What is worth more – a quick sale or a long-term customer relationship?
Anyone who is interested in positive business development in the long run must not try to sell something come hell or high water. The key is to maintain a long-term customer relationship. And for that, an AI system has to understand what is important for the company and what is beneficial for the customer. We call it enhancing the customer lifetime value.
Customer lifetime value (CLV) is the total amount of money a customer is expected to spend in your business, or on your products, during their lifetime. This is an important figure to know because it helps you make decisions about how much money to invest in acquiring new customers and retaining existing ones. Let us demonstrate this with an interesting example: The CLV of a car owner might be as much as 30,000 euros if they only buy one car from one brand. But the CLV of a regular coffee drinker might be even higher than that if they drink a coffee-to-go twice a day on their way to work and back – it depends on how long they do it for. One thing that we have learned from that simple example is that we should value our customers in the long term.
This means that we will do everything within our power to ensure that satisfied customers remain satisfied customers of ours in the long term. First and foremost, we will provide them with the expected performance and offer reasonable rates. But the customer experience on the product side is only half the battle. Ensuring our customers are happy in the long run also means avoiding making them unhappy. It might sound simple, but it's not. Because customers aren't annoyed on purpose, of course, but inadvertently. This can be because you make them an unwanted sales offer at the wrong moment, because you react inadequately to a complaint, or because you give them the impression that your agenda is sales-driven. All of this, in turn, is a question of communication. Up to now, our communication has been a string of individual customer contacts. But a dialog, an ongoing conversation that avoids misunderstandings and annoyance, would be much better. After all, it's only logical not to call a customer who complained about something yesterday to sell them an iPhone today. No one would be that insensitive in an ongoing dialog.
What we have in mind follows a different idea. Two buzzwords for this: "One Conversation" and "next best action". One Conversation stands for the approach of a continuous dialog with our customers, and next best action stands for the demands we place on our communication.
In other words, we would like to treat our customers like regular guests. Greet them by name, know what they like, know what they need and understand what they don't like. What's simple in theory, however, becomes a bit more complex with our multitude of touchpoints and content. That's why we're letting an AI system help us. With One Conversation, we're creating a database that remembers over time what makes sense with which customer and what doesn't. The system also continuously learns what works well and makes targeted suggestions that have a very high probability of success. It doesn't matter whether our customer called the call center yesterday, was on the website today or will chat on WhatsApp tomorrow – One Conversation keeps an eye on the course of the conversation so that every conversation partner, whether human or machine, can react on our side with the right "next best action". This is then not only smart, but downright empathic.
In our true One Conversation, we communicate both help and offers to each customer in the right moment and the right way – and that is not always at the first opportunity.