Most contact centers have a Voice of Customer (VoC) initiative in place that pulls together customer data from sources that can include web and voice surveys, quick polls and social media. In what Forrester Research calls the age of the customer , VoC programs are clearly a mission critical component of contact center operations.
Yet having a VoC program in place and actually deriving value from the effort is not always an easy task. A 2013 survey  conducted by the Temkin Group revealed:
75% of companies are only collecting or analyzing data without deriving much actionable insights
46% are only collecting data without analyzing or doing anything relevant with it
23% collaborate around this data with other groups
Only 2% transform their business using collected data and insights derived from it
These numbers are alarming considering the advancement of technology in contact centers in the last ten years and the importance of understanding and retaining customers. One might wonder why we don’t see a greater use of all the rich customer data that is being retained. The answer is simple: There is not an easy way to collect, correlate and report on data that comes from different channels and resides on different platforms. But let’s look more closely at this issue.
There are typically two types of data sets collected in contacts centers:
1. Customer feedback
Survey feedback data sets typically hold the answer to basic “what?” questions such as, “What is the level of customer satisfaction?” or “What is the likelihood to recommend?” By collecting answers to these and similar questions, surveys can provide answers related to why satisfaction ratings are high or low, but these responses can only be obtained in text comments that are not always provided by customers. Ratings and satisfaction levels are important, but this data alone is not sufficient to derive actionable insights without the rich contextual data contained in survey verbatims.
2. Information about customer interactions
Interaction data includes customers’ open cases, phone calls, helpdesk tickets, sales orders, or any other customer interaction information that gets recorded, tracked and – ideally – attached to the recorded call. This data holds the answers to "why?" – “Why is this customer calling?” “Why is that customer pleased or upset?” “Why, exactly, does this customer want to return, cancel or upgrade?”
Think of these separate data sets as two dimensions that complement and help explain each other, keeping in mind, however, that they are often disconnected – and for good reason:
The nature of these data sets is not the same
Each of the two data sets are typically used for a different focus
They are collected and stored in separate repositories
Reporting on these two data sets is also different
In order to derive the most meaningful insights from collected data, contact centers need not only to understand the “what” and the “why” of customer interactions, but must also be able to correlate the two. Contact center managers need to look at both the feedback and interaction data as one unified data set. To connect the two data sets together, some contact centers try various home-grown applications and after-the-fact analytical tricks with great difficulty and little success. Quick fixes like these are neither scalable nor reliable.
Home-grown analytical methods are not scalable because the infrastructure and connection requirements are constantly changing. Issues of this type typically occur when changes must be made to data sources, survey campaigns, and questionnaires, not to mention changes to systems and software because of necessary upgrades. It’s very easy to see why this complex analytics environment can be very costly to maintain and is highly prone to unanticipated malfunctions.
Nor are the home-grown solutions reliable; a simple miss-mapping of data sets can yield exponential problems that are hard to trace and fix. All too often this translates into trust issues due to inaccurate reporting, and here, too, additional costs are incurred in order to fix the problem.
An integrated approach to bridge the two dimensions
A long-term, strategic approach is needed to solve this two-dimensional data problem, one that should include connected data sets and platforms as well as unified data collection, management, and reporting processes.
Connected data sets and platforms
Each day thousands, if not tens of thousands, of customer interactions are recorded in most contact centers, and it is therefore imperative for contact center supervisors and managers to have meaningful access to the combined data environment. For example, quality and assurance agent should be able to view survey results and relate them to the call recording that elicited the survey response. Furthermore, he or she needs to trace the answers back not only to the caller/customer, but also to the specific task, workflow, team and agent for QA and training purposes.
A well-thought out process for dealing with all this rich customer data is as important as the technology powering it. Contact centers need to have clearly defined and documented processes for collecting, managing and reporting on data. But this alone is still not enough: they also need a clear mapping of processes that get triggered based on results. For example, some contact centers have a recovery team that gets engaged when customer feedback falls below desired levels. A unified process and an integrated system allow call centers and the entire business to look through the full data stack in order to make drill-down and roll-up exercises quite easy and effective.
Drilling down from the what to the why
Consider the Net Promoter Score (NPS)® as an example to illustrate how. With an integrated approach to analytics in place, a contact center manager can look beyond the NPS and discover the root cause of these scores. If systems are connected and the requisite processes are in place, the QA manager can review interaction scores in the context of related survey answers, recorded calls, agent evaluations, workflow reports, score cards and more.
For a more detailed view, consider this example: a low NPS submitted via survey alerts the QA manager, who is able to identify the detractor by profile or customer segment and then compare this to other responses related to billing issues, and review specific call recordings. While this is valuable information, it’s not quite enough to take action. Exploring further, the manager is able to drill down to related workflow reports which suggests that customers seem to be frustrated because agents are not adhering properly to a new billing workflow. Upon further review, the manager recognizes that the agents have not been properly trained on this new billing system. With the ability for the QA manager to connect all these dots, the root cause of low satisfaction scores has been discovered, and armed with this information the manager can now set an action plan into motion that will include adequate training for the agents.
Rolling up from the why to the what
The opposite direction of inquiry is as useful and true as the drill down exercise. A contact center manager can start from a single customer mention of canceling service in a call recording and roll up from there to view survey scores, NPS® responses, and other related feedback. The magnitude of the problem can then be assessed by rolling up to satisfaction levels related to certain features of the product or service in question. If the issue is compelling enough to merit a response beyond that to the individual customer, it will be easy to define an action plan accordingly.
I didn’t say it was easy
Hopefully these examples help you understand the importance of approaching any Voice of Customer initiative with a strategic approach. This is certainly not the easy way out, but it is the only way to achieve success in terms of ROI and delivering the superior experience that your customers demand and deserve. A unified VoC approach built on an integrated platform is essential for contact centers that are trying to optimize a full understanding of customer and agent behavior with actionable data.
Accurate data, efficient processes and an integrated platform also enable contact center managers to correlate findings with the actions of their agents for coaching and development purposes, which in turn improves customer experience and loyalty.
Yes, you have a Voice of Customer program in place, and now is the time to derive the full value of both the why and the what dimensions of customer behavior.
For this, HP WFO Software can help. Contact us at firstname.lastname@example.org to learn more about our Voice of Customer and multichannel analytics solutions as well as our Professional Services consulting offerings.
 Forrester defines the age of the customer as a: “20-year business cycle in which the most successful enterprises will reinvent themselves to systematically understand and serve increasingly powerful customers." Organize Your Infrastructure Team For Customer Obsession. December 16, 2015.