General Election 2019: Qriously Prediction, Plus Survey and Social Data Analysis
By Abraham MullerDec 11
Published August 2nd 2018
With so many telecoms providers on the market, keeping track of competitors and what tempts consumers to jump between them is no easy task.
Identifying churn risk is a social listening use case the React team hasn’t explored for a while (if ever) and when we were presented with some numbers from one of our analysts Natascha Sturm, we wondered why not.
She presented us with a Brandwatch Analytics dashboard that showed how people talked about three large UK providers, with the mentions categorized by intent to switch. It was fascinating to look at, so we thought we’d share some of the learnings on the blog.
Please note that we have anonymized the brands involved here, referring to them consistently throughout as Provider 1, 2 and 3. We analyzed conversations surrounding each of them in regard to customer service across public social media posts.
While it does depend on the influence of your customers, generally speaking the more your brand is getting complained about in public the more visible the negativity is going to be.
Provider number 1 has clearly not had the best year. Even when looking at the negative mentions as a percentage of all mentions, they still came out worst.
Within these complaints are all kinds of different issues, from bad mobile internet connection to slow communications.
By monitoring the level of negativity compared to competitors and the common complaints that arise, telecoms companies can benchmark themselves against their peers as well as gain insights into what improvements are being demanded most by customers.
Looking at competitors’ complaints can also help them gain a competitive edge. For example, if Provider 2’s waiting times are continually complained about online, Providers 1 and 3 could use their marketing to pledge to never keep people waiting, encouraging those annoyed by Provider 2 to switch to them.
Unexpected churn is always bad for businesses. And in the telecoms industry, when there can be literally millions of customers to deal with, building a personal connection with each of them is never going to be easy. That means it’s not always obvious when a customer is going to decide to switch to a competitor. Identifying trends around why people switch away from your company could help with forecasting and help them address those issues before customers make their final decision to switch.
To give you a more concrete example, here’s conversation around switching away from particular providers gathered over a year. Again, Provider 1 has a lot more switch conversation than their competitors, and it’s actually risen year on year.
By assigning a value to each of those mentions (the average annual revenue per customer, for example), analysts can begin to see in real terms how much is at stake. We’ll get to this in lesson 4.
Keeping track of competitors that are tempting your customers away can help networks to identify what those temptations are and to address them.
Natascha was able to work out which companies networks’ customers were talking about switching to. Given what we’ve already told you about Provider 1, you might find the following results surprising.
In fact, Provider 1 is doing a pretty good job of tempting Provider 2’s and 3’s customers away from them. Meanwhile, few people seem to be discussing moving from Provider 1 to 2 or 3. Perhaps Provider 1’s customers are being tempted by other competitors that we didn’t measure.
That said, Provider 3 is having more trouble from Provider 2 than Provider 1.
With a full set of competitors, this data could give networks more insights on who their real rivals are and how that changes over time.
Putting the data we have together we can understand the full picture a little better.
Based on the above analysis alone, it appears that Provider 1 might be expecting to gain the most custom from its competitors’ current subscribers. But, given the amount of intent to churn conversation, it’s also the provider that seems like it’s going to lose the most overall.
If we combine the number of people intending to switch away from a provider and incorporate the people switching to that provider, we can use their average annual contract value to give a monetary figure describing the amount the company could expect to lose or profit based on these conversations.
Here’s an example, although please note that we’re looking at customer service related conversation only and only looking at a limited number of competitors.
|Provider||Number found switching away from them||Number found switching to them||Estimated overall loss/profit*|
Of course, there’s more to this than social media mentions. But if telecoms providers are looking for ways to improve their offering and keep an eye on churn from customers who aren’t bothering to respond to mid-contract surveys, this is definitely one way to do it.
Special thanks to Natascha Sturm for sharing her telecoms analysis