It’s not about how you get those customer insights, it’s what you do with them
Understanding customers is a key postulate of modern business. There are hundreds of different types of software or research services providers that aim to shine a light on what happens in the heads of consumers. At GemSeek we have always been method-agnostic when it comes to gathering data. We use primary research, data analytics and data science to unearth the truths that customers are trying to tell us and, more importantly – answer question that follows inevitably: “Ok, what should I do about it?”.
And somewhere along the way, we realized that in order to answer the “so what” question, we need not only inquire about past experiences, but also try to predict what happens next.
It’s almost like we work at the intersection of past, present and future:
- Past – we help separate the noise and the signal to truly understand things that happened. Sometimes the answer is apparent, sometimes we have to dig deeper than usual with an advanced method like Root Cause Analysis to understand the multiple factors that led to an outcome. Why did those customers leave us? Why did we get so many complaints about that new product?
- Present – we keep an eye on what’s happening at the current moment by examining real-time-customer feedback
- Future – we use data science to predict with a high degree of accuracy what customers are likely to do in the future
Getting customer insights about past experiences
Understanding past experience is fairly straightforward. Regardless of whether you are a B2C or B2B company, you have some kind of customer survey setup and in addition to it, you might also have any of these sources of feedback:
- Notes from client meetings
- Customer Service Agent notes
- Transcripts from customer calls
- Transcripts from zoom meetings
- Customer feedback surveys
- Chat transcripts
Customer surveys are fairly easy to setup and there are no limits to them, but because of this we often witness the phenomenon of the “all-consuming CX Feedback programme” – surveys contain 50 or 100 questions that most people abandon part-way through and CX or insights managers spent more time preparing reports than analysing root causes or fixing issues.
If you, too, feel like you are slowly being pulled towards a supermassive black hole of questionnaires and Power Point reports, we summarized our experience with hundreds of CX programs setup in these 3 best practice principles:
1. Use available tools for their intended purpose – you don’t have to interrogate all your customers on all matters all the time.
- Use short always-on surveys that capture only the essential information
- If you need more details about a specific topic, send an ad-hoc survey
- If you are trying to answer a specific strategic question, try a qualitative research project (a focus group, for example) with a small group of customers.
2. Go outside your current customer base.
It’s not enough to talk only to your customers – talk with the customers of your competitors – they will give you much needed context. In addition, such types of benchmarking research projects allow you to calibrate the experience you deliver vs that of you competitors.
3. Audit and update your program regularly
Businesses change, priorities do, too. We recommend to audit your CX feedback programme to fine tune that it is still fit for purpose
- Are you looking at the response rates of your surveys – are they going up or down
- Are you able to further dissect your CX feedback and link it to customer personas or segments?
- Is there an internal Owner for every question you ask? If not, why are you asking for your customer’s time?
- Is there an internal Owner for every KPI you measure – who is accountable for a drop in that measure – and what can they do about it?
Real-time customer insights to act quickly
Outside of customer surveys, there is a gold mine of insights, which in addition to being full of profound insight, is also real-time and allows businesses to act rapidly. What I am talking about? User-generated content. Text data is basically everywhere: ranging from survey responses to emails, complaint forms, call center agent notes, chat box conversation to unprompted and genuine feedback (which is my favourite) coming from social media, forums and reviews for example. The granularity of insights coming from text data is unprecedent and often underutilized and siloed.
Here are two of stories from our experience – from very different industries, which only comes to prove the universal power of text analytics consumer insights.
As you know the telecom industry is one of the most data-rich and data-intensive industries. The volume of individual pieces of text feedback can easily surpass 5 million when collected via different channels: transactional and relationship NPS surveys, product surveys, call agent notes, feedback forms and many others.
It means that no matter how your customer experience program is structured you can get text analytics insights across every touchpoint and for every product. You can also uncover brand insights that will help you ultimately improve your messaging and communication with clients and show them that you don’t only listen but act on customer feedback.
For one of our clients in the industry we created a map of more than 200 topics in a customised topic framework. What we found out, on top of as-expected evaluations of product and sound quality, reliability, and others, was an issue with the TV service of the competitor our client didn’t know about. Our client, on the contrary, had the solution included in the standard package they provide and they always assumed that it’s the same for all other providers. Armed with this information, they launched an advertising campaign to target this issue competitors’ clients are experiencing to attract them.
The next success story is about a large multinational retail chain that had a very specific issue at hand. In a particular region of Germany, their shops started to underperform regularly, visible through a drop in their sales. There was no rational explanation and no indication on the reasons based on pre-defined CX metrics. We turned to the unstructured customer text feedback to look for drivers of dissatisfaction that were specific to these locations. We discovered an impactful negative sentiment topic formed around “Changing rooms” in the underperforming shops. Further analysis allowed us to conclude that the length of the curtains in the changing rooms was the main reason for reduced sales. The impact was immediate: 1 month after the issue with the curtains was addressed, sale volumes across the region returned to the expected levels. The next logical step for them was linking CX improvements to sales in shops and understanding which were the most important drivers which impacted sales at each branch location. They were able to understand the value of NPS across branch locations, as well as drivers which influence specific customer groups- ex. women vs men, various age groups, demographics, etc.
Customer insights for the future
NPS and customer surveys are great for giving an overall view of your customer satisfaction. However, these is one major problem with them – they are as good as the fraction of your customer base that actually bothers replying. In most (B2C) industries response rates rarely go over 20%, which means that you never hear from 4 out of 5 customers.
Around 5 years ago we worked with several clients to develop a solution to this challenge. We called it Predictive NPS. Our clients can now predict the NPS (or satisfaction levels) of the silent majority of customers who do not respond to surveys with an accuracy of over 85%.
And our most successful clients actually use this insight to provide personalised service. Every day their Service teams are provided with lists of customers which they contact proactively. At the cost of a phone call a customer’s issue can be resolved and that customer can be retained. On an annual basis, we see churn in these cohorts reduced by 30-40% – this means hundreds of millions of retained revenues for companies which introduce Predictive NPS in the first 2-3 years. And, most rewarding of all – we witness increased employee engagement and customer engagement from the mere fact that a problem has been resolved with little or no effort, often to the surprise of the customer.
Read the whole success story