Published in General

Making VOC Data More Actionable

There is a lot of talk in the industry about making Voice of Customer data more actionable. But to achieve this, you must first understand the type of data that is uniquely available and actionable in a successful VOC program.

Actionable data is data that you can use to improve the operations of the company.  It goes beyond answering “what” to understanding “why.”

VOC programs fail most often because they provide just scores, changes in scores, or data that is only part of the solution. This only tells business managers that their SAT scores are down this month without telling them the reasons why or pointing out comments and stats to help them see the impact of fixing the problem.

If you present your VOC results as broader business story, rather than just a VOC/SAT report, success will skyrocket. It is hard to do, and requires thinking big, being ready to tackle processes beyond your job scope, and thinking like an executive.

Unfortunately, many VOC practitioners place their efforts on the collection side, improving surveys and feedback mechanisms. They need to think more strategically about VOC data.  More surveys are not the answer, but more strategically designed feedback mechanisms that yield actionable data is what is needed.

How does data become “actionable data”?

Actionable data actually points to a specific condition or state within a customer’s experience that the company could have an immediate impact on, such as a specific product problem. Another example is an issue with an operational procedure or policy that causes some customer frustration, or perhaps a poor interaction with a customer service agent regarding a refund. These are specific types of insights that can point to specific actions a company can take to keep customers from leaving or to directly increase loyalty and satisfaction.

To have the most impact, actionable data needs to be shared with others in the company. However, many companies are collecting VOC and operational data solely on a departmental basis. They may be using several different tools that are not integrated, which causes them to have an incomplete view of customer experience. If you are able to combine VOC and operational data, you not only have what customers feel and say, but you can compare it to what they actually do. This gives you the most complete understanding of customer intelligence.

What types of VOC data should be included? 

The optimal VOC solution is able to incorporate and process both structured and unstructured VOC data. When you combine structured data with unstructured data, such as freeform replies to open-ended survey questions or comments on the Internet, you add another layer of depth that can give you a complete picture. For example, you can see what customers are saying about a poorly performing product, why customers in a specific region for a specific type of product and for a specific time period are unhappy, and what were the key issues that drove low satisfaction. Text analytics is the key to understanding these questions.

Incorporating text analytics into a VOC program helps companies understand the meaning of the comments and suggestions coming from customers so that they can effectively act on them. VOC systems are available today that provide a dashboard for analysis and reporting of structured data from call centers and customer surveys. The best approach is to treat text data just like structured data. This allows you to automatically process and analyze it, instantly seeing the top ten issues, suggestions or reasons customers left the company, and more.

Making VOC data more actionable should be the focus of any successful VOC program. Incorporating structured and unstructured data, using strategic thinking in designing feedback mechanisms, integrating with operational data such as CRM, and sharing the data throughout the company will ensure the greatest positive impact for your organization.

Chris Cottle is EVP of Marketing and Products at Allegiance