It’s exciting to see Harvard Business Review highlight the huge potential of real-time analysis of customer feedback. Not as an academic exercise, but as a core business benefit. As a result of the pandemic and accelerated digital transformation, most business leaders agree that listening to their customers has become more important than ever.
We live in an experience economy, where customer needs, expectations and experiences are shaped not just by direct competitors, but every brand they interact with.
“In order to succeed, firms need to understand what their customers are thinking and feeling.”
Building on this theme, Mohamed Zaki, Janet McColl-Kennedy and Andy Neely from the Cambridge Service Alliance (CSA) have written a fascinating article in Harvard Business Review.
Traditional feedback processes that focus on quantitative measures, is not up to the task
The authors highlight the huge amounts of time and money that firms spend on getting to know their customers better, yet “most firms are not very good at listening to customers.”
The problem is the tools and measures they are using. Quantitative surveys with NPS or CSAT scores remain the industry standard, despite:
- Requiring a huge amount of time and resource to create and report on.
- Providing a frustrating experience for the very customers the firm is seeking to impress.
- Failing to tell firms what their customers are thinking and feeling.
“Qualitative approaches, like focus groups or manually reading and analyzing customer feedback, were too labor intensive to scale. Now, technology has changed what’s possible, and tactics need to catch up.”
Unstructured text comments are a goldmine of potential insights
Businesses need a better way of understanding their customers, and they need it quickly. According to the authors, there is “a goldmine of good data if you know where to look and how to analyze it. Customers often reveal their true thoughts and feelings in the open-ended comment boxes typically provided at the end of surveys. In general, the content of these comments offers a much more reliable predictor of a customer’s behavior. Yet, these are often ignored, and if used at all, are typically used after the scores are computed.”
The authors solve this problem by analysing verbatim comments using an AI model similar to one of the models we use with our own clients. Their customer-centric framework extracted ‘what’ customers were talking about (activities, products, interactions etc) and ‘how’ it made them feel (emotions and sentiment).
6 key business benefits of using AI to track how customers feel, in real-time
As a result of their research, the authors identified 6 key business benefits that accrue when firms use AI to analyse their unstructured customer feedback:
AI can show you what you’re missing
Businesses often misjudge customer priorities. Text comments can highlight where internal assumptions don’t match with customer reality.
Train your employees based on what’s actually important to customers
Understanding evolving customer needs and preferences enables businesses to design training programmes that ensure staff and customers stay on the same page.
Determine root causes
The breadth and depth of AI algorithms can identify not only the surface problem but also what’s causing it.
Capture customers’ emotional and cognitive responses in real-time
Feedback is captured and analysed while it’s still fresh. As the authors noted: “It is important to capture real-time feedback as emotional and cognitive responses can dissipate over time and details of the interaction are likely to be forgotten.”
Spot and prevent decreasing sales
Identify early-warning signs of defection, based on the issues and experiences that customers share.
Prioritize actions to improve customer experience
By monitoring feedback in real-time, businesses can quickly identify and respond to issues and then measuring the impact of their actions.
To read more about how MyCustomerLens is using AI to help firms create stand-out brands and experiences, click here