Better customer targeting

[phonenumber]

Predictive analytics can give you the information you need to identify customers who are likely to churn (stop interacting with your brand) - for example, if they have stopped opening your emails or interacting with your social media. You can then focus on exactly what measures you need to take in order to reel these france phone number list customers back in and keep them interested in your products. This can involve using methods such as dynamic pricing - offering different customers personalised discounts, discerned from data gathered on their previous purchases.

These are both examples of how predictive analytics can help you to better understand (and therefore target) your customers. It ensures that you’ll be spending time engaging with the customers who need and deserve it the most. Without predictive analytics, you run the risk of investing time and energy in the wrong customers - which will drain your resources, distort your customer insights, and ultimately lower profitability.

Building customer loyalty
Everyone wants loyal customers - these are the customers who are likely to go on to become valuable brand ambassadors and spread the word of your products far and wide. Not every customer will become an advocate (as nice as that would be) - so how do you decide which customers deserve your attention?



Loyalty rewards programmes, based on preferences discerned from predictive analytics, are a great place to start. By knowing which products and perks tend to appeal to your customers, you can heighten the value of your loyalty schemes, and make your customers more likely to engage with them enthusiastically. You can also use predictive analytics to determine every customer’s lifetime value - this will help you to identify the customers that are likely to be worth investing in.