How To Build A Bullet-Proof Justification For Your New IVR

How To Build A Bullet-Proof Justification For Your New IVR

How To Build A Bullet-Proof Justification For Your New IVR
Using insights from your callers' actual experiences instead of unreliable "guesstimates" from vendors
and consultants gives you a business case that you can trust.
The opportunity to reduce costs using IVR automation is widely proven - with many case studies citing
10-30% or greater reductions in agent-handled calls. Yet many companies struggle with the decision to
invest in new or upgraded IVR systems. Obstacles to gaining management support and budget approval
can include:
• Problems and opportunities in current call handling are not visible in existing reporting.
• Caller dis-satisfaction with IVRs raises questions for any proposal to subject more callers to IVR
automation.
• Cost savings based on vendors' and consultants' projections are perceived to be untrustworthy.
• Too many stories or past experiences with IVR projects that did not meet expectations.
These barriers share one common trait - they can all be traced to incomplete information and its
consequences. For example, with no simple way to quantify actual caller behavior, companies too often
rely on vendors' optimistic projections to justify new investments. Companies also readily acknowledge
gaps in reporting, which can give the false impression that the current IVR is working satisfactorily. And
lacking visibility of actual caller interactions to guide design choices, voice developers continue to use
the same "best practices" that have produced the current generation of frustrating voice user interfaces.
Fortunately for both callers and call centers, innovative new solutions have finally made it cost effective
and practical to gain insight into actual callers' behavior and experience. New technology has solved
one problem - following the caller from dialing to hang-up (across all transfers & without installing any
new software!). And, it has begun to address another - replacing manual categorization of calls with
automated analyses.
With a true cradle-to-grave view of how and where callers spend time, companies can now replace
subjective "guesstimates" with solid data about where their callers get frustrated and where their
agents' time is wasted. The result is a compelling and concrete business case for new IVR automation and reduced risk of failing to meet expectations.
Limitations Of Traditional Approaches
The analysis of the potential value of a new or upgraded IVR has traditionally started with an
examination of existing data. Such data may include call detail records, switch reports, IVR logs, and
reports from agent desktop applications.
Desktop application reports may include agent-provided information about the call. Unfortunately
though, such data can be problematic. It's not atypical to find ~20% of calls marked "resolved" by
agents (who sincerely believe they did their job), while the caller is unsatisfied and considers their
inquiry unresolved. And pressures to minimize handle time can drive agents to quickly complete a form
rather than thoughtfully select the best classification for each call.
Before analysis can begin, existing data must first be extracted from a myriad of voice and data systems.
This seemingly simple step can easily take weeks or months. Some data may be impossible to access,
such as that held in systems belonging to suppliers and outsource partners.
Next, available data needs to be cleansed and prepared for analysis. Some methodologies include the
transformation of all data sources into a common form. At a minimum, data from disparate systems
must be aligned so that calls in one system can be linked with data about the same calls in another.
Finally, analysis can begin. Findings typically describe conditions at a specific site or step in the call flow:
•
•
•
•
Breakdown of transaction types (using desktop data or agent classification)
Transfer rates and destinations by site or skill
Top locations where callers opt-out or hang-up
Self-service task success & failure rates
Such findings describe what happened - but can't describe why it happened. This is a very significant
deficiency, since understanding why callers or agents take certain actions is required to design strategies
that will change their behavior.
Understanding why requires an assessment of intent and emotional state as callers proceed through
interactions with automation and/or agents. Unfortunately, this level and quality of understanding
simply can't be extracted from data such as application logs and call detail records.
Notwithstanding problems in the underlying data sources and the time and effort required to get this
far, such findings can be helpful if used properly. Typically though, the next step requires companies to
take a leap of faith. It's not uncommon to find the following kinds of assertions after charts and graphs
of existing data:
• If we move 20% of transaction A into self-service, we will reduce agent-handled call volume by x%.
• If we increase self-serve rates by 10%, we will save $x millions of dollars per year.
• If we reduce transfer rates by 15%, we will save $xxx thousands of dollars per year
The trick seems to be to propose a target that isn't too aggressive, but is large enough so that the
savings potential gets attention. Usually a few sample actions are described, such as building a new
application, implementing speech or re-recording prompts. But rather than a roadmap of actions that
will each produce a specific portion of the hoped-for benefit, there is instead an assumption that
following "best practices" will yield the intended results.
To senior managers evaluating budget priorities, many questions remain unanswered:
•
•
•
•
Why are callers opting-out, failing or hanging-up?
Why are callers being transferred?
Why are call volumes or handle times increasing?
What evidence is there that _____________ (e.g. re-recording prompts, new self-service, natural
language routing, etc.) will make a measurable difference in our call centers and with our callers?
• How do our agents handle calls that fail out of the IVR?
• How many callers will use each proposed self-service application and how much agent time will each
save?
• What exactly are the top 3 things that will produce the expected savings or satisfaction
improvements?
At this point, there are two possible outcomes - neither of them satisfactory. The proposed IVR project
may fail to get management support. This is very disappointing for the line-of-business, the IVR team
and the call center, who are usually correct in their belief that a well designed IVR would indeed reduce
costs and improve caller satisfaction.
Or, the company may proceed with the project (with unduly optimistic expectations). Unfortunately,
given the limited understanding of actual caller experience and reasons for caller behavior, there is
significant risk that the resulting system will fail to meet its goals.
In summary, the traditional approach to evaluating the potential value of a new or upgraded IVR can be
described as follows:
IVR Strategy From Existing Data
1.
2.
3.
4.
5.
Extract and transform existing data
Identify problems and/or opportunities (i.e. what is happening)
Pick an improvement target that seems both achievable and compelling
Implement the new IVR using the chosen developer's "best practices"
Iterate and tune until project goals are achieved or resources are exhausted
There are two notable weaknesses in this approach. First, there is relatively little quantitative analysis
behind the project goals for reduction in costs or improvement in caller satisfaction. And second, the
new system is designed using "best practices" rather than a true understanding of the center's unique
caller population.
Unfortunately, evidence of these shortcomings is plentiful. According to a Frost & Sullivan 2006 IVR
report, the primary reason for reluctance to deploy speech self-service is its failure in the past. And, a
Yankee Group consumer study in 2007 reported that 2/3 of respondents say they regularly opt-out of
automated systems.
An IVR Strategy Based On Knowing Your Caller
Freed from the constraints and limitations of existing data, leading edge call centers are using caller
experience analysis to drive IVR automation strategy. Rather than speculate on incremental
improvements and hope that "best practices" will achieve them, companies can now measure actual
caller behavior and quantitatively model the impact of new or upgraded IVR automation.
This new approach to planning IVR automation and quantifying expected benefits follows 5 steps:
IVR Strategy Using AVOKE Methodology
1. Capture dialing to hang-up caller experience (any and all IVRs, queues and agents, in-house &
outsourced)
2. Identify problems and/or opportunities (what is happening)
3. Determine root cause of caller and agent behavior (why it's happening)
4. Formulate and quantify strategies for new/improved IVR automation
5. Implement the new IVR using knowledge of caller behavior and identified automation strategies
Problems and opportunities are found by analysis of how callers spend time from the moment they dial
the contact number until the moment they hang-up. As the 2007 Yankee Group study confirmed, the
top sources of caller dissatisfaction are all related to wasting the caller's time. Of course, unnecessary
time in the call also drives excess cost.
Percentage of
Respondents
Reason
Long hold times
63%
Confusing automated menus
50%
Too long to answer
27%
Too many rep transfers
21%
System or agent did not have previously entered info
19%
Agent lack of knowledge about you
12%
Other
8%
Top Sources Of Customer Dissatisfaction
Yankee Group, Anywhere Consumer 2007 US Survey
By optimizing how time is spent in the call, call centers can simultaneously achieve both greater
efficiency and improved caller satisfaction. The analysis of how callers spend time uncovers 3 specific
types of opportunities.
Eliminate The Need For The Call
The best way to save call time is to eliminate the call entirely. And, the first calls to eliminate are those
repeat calls that are triggered by failure of an earlier call. Analyzing how the first call ends reveals those
that were not served at all, and those that were served unsatisfactorily (by either agents or IVR
automation). These callers will call again, and the first call needlessly wasted both caller and call center
time.
More calls can be eliminated by analyzing the true reason for the call. This reveals calls that can be
avoided by proactive notification and by improvements in other contact channels.
Reduce Total Caller Time
Managing queue times is well-understood, so the next focus is to find opportunities to reduce IVR time
and/or agent time. For example, many IVRs are unnecessarily verbose, which extends IVR time, causes
opt-outs, and drives excess cost in telecom charges and IVR resources. Opt-outs and other IVR
misroutes can also waste the first agent's time, whose only contribution may be to transfer the caller to
the correct agent.
Comparing interactions for the same activity in the IVR versus with agents can also reveal more efficient
IVR dialog structures. Error-handling in the IVR can also be a very large time sink, sometimes with only
marginal recovery benefit. Finally, opportunities can be found to optimize the process environment that
agents operate within - such as needlessly repeating tasks completed previously in the IVR.
Shift Time From Agents To Automation
This is the primary focus of most IVR automation initiatives. Analyzing how callers spend time with
agents reveals those repetitive activities that are a good fit for IVR automation. The list of automatable
activities can be further classified into those that are the best fit for various input modalities, such as
touch-tone, directed dialog and/or natural language.
For each discovered IVR automation opportunity, the cradle-to-grave view of the call enables
measurement of the amount of time currently spent by callers and agents. For example, one can
measure the amount of time that agents and callers spend on an automatable identification task, the
amount of time wasted by opt-outs or misroutes at a specific menu location, or the amount of time
wasted by an unnecessary call. Multiplying this time measurement by the frequency of occurrence of
each opportunity yields the maximum possible improvement potential.
Of course, this upper limit can never be achieved, since callers are never 100% cooperative or 100%
successful with IVR automation. Instead, the upper limit serves as a useful boundary for testing
expectations.
Caller-Centric Design
Having identified, quantified, and prioritized the highest value automation opportunities; the next step
is to establish design strategies for each that will maximize caller success. These design strategies
provide a crucial link between the planning and implementation phases. Design strategies serve as a
knowledge transfer vehicle. They encapsulate knowledge of "why" callers in a specific center behave as
they do such that it can be applied to voice user interface design.
Without this knowledge transfer, IVR designers are denied the opportunity to tailor the user interface to
the unique needs and behaviors of callers to a specific center. Without such understanding, "best
practices" can produce an acceptable design for the "average" caller. But, interaction design based on
an understanding of how and why a specific caller population behaves produces a higher performance
result.
Quantifying Expected Results
To quantify the value of each identified IVR automation opportunity, the impact of each corresponding
design strategy can be modeled. Such analysis may find, for example, that an identification module in
the IVR would replace 60 seconds of agent time with 70 seconds of IVR time. This change can be
modeled for the center's total volume by multiplying it by the percentage of callers that will likely use
the new identification module successfully.
Essentially, this caller-centric methodology employs a time study of the paths callers take, the call
process, and the interaction steps from dialing to hang-up. Time usage is evaluated for each different
reason for call, since each different reason has its own intended caller path - and its own actual map of
how many callers follow that path and how many opt-out, abandon, misroute or otherwise fail. The key
is to analyze the behavior of all callers with the very same need - and to understand why some succeed
and others fail.
The result is a quantified roadmap for IVR automation, based on a deep understanding of the center's
callers and business objectives. The roadmap consists of 3 major components:
IVR Automation Roadmap
1. List of each significant IVR automation opportunity and it's magnitude in terms of total caller and
agent time.
2. Specific design and implementation strategies for each IVR automation opportunity.
3. Expected value of each implementation in terms of caller utilization and saved caller and agent
time.
Despite the obvious value of a data-driven strategy and informed IVR investment decisions, such
comprehensive analysis of caller behavior and IVR automation potential has historically been
impractical. It was too difficult to assemble a cradle-to-grave view of the call. The analysis work is labor
intensive and required specialized expertise. And, business timelines and priorities did not allow for 612 month investigations.
A New Breed Of Analytics
BBN developed AVOKE Analytics to simply and quickly deliver data and insights about a center's actual
caller experiences to operational management and strategic decision making.
BBN's solution consists of the AVOKE Call Browser and the AVOKE Methodology. The methodology
provides a repeatable framework for synthesizing quantified action plans from caller experience data.
And, the AVOKE Call Browser is a revolutionary new software-as-a-service that captures and analyzes
caller experiences.
Key attributes of the AVOKE Call Browser system include:
True End-to-End View The AVOKE Call Browser captures the entire call from the moment the caller dials
the contact number until the caller hangs-up, including all transfers and all outsource partner resources.
Data, Audio and Transcription The AVOKE Call Browser combines call data, cradle-to-grave audio
recordings, and a full text transcription in a single interactive environment. Search and data views
enable discovery of patterns (what happened), with drill-down to actual call audio to understand caller
intent and emotion (why it happened).
Path Data and Audio in the IVR Listening to callers navigate, succeed, and fail in the IVR - and then
following them to the agent - is the only way to truly understand caller behavior.
Audio in Queue Listening to callers in queue provides another opportunity to learn more about the
caller's intent, emotional state, and view of the IVR and/or agent.
Audio with Agent Find and quantify automatable tasks. Learn how agents succeed at tasks the IVR
failed to complete.
Quick Results Budget cycles allow a few months to evaluate and build business cases for new initiatives.
The AVOKE Call Browser is typically up and running within 2 weeks.
No Software Purchase Your goal is to evaluate the business case for IVR automation. You don't need to
buy a complex software package that you'll only use for a couple months.
No IT Integration Using patented BBN technology, the AVOKE Call Browser is integrated in the phone
network, not in your data center.
About AVOKE Analytics
AVOKE Analytics is a cloud-based whole call recording and analytics solution. The solution enables
companies to optimize service performance from the customer’s perspective. The AVOKE system
records calls in the telecom network, eliminating IT requirements and obstacles. It follows your
customers, uninterrupted, through their entire journey as they traverse the IVR, all transfers, internal
call centers and partner sites.
The solution consists of the AVOKE Call Browser system, the AVOKE Customer Effort Index benchmark
service, and AVOKE Professional Services.
For more information on AVOKE Analytics, contact:
Raytheon BBN Technologies
10 Moulton Street
Cambridge, MA 02138
avoke@bbn.com
617-873-1600
www.avoke.com