’d highly recommend you take advantage of something like this if you plan
on continuing a career of making really large companies mad at you. It’s very profitable in the
short term and very harmful to your bank and credit score when they track you down. If they
find you, you can’t win.”
Florance told the AIM Group that CoStar also found emails from RealMassive staff protesting against what they knew was illegal activity. RealMassive paid contractors to crop out
CoStar’s logos when re-posting the content, Florance said.
RealMassive CEO Craig Hancock said in response that, “CoStar’s claim that we deliberately added its photos to our database was false. Our firm went to great lengths and expense
to avoid acquiring CoStar’s images, but apparently a few images slipped through the cracks
early on. We are glad to have this lawsuit resolved.”
Not the first time RealMassive is litigated
It is not the first time a member of RealMassive’s team has been sued for intellectual
property theft. In 2009, Craigslist filed a lawsuit against McClure and his then-company,
Troopal Strategies, Inc., complaining that Troopal distributed software designed to allow advertisers to auto-post millions of advertisements to Craigslist.
Troopal was also based in Panama, which McClure said at the time made the company
“Craigslist-bulletproof.” The court ruled against Troopal. CoStar said it is not clear whether
McClure ever paid the $8.2 million U.S. default judgment against him.
CoStar said that, as part of the settlement, RealMassive is required to pay a $1 million
U.S. initial payment and $4,000 U.S. per photo per day, plus attorney fees for any subsequent
CoStar content that appears on RealMassive.com
So can CoStar collect this time? After all, RealMassive like Troopal is not based in the
U.S.. Florance said yes. “We’re not bashful in collecting. We’re willing to spend as much money [on legal fees] to collect on the judgment as it took to get the judgment.”
RealMassive’s “real” headquarters is in Austin, Texas, Florance said, and CoStar made
sure to name in the settlement “any investors, employees or principles involved. So they can’t
hide behind the incorporation in Panama.” Both MClure and Hancock are named.
Still, does a shop like RealMassive have the cash to pay the fine? “If not, we’d require
them to go through bankruptcy,” Florance said.
Florance admits that sometimes companies make mistakes with CoStar’s Terms of Service. “When that happens, we call them up and it’s resolved easily,” he said. “It happens all
the time. But when we find people who have been sued before [like RealMassive’s founder],
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Vol. 17 No. 5
CoStar said RealMassive must required to pay a $1 million U.S. initial payment and $4,000
U.S. per photo per day, plus attorney fees for any subsequent CoStar content that appears
on RealMassive.com.
then the gloves come off. If we feel you’re a sociopath, we’ll treat you that way. We invest a
lot in building our websites and content. If we sat by and let people just steal the content on
our website, we wouldn’t be around to serve our clients. So when we find people taking our
content, we have to be very serious about it.”
RealMassive also signed an agreement with CoStar agreeing to pay damages, prohibiting
it from scraping CoStar-powered sites and binding it to CoStar’s websites’ Terms of Service.
The two firms agreed to “work together to avoid future disputes.” RealMassive added in a separate statement that CoStar agreed to mark its copyrighted images and to give RealMassive a
written takedown notice before filing any future lawsuits.
CoStar still has a pending lawsuit alleging similar damages against Apartment Hunters,
claiming it repurposed images of multifamily properties published on CoStar-owned Apartments.com.
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Vol. 17 No. 5
Ads fuel China’s used car market
Vertical Renrenche poised to benefit in hot market
Emerging auto vertical Renrenche is piggybacking on surging online demand.
BY DON GASPER
The fast-growing market in China for second-hand cars looks like it will soon be the
world's biggest. Domestic auto verticals have
played a major role in helping this happen.
This transformation is in part due to
the efforts of people like Li Jian and Du
Xiyong, co-founders of auto vertical Renrenche.com. The company, based in Beijing,
was set up only in April 2014, but has benefitted from investment ($85 million U.S.) by
Chinese e-commerce giant Tencent.
Li is a former IT engineer who, like
two other co-founders, used to work for Baidu, China's answer to Google. Du, on the other hand, worked for 14 years as an auto news
editor.
At the start of 2014 they sat together
to discuss establishing their own business. After deliberating, they opted to join the burgeoning used-car market, because they saw it had great potential.
Market for used cars growing rapidly
China had already become the word's largest automotive market in 2009, spurred
by the government cutting tax on car purchases.
In 2015, according to the China Association of Automobile Manufacturers
(CAAM), 24.6 million cars were sold in the country, an increase of 4.7 percent on the previous
year.
Now China is poised to become the largest market for second-hand cars too. The CAAM
said that last year 7 million used cars were purchased — up from 1 million in 2014. By its esti-
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Vol. 17 No. 5
mates, by 2020 the number of used cars that exchange hands will be the same as the number
of new car sales — 29.2 million.
"The company is creating an online 4S showroom for second-hand cars, and making the
deals more transparent and effective,” said Li Jian, Renrenche’s CEO. “It will expand to more
cities and provide higher-standard services."
Although Renrenche is not a leading auto vertical in China (SimilarWeb ranks it as No.
15 among China's auto and vehicle websites by traffic), it has
seen rapid growth.
In Jan. 2015, around 300
second-hand cars were sold on
its website, with the total rising
to 10,000 by the end of the year.
“The Chinese are much
more open to online shopping
than, say, Europeans, partly because everything in China is so
huge, and of course the density
of outlets per inhabitants is lower than in developed countries.
So, a trip to a car dealership easily takes half a day or longer, to
Although Renrenche is not a leading auto vertical in
visit three or four dealerships to
China, it has seen rapid growth.
compare different brands is often
not practical. Therefore, the information gathered online is much more important,” Bejingbased auto industry expert Harald Buchmann told the AIM Group.
A shifting model: From B2C to C2C
Du told Hong Kong's South China Morning Post this month that he thought the established B2C model where Chinese people bought second-hand cars only from agencies might be
starting to change to the C2C model used by his company. Within the B2C model, there is usually a 30-50 percent mark-up between what an agency pays the original owner and the resale
price it charges the new purchaser.
On Renrenche, purchasers pay 3 percent of the selling price to the platform once the
transaction is complete. Included in that commission is a check-up of a car’s previous acci-
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Vol. 17 No. 5
dents, water damage and repairs history. The site then issues a test report for each car,
which is shown online.
Renrenche also offers a free repair service for cars within one year of the sale or after
a car has covered 20,000km.
Within two weeks of the sale, the purchaser can even return the car to Renrenche and
request a full refund.
Renrenche uses search engine expertise to outsmart rivals
Since mid-2015, China has seen a marketing war between auto verticals. Some sites
boast celebrity endorsement, while others offer deals at zero commission to attract customers.
Du has said that in his view the services of the various platforms were more or less
equal. Where his company scored, however, was in its greater traffic.
“For example, there are 3.7 million web pages of our website included in Baidu's database, but for one of our competitors, Guazi.com [set up by classified site Ganji.com and now
run as a unit within 58.com], there are only 700,000,” he said.
Du attributes this to the skills his colleagues acquired while working for Baidu, which
enable them to make Renrenche’s site more visible to those using China’s dominant search
engine.
However, it has not been all smooth sailing for the company. Recently, allegations
have circulated that international consultancy firm Roland Berger found that Renrenche had
falsified its transaction figures, doubling deal numbers in its publicity materials.
Du has maintained that Roland Berger has never investigated Renrenche and is not the
source of blame. The suggestion is the reports were part of a dirty-tricks campaign waged by
one of the website's rivals.
Du maintains that his company conducts due diligence work on every deal, including
verifying customers' telephone numbers, their bank account details and bank statements
showing the deal, and the transaction records published by the vehicle management authorities.
He believes that in the long term it is reputation that counts.
Renrenche is now getting ready to launch an auto finance business as a sideline. However, the company is not considering listing its business at this point, despite a hefty valuation of $500 million U.S.
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Vol. 17 No. 5
Rivals welcome QuikrJobs to India
Competition already fierce for blue-collar job listings
As a new vertical enters the market in India, we take a look at four verticals serving
blue-collar jobs.
BY SHILPA SHREE
The launch of recruitment vertical QuikrJobs in 2015 by India’s leading horizontal player Quikr is set to reshape the country’s jobs sector. The
new site is set to focus on blue-collar jobs.
QuikrJobs CEO Pranay Chulet has said the company would
“bridge the gap between recruiters and a large portion of the
country’s job-seekers who have no access to the Internet.”
However, the local market for blue-collar positions is already highly competitive. the AIM Group analysed four job verticals that will welcome the new challenger into the fray.
Babajob.com: Leading low-pay player
Babajob, partly funded by Gray Ghost Ventures, Khosla Impact Fund and Seek, believes
it is the largest job marketplace for positions with a salary below $300 U.S. a month. It focuses on jobs for drivers, delivery workers, maids, cooks and retail employees.
“We are seeing a change in the way
people are getting hired. People are moving from informal to formal sectors,” Vir
Kashyap, COO and co-founder, told the
AIM Group. “An employer like an Ola (taxi
service) or Grofer (delivery service) can
log into Babajob to hire their delivery
boys. We also have (business process outsourcing companies) hiring telesales, sales staff and
the like.”
Babajob’s flagship product, Rapid Hire, provides employers with a list of job candidates
and connects them to employers by phone. Rapid Hire starts at $30 U.S. a month for employers.
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Vol. 17 No. 5
“This is a fairly new market,” Kashyap said. “We do have some overlaps with Naukri
[leading job vertical], Monster and the others. Some of the companies that have an offline
presence and work as managed services firms are also our competitors.”
The privately held company said revenue grew by 6-7 times in 2015. It holds 5.2 million
people in its database, with almost 300,000 job listings.
Revenue comes from employers who pay per-lead fees, but the company is considering
ways to generate revenue from job candidates.
Like Quikr, Babajob offers a missed-call service.
Careesma.in: Leading B2B marketplace
Careesma.in claims to be the leading B2B recruitment marketplace in India, with about
60,000 job listings.
About 10 million candidates are registered, the company said.
“We have an edge in reaching the
small- and medium-sized market (SME),
and regions where other portals can’t
reach. The SME segment is the backbone of
Careesma,” Antonio Gonzalez-Barros,
Managing Director for India, told the AIM
Group.
Gonzalez-Barros said Careesma has a “unique freemium model” that it uses to
“attract and provide value to the SME segment better than anyone else.”
After a trial month, a company is limited to one job post a month. “But if they want to
post more, or want to benefit from premium services, then they do have to pay,” GonzalezBarros said.
The company said it has 2 million unique users a month and adds 12,000 resumes per
day.
“We have seen accelerating growth in the last three years,” Gonzalez-Barros said.
Careesma India is part of a network that includes Austria, Poland and Italy. Careesma
India is fully owned by a holding company in Spain, where Grupo Intercom is the major shareholder.
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Vol. 17 No. 5
Nanojobs.com: Domestic staff specialist
Nanojobs is a regional player specialising in blue-collar and gray-collar jobs. The
company has listings for maids, cooks, nannies, babysitters and caretakers, and recently
raised about $150,000 U.S. in angel funding from 50K Ventures and
its founder Vineel Nalla.
“Quikr entering this segment is going to heat up the competition,” said Anupam Sinhal, one of the co-founders of NanoJobs.
“Considering the fact that this segment cannot speak English, we
manually upload their information on our portal. I am not sure how
Quikr will address this challenge.”
The company said it has no plans to expand Nanojobs.com but it intends to expand its
sister site BookMyBai, a recruitment vertical aimed at domestic staff, to more cities.
“The business has a lot of scope in India where domestic help is part and parcel of everybody’s life,” Sinhal said.
RoundOne.in: Innovative referral model
RoundOne.in helps candidates find jobs based on referrals by Nishant Mathur, a former
Accenture consultant and INSEAD France graduate. It has raised funds from HT Media’s
Shine.com and Arun Duggal of Infoedge.com.
The unusual company model helps users contact
another user at a company where they want to work. If
both agree, the candidate is referred.
“We are a technology-driven company and have a
strong algorithm for searches, which can be easily replicated in any other country,” Mathur said.
About 2 million job candidates have registered on RoundOne, and about 30,000 midsenior employees are available for interviews. Job candidates can get referrals in about 2,500
companies. A premium membership enables users to speak with unlimited interviewers for six
months for $30 U.S.
In a market where fake profiles are common, RoundOne has found a solution.
“Fake profiles are not as big a problem on RoundOne, because if the referrer/
interviewer does not feel the person is genuine, they won't refer them to the company,” Mathur said.
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Vol. 17 No. 5
More news and analysis on AIMGroup.com
Reminder: Here are some headlines you might have missed on AIMGroup.com. Most of these articles
are clients-only, so you’ll need your username and password to read. But if you sign in once, you’ll be
able to read all.
Nordlander on Avito’s paycheck to shareholders
Avito founders Jonas Nordlander and Filip Engelbert have reason to be proud of astonishing
growth in revenue in 2015, when counted … (Read more…)
Juwai names new CEO
Juwai.com, the Chinese-language international real-estate website, has a new Chief Executive
Officer.The company has announced that it has appointed a former bank Chief Operating Officer, Charles Pittar, to … (Read more…)
U.K. Chancellor gives AirBnB hosts a tax break
The U.K. Chancellor has given Airbnb hosts and marketplace traders a tax break, implementing a £1,000 per year tax-free allowance for Britain’s micro-entrepreneurs.
The new tax-free allowance will … (Read more …)
Dice grows brand awareness with Europe-wide campaign
Following a successful billboard takeover at a London underground station last November,
Dice is extending its campaign to cover Greater London, Berlin, Cologne, Munich, Amsterdam,
Brussels, Ghent and Antwerp.
All markets will use the ‘Hot Tech Talent’ creative, which is about … (Read more…)
OnTheMarket expands into Northern Ireland
Since its launch in January 2015, OnTheMarket has gained significant ground in England, Wales
and Scotland and now also carries thousands of listings from real estate and letting agents in
Northern Ireland, where it aims to challenge existing players PropertyPal.com, PropertyNews.com and Zoopla.
Helen Whiteley, OTM’s commercial director, said: “Having made tremendous progress in …
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