With predictive analysis, you can give your customers exactly the right message at exactly the right time. If you know how to use that is. Here, we share our best tips.
The most important thing when you start working on predictive analytics is that you know what you really want to use it for “.
Do you need to attract new customers, increase additional sales or convince old customers to remain at all?
If you don’t know this, you can collect as much information as possible and analyze it without getting any value. It is the goal of the analysis that determines what you need to know.
Secondly, it is not enough that a small group in the marketing department works with the analysis.
In order to take advantage of today’s opportunities in the form of available customer data, analytical opportunities and effective marketing techniques, a company must collaborate cross-structural within its own organization.
The basis for successful use of predictive analysis lies in ensuring that the company has the necessary information. But it’s not enough. The company must also have the ability to use it effectively for business development and customer communication.
To achieve this, all departments must contribute their different skills, tear down the walls and work together on the same level.
Then it is time to take stock of what information is needed and not least what information you already have.
Don’t start running out and gather unstructured external information without digging where you stand. The IT department can often pick up a lot of customer data that we didn’t even know we had. But they need to know that it is needed to produce it.
If you sell skincare products, then ask how much time customers spend on their skin, how much they are willing to pay and how often they shop. They often gladly share with them, just remember to ask the right things so you really get useful information.
Last but not least, predictive analytics is not a one-shot campaign.
This is about making predictions, and the more you learn from your customers, the better the predictions you can make. Let what you learn go back into the analysis work, so you can constantly refine your results.