5 Experience Predictions for Retail in 2019
In the retail industry, one that’s known for its ability to continually reinvent itself and find new ways to connect with consumers, the huge shift in consumer behavior from physical...
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Wai Au is Global Customer Experience Lead at the Sage Group, a major provider of enterprise software. He has been a text analytics user for over 10 years.
There’s a big difference between understanding the scores customers give you and understanding how they really feel. On their own, satisfaction scores give you a partial impression about a customer: how he or she feels about the issues you thought to ask about. But when you’re able to hear their thoughts in their own words, you get a much more accurate impression of how your business as a whole is performing.
Particularly when you have lots of customers or lots of feedback, text analytics is a very valuable tool — helping you make sense of huge quantities of written customer comments quickly and efficiently. But it’s also an easy capability to misuse. Here are four principles to getting the most out of text analytics, ensuring you use it to drive real value in your business:
Combine text analytics results with other types of data
Once you’ve analyzed a batch of customer comments, there’s often a temptation to charge forward with an action plan for any issues you’ve found.
But your plans shouldn’t be based on text analytics alone. Incorporate other measures into your decision-making, whether it’s customer satisfaction scores like NPS or operational metrics like ASA (Average Speed of Answer). At Sage, we’ve even used our data to predict the business impact of customer experience improvements. We’ve found that promoters tend to renew more and spend more than detractors, and can use these findings to plan smarter improvements.
Bringing in other data allows you to validate initial text analytics findings, and to make them more accessible to colleagues who aren’t customer experience experts. It also helps you monitor your improvements on an ongoing basis. Rather than waiting for another batch of customer comments to run another analysis, operational metrics and NPS can show you much sooner if your plan is actually generating changes.
Keep insights simple, and focused on action
Text analytics often reveals unexpected details and opportunities within customer feedback. But as interesting as these findings can be, not all of them will be critically important to your company.
When sharing these findings, or turning them into action plans, distill them as much as possible into a few concise recommendations. This is particularly important when you’re working with company leaders. Sage’s executives have come to value customer comments very highly, but when we share text analytics, we always focus on the three to five things most important things for us to work on. Medallia’s reporting really helps us identify those three to five things.
This focus on simplicity and actionability has led to a big increase in analytics usage for Sage teams across the globe.
Don’t treat text analytics as a substitute for reading comments
As I’ve mentioned, customer comments are important because they help you understand the feelings and needs behind feedback scores. Text analytics helps you gain that understanding very quickly.
However, don’t get carried away by the depth of insight you’re able draw from text analytics findings. Good text analytics tools includes detailed sub-topics for each high-level one — and when people start clicking into those subtopics, and getting greater detail into the nuances of customer comments, they sometimes think that they’ll eventually understand exactly what customers are talking about using text analytics alone.
But ultimately, the real point of text analytics is to point you in the right direction. To really understand what customers are saying and feeling, you still need to read what they’ve actually written.
Share and define responsibility for text analytics
Sage is a large, diverse company. We serve customers in 23 countries, some of whom have access to over 50 products. This means there are too many written comments, about too many unique situations, for a single text analytics team to read on its own.
That’s why we’ve found it so important distribute responsibility for text analytics to people across the company. Our global customer experience team trains certain Sage employees in each country to use text analytics on their own — analyzing customer comments and resolving the issues they find. At the same time, our global team regularly checks in with each region to give advice and investigate pain points that cross borders.
This structure ensures that we find issues of all sizes — ones that are very small and specific, and ones that are too large for a single region to notice.