Customer management can be a difficult process if we do not understand why our customers behave the way they do. Why are they leaving us? Is it because they are not satisfied? Could we have anticipated it and take action before it was too late? Moving from a reactive customer management to a proactive customer management strategy can help you identify customers that are likely to stop buying, or customers that are displaying unusual trends.
Making the most of your data by using applied AI we can help you identify key customers and prioritise those your team should focus on, minimising revenue at risk. Simultaneously, our Azure Proactive Customer Management tool also integrates a recommender engine that suggests what products or services your customer is more likely to buy, and consequently increasing revenue opportunities.
For each customer, we use several AI models to calculate risk probabilities and the potential value at risk. Using data you are already have, such as historical transactions, customer and product details, customer support history, etc. you can take a data-driven proactive customer management approach and take action now, not when it is too late.
After the AI models have finished computing the predictions, the results are delivered in an easy-to-use dashboard where you will find all the information you need to start reaching out to your key customers, focusing on fixing problems and driving revenue growth.
If you have a large number of products and / or customers, Azure Proactive Customer Management is for you. Examples include:
