Not so long ago, reducing customer turnover was a huge challenge for companies. While their best sales professionals were bringing in new customers at the front door, existing customers were happily walking out the back door. In fact, it was a case of mopping up the water.
Fortunately, this is no longer necessary: Artificial Intelligence offers a solution. Companies that are looking for a targeted and effective approach to reduce customer churn would do well to make use of the possibilities that AI has to offer.
What is customer turnover?
The number of customers that leave a company in a given period is called customer turnover. It is inevitable that some customers will leave. But as a company, you naturally want to do everything possible to keep customer turnover as low as possible. The level of customer turnover gives you a good idea of how your business is doing.
This is what customer turnover says about your business
If you are losing more customers than you are gaining, this is obviously not a good sign. In other words, customer turnover says something about the health of your business. In addition, you can see from customer turnover how satisfied customers are with the service you provide.
A low customer turnover rate can be taken as a compliment, while a high customer turnover rate should be taken as a strong signal that you need to pay extra attention to the customer experience.
High customer turnover costs money
Customers who commit themselves to your company for a longer period of time naturally bring in more money than customers who leave quickly. This applies in absolute terms, but also in relative terms: a customer who leaves your company within a short period of time has cost you a relatively large amount of money to acquire.
Investing in existing customers Therefore, it often pays off much more than investing in acquiring new customers. In other words: reducing your customer turnover ensures that the costs associated with customers are better balanced with the revenue they generate.
Sales AI helps you reduce customer turnover
Once a customer is gone, it is too late. But whether a customer intending to is to leave soon, that is hard to predict, of course. That is, that is how it was in the time for artificial intelligence.
Nowadays, most companies have a gold mine of data at their disposal. But many of them have no idea what they can do with all that data. And that's a shame: with the help of sales AI This is because you can easily convert the data that is lying around to make an overview of the signals and risk factors associated with the customer journey. This enables you to act in time and not lose customers unnecessarily.
Signal changes in behaviour
By using AI to analyse your data, you can easily shed light on behaviours that predict that your customers might leave. For example, do you provide a financial service and a customer's number of transactions suddenly drops? Or do you offer online software and a customer suddenly uses it less than before? Then it's probably time to take action. AI enables you to discover patterns in your customers' behaviour and to anticipate them.
Detect critical moments
Often, a product or service also has a kind of 'natural cycle'. For example, just before a subscription ends, customers often reconsider their choice: does the current product still suffice, or is it time for something new? There may also be certain times of year when customers leave more often.
AI helps you to identify the moments when you need to invest more in retaining existing customers. You can even distinguish between different customer profiles and determine this turnover for different products or services.
Reactions to negative experiences
Has a customer had a negative experience with customer service, has the price of your product suddenly gone up or is it difficult to change a subscription in the online customer environment? A negative experience with your service, product or customer service may cause customers to look elsewhere. Your data tells you exactly which experiences are at risk and which customers are affected at any given time.
Approach dissatisfied customers in time
Because AI picks up on alarm signals that indicate customers who may be less satisfied, your sales team knows exactly when to act in order to proactively ensure that the relationship with these customers is restored.
Often, a negative experience can be repaired with human contact. Using AI, you can ensure that this takes place at the times when it is needed.
Put extra effort into loyal customers
Extra efforts on loyal customers? Maybe this sounds superfluous at first: you already have these people, don't you? But those who are familiar with the 80/20 principle will find it an open door.
This principle states that 20% of your customers generate 80% of your company's income. Seen in this light, it is not so strange to invest regularly in this segment in particular! After all, ensuring that these customers continue to feel valued and deeply connected to your company secures a large part of your current income for the future.
AI is not a replacement, but a complement
Of course, AI is in no way a replacement for your sales colleagues. You still need a team of professionals to use sales AI to reduce customer turnover. Understanding your customer journey and who to call at what time is only the first step. After that, of course, it is still essential to have a team of service-oriented sales leaders who are stars in customer contact and know what strings to hit (and what tone to strike) to ensure that customers stay with you for a while.
Trendskout Sales Booster
With the Trendskout Sales Booster you will have a complete Sales AI software package including sales forecasting consisting of an umbrella system with many plug-ins. With these, we easily customise the software for your organisation. This saves a lot of programming, making it possible to implement the AI system for a concrete business case in just a few days.
Read more about the business case of Coeman Packaging
Our accessible software not only offers a faster and more flexible turnaround, but also higher profitability. This makes it worthwhile to work with sales AI even for smaller projects.
