Elles has a lot of data about Lucardi’s customers. She would like to use this information to really get to know her customers. She wants to use that knowledge to send customers personal mailings, with products, offers and information that are relevant to them. Surprising customers with an email, that’s the goal! Because it perfectly suits their needs, which they may not even have known they had.
Customer behavior is not always straight forward.
Elles herself started segmenting Lucardi customers based on their behavior. She looked at the behavior in purchasing type of material. Nevertheless, the mailings did not become more relevant, because customers could not be segmented based on these simple rules. For example, Elles ignored gift buyers. Elles asked Veneficus how she could make her mailings more relevant.
Together we developed a personal mailing to regular
Lucardi clients that is almost 50% more effective.
We use algorithms to analyze customer behavior and define advanced customer groups .
The segments that Elles had applied were based on rules. For example, if someone had bought gold products, they would appear again in the mailings. This will apply to a number of customers, but customer behavior is often much more complex. There are four dimensions to which Lucardi can become more relevant: informative, moment, price and product. By analyzing information about customers, products, transactions and demographics, we have defined customer groups with a clustering algorithm.