A Metrics-Driven Strategy

Transcription

POINT OF VIEW
Positioning Content for Success: A Metrics-Driven Strategy
Positioning Content for Success:
A Metrics-Driven
Strategy
By Kevin P. Nichols, Director and Global Practice Lead, Content Strategy,
SapientNitro & Rebecca Schneider, President, Azzard Consulting
POINT OF
VIEW
You may have heard people say “content is king.” You may have also heard that content strategy is the
tool used to unlock the true potential of content. But if content is “king,” how do organizations validate
the worth of their content and improve upon this valuable asset?
Return on investment (ROI) for content strategy is a hot topic. But let us push that conversation even
further. How do we leverage metrics and analytics for content development? How do we make content
work for us?
Whether you are an analytics or metrics expert, a content strategist or a content creator, you will be
able to start to derive a formula for successful content by the end of this paper. You will have a greater
understanding of the appropriate metrics, analytics and KPIs necessary to make content intelligent.
You will know which metrics will measure content efficacy, and how to refine personalized content,
develop useful metadata and taxonomy, measure what is important for publishing and content lifecycle,
ensure effective content governance, capture mobile-specific information and avoid pitfalls.
DEFINING CONTENT STRATEGY
In order to understand content strategy, let us first discuss a working definition for content.
Content communicates an idea that is recorded.
Content strategy focuses on the ways to meet the needs of content consumers, exercising oversight and management of content
distribution. Content strategy is the systematic, thoughtful approach to surfacing the most relevant, effective and appropriate
content at the most opportune time, to the appropriate user, for the purpose of achieving a company’s strategic business objectives
and customer goals.
© Sapient Corporation, 2014
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POINT OF VIEW
At SapientNitro, we break this concept of content strategy down into three pillars:
Pillar 1:
The first pillar is content experience or the end-user experience. It includes the information provided to the end
user and includes anything from terms used to search for products to personalized content and content structure.
Pillar 2:
The second pillar is content delivery (what we call “the content lifecycle”) — the model we use to acquire, create,
maintain and optimize content.
Pillar 3:
The third pillar is content governance and considers the operational processes and mechanisms required for
successful content.
The term metrics is oen used interchangeably with KPIs and analytics, so let us clarify some o-used terms before we go any further:
Metrics are tangible measures of inputs and outputs.
Key performance indicators (KPIs) are sets of metrics used to quantify progress towards organizational goals.
Analytics are conclusions drawn from metrics.
There are many kinds of metrics, which typically fall into two categories: hard and so.
Hard metrics are quantifiable measurements. They are the “what.” These are the numbers and facts. Examples include
conversions, number of visits, time on site and key words. Hard metrics are crucial when measuring the efficacy of content solutions
and demonstrating quantifiable ROI.
So metrics are qualitative measurements to get to the feelings or motivations behind an action. They are the “why.” Examples
include focus group research, marketing trend studies, online behavioral analysis and customer satisfaction surveys. It is best to use
these measurements when trying to further understand customer behavior and hard metrics data.
CONTENT PERSONALIZATION
Now that we have some basics out of the way, let us dive into content
personalization, the process of developing intelligent online content
solutions that are tailored to a specific user.
Personalization is an evolving process; it requires an understanding
of customers and an ongoing analysis of customer behavior. Types of
personalization include content based upon:
> specific type of user
> user location
> user behavior; and/or
> information (e.g., gender, age)
within a user profile.
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POINT OF VIEW
What types of metrics should we use to ensure that personalization is effective? Consider where does the customer go and
where can content be personalized? A good way to determine this is to look at the customer journey. For a desktop website
experience, this may be a click-stream path to purchase, or return visit to a particular area of a site. For an end-to-end omnichannel
experience, this would include all of the customer touch-points and what the customer does within each. (For example, a customer
clicks on a banner ad while using a desktop computer, which takes her to a website. She creates a profile and later uses her smart
phone to locate the company’s store via a Google search. Upon arriving at the store, she scans a product’s QR code to compare
products, checks for any available coupons and purchases the product. Once home, she follows the in-the-box instructions to share
the experience on social media.) Other critical metrics are length of visit per page and the depth of visit.
In order to improve upon personalized experiences, it is imperative for you to understand how customers behave, which touch-points
they use and how they use them. It is also important to understand what content each customer sees as relevant and useful. Since
most personalization begins with an assumed or predicted customer journey, it is critical that you evaluate the reality of how a
customer behaves against what was previously assumed, so that content can be optimized.
Aer the user journey, the next important metric is based upon the customer’s reasons for coming to the site. We can determine
this by looking at top keyword searches or the customer interaction history. For example, what accessories were previously
purchased? What types of music or books has the customer ordered in the past? In order to evaluate this customer rationale, your
technology solution will need to use cookie-based logic or another type of profile logic.
And last, where and when does the customer convert — in other words, where and when does the customer complete a task
(e.g., filling out a user profile, adding an item to a shopping cart, registering for an event)? Site registration, viewed product
information, and purchased product are all good metrics to help understand conversion.
TAXONOMY AND METADATA
Metadata and its associated taxonomy can significantly support the
content experience. And improving taxonomy (for navigation and search)
and metadata (filters to find the desired result) can get the user to the
content as quickly as possible.
In order to determine key taxonomy and metadata metrics, first ask
yourself: Is the user finding what he needs? Is the navigation taxonomy
working? Is he using metadata filters as expected? Take a look at the
organic and paid keyword search rankings. Find out which
keywords are converting. For example, when shopping for a computer,
are people searching for “notebook” or “laptop?” Also, find the top
successful searches. Are these searches for seasonal items, brand names
or accessories for products already owned? Other useful statistical data
to pay attention to are click streams to specific product categories.
For instance, if a customer is looking for children’s furniture does he click
on “children” or “furniture” first?
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POINT OF VIEW
Second, what is not working? Ways to discover this include bounce rates (when a user enters a page from outside the site,
then immediately leaves) and exit rates (when a user spends time looking around the site, then leaves). Was the page unhelpful?
Was the product without a picture? Was something out of stock? Keep in mind that exit rates are considered successful when
customers leave aer converting. Another piece of data to look at is the previous page prior to search, which can point out
potential navigation problems. If a user is on a home décor page and searches for a lamp, that probably means she is expecting
to find it within that section.
Third, what terms should be added to taxonomy or metadata? Consider adding terms that are used frequently that return
no results because of the way they are named or search terms in ad hoc description fields that may or may not be in the
actual taxonomy.
And fourth, what terms do users employ in search? There are oen search terms that are variants of a preferred term
(e.g., soda vs. pop) and terms used in taxonomy but not in SEO metadata. Look at refined searches, which are key to not
only adding terms to the taxonomy but also looking at how users navigate the site.
PRODUCTION AND CONTENT LIFECYCLE
Content lifecycle metrics seek to measure the effectiveness of the overall
content delivery processes. The lifecycle is the entire end-to-end process
in which content is acquired, created, managed, published and then
optimized or retired.
Start by understanding the benefits to an improved content lifecycle
process. One benefit is time saved (and therefore, cost saved) in each
step of the content lifecycle when the optimal choices are made for
your business. An additional benefit is reduced time to market for new
products as content bottlenecks are removed.
So, what metrics can help improve content quality? Examples include
reduced numbers of errors in content (when product items are
properly tagged), decreased content redundancy to improve content
quality and reduce cost, and decreased response times to feedback,
content errors and content changes. Also, streamlining robust localization
processes result in reduced localization costs and increased ROI
due to more efficient CMS processes.
Acquire/
Create
Content
Enhance
Content
Manage
Content
Governance
Publish
Content
Evaluate
Content
Improving internal user satisfaction should not be overlooked either. Determine the number of people using CMS compared to
those who should be. If your employees are not happy with the system, they are not going to use it, which will affect the success
of the entire content strategy. Use a survey instrument (e.g., ForeSee) to find existing problems and then measure the increase in
internal organizational satisfaction once they are addressed.
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POINT OF VIEW
CONTENT EFFECTIVENESS
Content effectiveness enables good content experiences. Content journey, content quality and overall fit for the user are all key aspects
for customers and businesses.
TRIGGER
IN-STORE
WWW.COMPANY.COM
As she approaches her
local store, she receives a
push notification on her
phone, letting her know
about new accessories.
SMS
Mobile Web
Michelle,
an existing
customer, receives
a text message
from retailer.
She clicks the e-spot to
view more. She clicks
on the product to view
more details.
As she adds to
her “favorites,”
recommended
products become
even more relevant.
Smartphone
Tablet Web
Tablet App
Desktop
Using her iPad, Michelle
visits .com to look for
new products. She
notices a module on the
homepage for a featured
product that is her
favorite brand.
Michelle saves
product to her
“favorites” and
continues to browse
the product catalog.
Michelle has saved
6 products to her
“favorites.” Michelle
updates her customer
profile and sends
her “favorites” to the
nearest retail location.
Entering the store, Michelle
is greeted by Ken, a sales
associate. He has Michelle’s
“favorites” ready for her to
view, which he pulled up
on his tablet.
Using the sales
associate tablet,
Ken is able to
pull up Michelle’s
profile, where he
accesses her store
loyalty coupons.
One way to measure content for efficacy is to measure the rate at which content is viewed, both in frequency and duration. Another
option is to conduct A/B testing. You may test these by creating and assessing the use of two different value propositions, homepages,
campaigns, headlines or images to see which performs best. Multivariate testing, which uses variations of data, is another way to
measure content effectiveness; it tests the placement of various items like filtered navigation on a page to help enhance performance.
Also, determine the most popular content — the content that is “trending” based on traffic and engagement time. Today, trending
apps can help uncover real-time performance of content.
So then, how do you determine if a content journey is effective? As technology continues to emerge and as user patterns change, it is
important to test an actual browsing path against an assumed, pre-defined browsing path. If customers are looking for a
soundcard driver, are they going home > support > drivers or home > product > support > drivers? You can also look at the number
of visits to convert and the time to convert. Check to see if they returned to your site aer any initial research to purchase, and pay
attention to how many visits they made and for how long. Where and when a customer exits prior to conversion can determine
trends based on exit behavior. Did they not like what they were seeing? Are they being forced down a certain path? And bounce rates,
which we have briefly discussed, can indicate that they arrived somewhere unwanted or unexpected.
Next, how do you determine user satisfaction? Find the rate at which content is being shared via social (e.g., email, Facebook) or
downloaded (e.g., user manuals, instructions), survey the user with user feedback tools (e.g., ForeSee) to help validate and refine the
metrics and determine problematic areas through bounce rates and exit rates.
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POINT OF VIEW
CONTENT GOVERNANCE
Content governance is the organizational oversight of content and it focuses on the operational models needed to manage content and
ensure its continued success.
When you are looking at content governance, you will want to look at the structure in response to requests. The time it takes to
implement content changes based on governance decisions is crucial. Be sure there is a governance structure in place
with defined workflows. For example, if there is going to be a major structural taxonomy change, how long will it take from request to
implementation versus one that is minor? Also, take into account how long the addition of new information will take. Look at the time
it will take for the governance committee to review requests and ensure that it is possible to complete a content review cycle.
Make sure content is up to governance standards in terms of accuracy rates, currency and effectiveness.
MOBILE
Metrics captured for mobile can be very similar to those captured for the web. However, the analytical perspectives will differ because
of the physical nature and practical constraints of a mobile device. And a mobile user behaves differently on a mobile device than she
does on the web; according to Mobile Commerce Daily, 68 percent of mobile searches result in a map look up, 61 percent of local mobile
searches result in a phone call and 59 percent of mobile users interact with businesses via social media regularly.
Executive Sponsor
Governance Committee
Strategy
Brand
Accessibility
Legal
Taxonomy
Content
Publishing
Taxonomy
Working Groups
Strategy
Operations
Technology
Marketing
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POINT OF VIEW
Smart phone metrics
Metrics to pay attention to include time spent on pages optimized for smart phones, which, in contrast to desktop web analytics,
may instead indicate that the user cannot achieve his goals or find information. In addition, it is wise to focus on taxonomy and
metadata related metrics as well as search rate.
While on mobile devices, users rely on search more than they do navigation found within navigation menus, so if you notice search use on
mobile decreasing for your users, it oen indicates that the user cannot interact with the search functionality easily.
Consider how oen the phone orientation changes from vertical to horizontal and vice versa. Unless there is a specific reason for the
orientation change, such as a user who wants to view a video and changes the perspective to do so, higher rates of orientation change
correlate with higher exit rates.
And how is social media being used? As mentioned above, over half of mobile users interact with businesses via social media regularly,
so it is imperative to survey the amount of traffic entering from social media. Businesses should also track user behaviors
in-store (like barcode-scanning and product comparisons) to monitor those behaviors. Another metric to look at is how many users accept
location awareness prompts; this metric can demonstrate trust with the brand as well as indicate demographic behavior information.
Tablet
Tablet devices have similar metrics to smart phones, and many of the below metrics can also be applied to smart phones. Also note that
several are important for personalized content and omnichannel experiences.
For websites that have apps, an important tablet metric to measure is how many users ignore the call-to-action to download the
app and opt to view the actual website. The advantages of the app may not be clear prior to download. Also, look at the number of apps
that are being downloaded versus purchased. This metric is relevant for organizations that offer both types of apps and organizations that
offer apps that can be activated aer a certain trial period.
For omnichannel experiences, measure the delta between the conversion rates on a tablet or smart phone versus a desktop.
How do customers convert on mobile device versus a website, and which products or services do they purchase on each? The difference
may indicate whether content is working well on the device and can help you derive customer behavior per channel (e.g., a customer wants
to view long-form specifications of a product on the website, which are not available on an app). Also look at how many users switch
to the desktop view from a mobile app. This could indicate that the user cannot use the app as well as the desktop. Look at the points at
which a customer goes from desktop to mobile and vice versa.
Two metrics that measure how responsive design is used include the screen resolution and the type of device being used. These
metrics measure how and where content is being consumed. For commodity or published content, what is the actual number of readers
in a tablet edition versus a paper published edition? Many publications such as The Economist, Vanity Fair and the like have offered
their subscribers complimentary digital access. How many users take advantage of this?
Pitfalls
You can use metrics and analytics to improve many areas of content, but there are some pitfalls that you should avoid. First, do not treat all
statistics equally; some statistics are more important than others. Second, not all data is good data, and more data does not always equal
better data. Third, you cannot just pick the indicators that tell you what you want to hear — and you should not let other stakeholders who
may be privy to the metrics do so either. Remember to use a critical eye to draw solid, specific conclusions.
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POINT OF VIEW
CONCLUSION
ROI is not just about more products being sold, conversions or operational efficiencies. By using solid metrics, content creators and managers
can improve their content with the robust metrics and analytics that make content optimization possible.
ABOUT THE AUTHORS
KEVIN P. NICHOLS, @kpnichols
Kevin P. Nichols is Director and Global Practice Lead for Content Strategy at SapientNitro. He has
over 18 years of experience. A Harvard graduate, he executed his capabilities in the Sabre Foundation
before traveling to Bosnia and Herzegovina, where he was Webmaster for Physicians for Human
Rights. He went on to Sapient Corporation as a UX Lead for global brands on Web and CMS projects.
Kevin played a key role in launching MIT’s OpenCourseWare project, and as a Senior Consultant at
Molecular, he led UX teams for global brands. He went on to become an independent consultant at
Kevin P Nichols’ Consulting before returning to Sapient as a Director of Content Strategy.
REBECCA SCHNEIDER, @azzardconsult
Rebecca Schneider has extensive background in librarianship, knowledge management, systems
and information technology. She formed Azzard Consulting, a content strategy services and staffing
firm, with the conviction that there are better ways to manage content. Rebecca has worked in a
variety of industries, including retail, education, real estate development, international development
and financial services. Rebecca is also familiar with non-profit and government sectors.
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A Metrics-Driven Strategy

Transcription

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