Today there’s a huge shift in how companies are looking at revenue.
The focus is now rapidly moving towards reducing customer churn instead of acquiring new customers at all costs.
According to Harvard Business Review, it costs 5 to 25x more to acquire new customers than to retain existing ones, which is one reason for this shift in focus for businesses.
Another huge benefit of being retention focused is creating brand loyalty with your customers, not only to retain their ongoing business but so that they will review you positively and spread positive word of mouth
There are tons of ways of improving retention and you probably know quite a few of them already.
In this article, I’ll introduce you to something that’s not mainstream yet but has the potential to revolutionise the way you look at customer retention.
I’m going to walk you through what’s wrong with the current system, and how to make it better with customer sentiment analysis.
I’ll talk about how you need to analyse customer sentiments in your customer service conversations to find out how your customers are feeling - allowing you to identify pain points, solve issues throughout their customer journey and ultimately reduce customer churn and boost retention.
Typical churn analysis today takes a very passive approach to finding reasons why customers are leaving.
Many companies try to find reasons for cancellation through an automated feedback form emailed to churned users, telephonic conversations, or broad-level analysis of manual ticket tags that agents selected during the cancellation process.
Once this data is collected, companies analyse it to find trends and commonalities among the cancelled customers.
But this is only one small piece of a much larger puzzle, so analysing cancellation feedback forms alone can never give you the true insights that you are looking for.
For example, it can tell you that a lot of your new users leave after the 3rd month. Or the most common reason for cancellation tag was 'app experience' and ‘delivery_problem.
These are very broad strokes. Let's look at why this level of insight isn't helping your customer retention
While customer churn analysis is done with the best intentions, the execution using current methods often isn’t optimal.
There are two main problems with the customer churn analysis methods we discussed earlier:
Having to explicitly seek feedback from churned users through surveys and follow-up calls carries huge fundamental flaws - which need to be addressed immediately.
Example - Customers who have cancelled because they were facing delayed delivery. Had the company paid attention to it before cancellation, they could have spoken to their delivery partner and fixed it.
Example - Close-ended questions like "Why did you cancel?" with multiple choice answers like "Not using it enough, Not easy to use, Too expensive" are restrictive and do not let the customers express their true opinion.
Example - Someone may mention 'delivery issues' in their cancellation survey but possibilities are there were more issues that are captured in your customer service database. By only logging delivery problems as the reasons for contact, you can not get rich enough dataset to get granular insights.
Example - Sending out a 50 questions regarding a customer's journey may give you good data to look at, but its almost sure to have a very low completion rate.
Example - Asking just a couple of questions like 'Why did you cancel' and 'What should we improve' may give you higher rate of completion, but the data acquired can never give you wholesome insights.
The most fundamental step in improving customer retention is to understand the drivers behind what’s causing customer churn.
While post-cancellation data collection can help to a certain extent, it’s far from ideal.
What companies need is to understand the pain points and challenges that customers are facing throughout their journey and fix those issues at the source, before they become a churn risk.
Conducting customer sentiment analysis is critical to understanding how customers are feeling about a product or service throughout their journey.
The best way to understand customer sentiment is to analyse customer service conversations.
It is the most authentic form of customer feedback because they share it without ever having to ask for it.
Your service tickets, live chats, emails and calls contain loads of valuable information about what’s bothering the customers, what issues are recurring and how they are feeling throughout their journey. You can also deep-dive into particular topics and get to the root of the issue.
All of this fantastic actionable data already exists within your customer service conversations, you just need to harness it.
In this article, we touched upon a few flaws in only doing customer churn analysis post-cancellation.
We also spoke about being proactive and analysing customer sentiments to benefit from the wealth of insights that customer service conversations have to offer.
If you’re struggling with a low customer retention rate and have been trying several things, it’s time to pause and think about whether are you proactively finding out the real reasons users are churning and fixing them or are you only focusing on plastering problems as they surface, or worse, not doing anything at all because of lack of insights or direction.
Customer sentiment analysis of customer service conversations is the most holistic way of looking at customer data.
When combined with customer churn analysis, it can give you the kind of insights that can enable you to nip problems in the bud.
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