Big Data. Unstructured Data. Hundreds, thousands, millions of customer comments.
Wrapping your head around thousands if not millions of customer comments and pieces of feedback, let alone what to do with it, is a familiar challenge for CX professionals.
The good news is that technology can help you make sense out of all that feedback—even when it comes in the form of unstructured text. Text analytics (TA) software uses machine learning, together with statistical, linguistic, and visualization techniques, to automate the analysis of text-based data. That data can come from customer feedback surveys, online reviews, social media, chat sessions, or notes that employees write to capture feedback during customer contact sessions.
Text analytics brings big data capabilities to customer experience management. And, because it doesn’t require end users to draw on advanced statistical techniques, it can be a powerful tool for engaging business partners and driving organizational change—the types of change you’ll need to make, to make the improvements your customers want.
To understand how customer experience leaders are using text analytics most effectively, The Medallia Institute interviewed 12 companies successfully using the technology to promote customer-driven change.
We discovered six practices that customer experience managers use to get the most value from TA:
1. Become a true business partner. Getting useful insights from text analytics is a bit like peeling an onion: each set of analysis generates new insights, which, in turn, should generate new questions. Partnering with managers who have a deep understanding of the business will ensure you dive deep into the right issues, ask the right questions, make reasonable interpretations, and draw the right conclusions. To be a true business partner, focus on the things that drive value in your business and the big issues that senior leaders care most about.
2. Bust silos with cross-organizational dialogue. Get people talking. Use TA insights to stimulate dialogue and debate across departments. When you bring different departments together to discuss TA results, you not only bring more knowledge to bear on problems, you also build ownership and commitment to finding and implementing solutions.
3. Build empathy with stories. It’s easy for senior leaders to fall out of touch with customers. TA surfaces compelling and emotional stories that vividly illustrate a customer’s experience. Engaging senior leaders with real stories builds empathy with the customer, and persuades key decision makers to take action.
4. Use data to validate and innovate. Text analytics is relatively new, and managers often need reassurance that its results are valid. Build confidence in your analyses by replicating findings that people already believe. For example, show that TA yields results consistent with more traditional, quantitative analyses. Once you show people that TA produces reliable results, they quickly want to use it to surface new ideas and opportunities for innovation.
5. Stimulate organizational learning. Because text analytics can be applied to unstructured data gleaned from any channel or data source, it can spur learning across otherwise siloed parts of the organization. By integrating customer feedback from different sources, across different channels and business units, the best TA users detect patterns and relationships that might otherwise be missed.
6. Act at the local level. The themes and insights revealed by TA become most useful when they inspire action at the local level. Leverage insights generated centrally (i.e., from large volumes of data across the organization) to stimulate targeted exploration locally—for example, at a given store, branch, or call center. This helps local managers find and solve problems that would be difficult to identify from a smaller sample of customers.
To learn more, check out our whitepaper, The Big Story Behind Your Big Data.