“When customers share their story, they’re not just sharing pain points. They’re actually teaching you how to make your product, service, and business better.”
Kristin Smaby, “Being Human is Good Business”
Capturing customer feedback at scale is no easy task, but vital for most companies. As the quote from Kristin Smaby explains, there are a lot of actionable business insights to be found in customer feedback, especially the kind of feedback that captures the whole story like reviews or open-ended survey questions. This blog post describes how to deconstruct customer stories in order to arrive to arrive at actionable business insights that will improve customer satisfaction. I will be using some examples discussed in our ebook “Text Analytics for Multi-Property Hotel Managers”. For more examples and analysis, check out the full ebook.
Individual Level Stories
The individual level shown in the graph has to do with each customer’s experience related to the brand. When customers give feedback, they will describe their individual situation. Naturally, this kind of communication is done using written “conversational language” because humans construct, communicate and process their reality through stories. At scale, this kind of data is hard to analyze manually, so an advanced text analytics solution needs to be used instead. The process described in this blog post is applicable to both manual and automatic analysis.
Identifying the themes your customers choose to discuss is important. Most of the reported themes shouldn’t come as a surprise. In the case of hotel reviews, the topics that show up are “room” & “service”. The third most prevalent topic is a surprise: towels. This topic is more important than price, TVs, or breakfast.
Opinions can be captured from both unstructured and structured data. What makes text a superior source is because it’s possible to measure opinions in relations to specific topics. Positive or negative mentions point at the same topic, building a coherent picture. Mentions of “clean” or “fluffy” towels made hotel customers happy, whereas “dirty” or “old” towels created the opposite effect.
The context in which the event happened provides additional information. Access to an organized library of customer comments for reference means you can always reference the original comments in order to understand exactly what happened.
Aggregating individual stories into statistically significant sample sizes becomes important when trying to establish relevancy. This will ensure that your company focuses on what’s important: the most valuable customers and the improvements with the highest ROI. It will safeguard against situations like throwing resources on vocal dissatisfied customers that are beyond retaining anyway.
Finding high-level correlations between metadata (for example time, geographical location or type of touchpoint) and customer comments can reveal which areas need the most attention. Perhaps certain locations need refurbishment, issues with the staff were isolated to a one-off event, a touchpoint is not optimized well. Advanced systems like Keatext can detect such correlations automatically and immediately bring them to the attention of the user.
Continuous monitoring of the data can provide an excellent way of measuring how the mentions are evolving over time. All that is needed is a date- and timestamp that accompanies the customer comment. This gives an organic measurement of the effectiveness of improvements over time.
The Result: Actionable Business Insights
Working this way with customer feedback will result in visible insights. For example, in our case study about hotel management, we found that good quality towels (clean and fluffy) would increase the overall satisfaction level by 25%. This insight is valuable because it’s not immediately apparent and has the potential of yielding a high ROI. These are the kind of insights one can work by working with customer stories. How fast you get there is up to you…
For more ways AI can help with empowering your customer to have their voices heard, check out our webinar.
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