Relative Insight’s latest Spotlight Series webinar showcased the power of root cause analysis software for customer teams. James Cuthbertson, CRO at Relative Insight, highlighted how AI-powered technology identifies why CSAT and NPS surveys go up or down.
“CSAT and NPS scores will go up, and they’ll go down,” James noted. “When it’s going up I’m sure that your leadership are very happy, and you don’t get scrutinized too heavily. When it goes down, leaders will ask ‘why is it going down?'”
Traditionally, responses to this question will have required manual analysis of one set of survey responses. In the webinar, James outlined why you need to apply consistent, repeatable root cause analysis techniques to truly understand what’s driving rises and falls in NPS and CSAT scores.
Continue reading for a summary of what James discussed in the session, including how specialist root cause analysis software offers a more comprehensive solution than LLMs like ChatGPT, how to get the most from automated root cause analysis and some of the answers you can extract from always-on analysis.
Or, if you want to watch the webinar in full on demand, you can access it via the banner below.
Making decisions based on why CSAT and NPS scores are changing
Customer score fluctuations are good at telling you how customers’ feelings have changed. However, they’re unable to tell you what’s causing it. James demonstrated how comparative root cause analysis techniques help you get to the why behind NPS, CSAT and other customer ratings.
Using an example of a retailer’s CSAT survey responses from a month where its score fell, he highlighted how root cause analysis software identified an increase in respondents talking about delivery issues and damaged products. James emphasized that comparing responses over time is vital to pinpointing what’s causing scores to change:
“We’re able to get to the source of the problem very quickly; what’s driving that drop. The way that we’re doing that is by comparison over time. If you just look at that month in isolation, you’ll see different themes emerge from your data. But what you don’t know is if they’re new, if they’re problems that have just always been part of your data set, or if they’re actually on the decline.
“And so by comparing month on month, week on week, day on day, we’re able to help you understand what is current, what are the things that you really need to pay attention to and really address to prevent that CSAT or that NPS score falling further.”
By comparing responses on a consistent, repeated basis – in this case month on month – customer teams can identify whether praise or complaints are in line with normal feedback, or if an issue has arisen that requires attention. In this example, the retailer took steps to address delivery problems identified in its CSAT survey and saw its score rise the following month.
Harnessing automated root cause analysis
James also discussed how customer teams can utilize automated root cause analysis for NPS, CSAT and other customer surveys.
He presented an automation blueprint that organizations should aspire to emulate for smooth analysis and reporting of text data. James outlined how Relative Flow, aligned with data collection tools such as Qualtrics and visualization dashboards like PowerBI, enhances reporting and allows senior stakeholders to make data-driven, impactful decisions.
“I’m not suggesting everyone should be seeing the world through this lens right now,” he noted, adding: “This is best in class, and what we’re helping some of our customers move towards because many of them already have these brilliant tools generating unstructured data. It’s about allowing us to harness that and start to bring the why into a previously quantitative, numbers-driven world.”
Part of impactful reporting is presenting data in an easy-to-understand way. James also showcased how Relative Insight’s Heartbeat tool, allied with Custom Themes, allows customer teams to track issues of interest within NPS and CSAT surveys.
Using the example of a manufacturer, James illustrated how the company tracked language relating to areas like “retailer issues” or “refund support” over time using root cause analysis software. This enabled the firm to visualize when issues were spiking in customers’ feedback.
Root cause analysis software solves problems
During the session, James focused on key business measures that root cause analysis software helps to explore and explain. Citing examples including call length, call failure rate, and FAQ and resource failure – along with CSAT and NPS – he discussed the outcomes of analyzing qualitative feedback around these metrics.
“A lot of customers are obsessed with these metrics — and rightly so,” he said. “But what’s the outcome? You do the analysis and what happens?”
He went on to discuss ways that businesses can use insights from text data to create organizational change. In particular, James focused on six examples of the types of change implemented following the use of root cause analysis software:
- Improved CX flow
- Training agents
- Improved FAQs / resources
- Partial process automation
- Implementing change
- Specific organizational decisions — e.g. product recalls or rebrands
Do you know why your metrics are going up or down? Have a continuous influx of text data you need to analyze, quantify and visualize? Speak to one of Relative Insight’s experts to find out how our root cause analysis software can help you find answers.
