Effectively combat churn and customer inactivity

Churn is not inevitable, but many companies are still looking for proven solutions to rekindle the interest of their inactive customers or to stem the tide of those who have decided to do without their products or services. If the majority of the actions implemented often have few results, this is not surprising. Based on traditional marketing approaches, they are completely drowned out by the mass of solicitations that customers have also received from their competitors. And because each of them is treated like any other, then unsurprisingly, those individuals who no longer feel connected to the brand by a singular relationship and customer experience, do not follow through on their poorly personalised attempts to retain or reactivate them. Yet there are solutions!

Companies are still not making sufficient use of their data

They have the raw material to fight churn effectively: their data! But it is necessary to make good use of it and to extract all the information value that will lead them to know their customers almost better than they do themselves, because they will be able to anticipate their expectations with formidable precision and then respond to them, exactly at the right time and through the communication channel that they like best. However, they need to be able to analyse all this information extremely finely for each customer who is about to leave them or has already been lost, to predict their needs accurately and to interact with them in a hyper-personalised way via the right message or the right offer.

Humanly impossible? Yes, but precisely within the reach of the CRM CopilotCRM platform, integrating the performance of machine learning and artificial intelligence. Where humans reach the limits of their analytical faculties when faced with the sheer volume of data to be studied, predictive marketing solutions take over, opening up new possibilities that are particularly effective in addressing churn issues.

Why do customers leave?

If the business operates on the basis of time-bound commitments - i.e. subscriptions - it is likely that the churn rate will be high if the company still uses marketing approaches that focus on its services rather than on the needs of its customers. Without a specific relationship with their customers, brands generally dread the subscription expiry period because there is nothing to stop them from turning to competitors, even a last minute promotional offer that seems to be well-targeted but actually misses the point.

Why do customers become inactive?

Another important issue that weighs on companies that do not offer long-term commitments is the problem of dormant customers, which largely affects retail professionals. Indeed, brands often find it difficult to reactivate some of their customers who no longer consume their products or offers and no longer interact with their services. Here again, the traditional tools used to try to retain and engage customers have reached their limits, as they are not based on the expectations of the latter but on what the brands market and, more often than not, according to seasonal patterns that one hopes will correspond to the desire of each of them. Under these conditions, it is difficult to revive the interest of inactive customers. Unless you completely change your approach.

Identify the warning signs of churn or inactivity

In a strategy aimed at reducing churn or the number of inactive customers, it is essential to refocus on the customer and to develop customer knowledge based on a methodical and in-depth analysis of data. This is to be able to model the behaviour of each individual and accurately predict their future actions, to detect their intentions, even the most imperceptible.

In concrete terms, all the information collected from customers must be sorted and cross-referenced: socio-demographic data (marital status, profession, etc.) and contractual data (amount, duration, etc.) as well as any interaction with the various services and points of contact (purchases, browsing on the web and social networks, history of exchanges by email, telephone, in-store, uninstallation of your application, etc.). The company will then be able to detect well in advance the risks of unsubscribing or inactivity and act to counter them.

Win back customers 

Once all the data relating to customer profiles and behaviours has been gathered, the brand will be able to draw a maximum number of lessons from it: what are the most effective actions to put in place for each of its customers in order to respond to their requests and transform their customer experience into a hyper-personalised relationship that is long-lasting and fruitful for both them and the brand. The analysis feedback is very diverse, such as identifying the reasons for dissatisfaction or the commercial messages that do not succeed, favouring the paths that have the greatest chance of leading to a new commitment or a purchase, not soliciting this customer for the moment or on the contrary, reiterating it at a certain time given the expiry date of their contract...

Each type of risk can be modeled on the basis of operational and score indicators. This enables the company to automatically trigger the most relevant communication tools (messages, offers, etc.) for each person concerned, according to the sales objectives and constraints previously set (sales pressure, eligibility logic, etc.). It is thus possible, with a view to reducing the number of inactive customers, to target only those who are most likely to be reactivated. By excluding very low potential customers from their action plans, companies will reduce their costs accordingly and optimize their ROI.

As our tools continually learn from customer history, which is itself constantly updated, brands have the most relevant levers at their disposal to maintain the link over time and prevent their customers from falling back into inactivity or being tempted by the competition. As for customers who have left, nothing is final! The enhanced knowledge of customer behaviours throughout the customer journey enables us to build models capable of proposing relational possibilities likely to win back each and every one of them.

What next?

Then, it will be enough for the brand to continue to communicate with its customers in an ultra-personalised way and to perpetuate this unique relationship.