Elles has a lot of data about Lucardi's customers. She would like to use this information to get to know her customers as well. With this knowledge she wants to send customers personal mailings, with products, promotions and information that is relevant to them. Surprise customers with a mailing, that's the goal! Because it perfectly meets their needs, which they might not even know they had.
Elles started working on segmenting customers based on their behaviour. She looked at behaviour in purchases of specific material types. Nevertheless, the mailings were not 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 succeed in sending relevant mailings.
The segments that Elles applied were based on rules. In this case, if someone purchased gold products in the past, then gold products would appear in the mailing. This will be true for a number of customers, but customer behaviour is often much more complex. There are four dimensions on which Lucardi can become more relevant: information, moment, price and product. By analyzing information about customers, products, transactions and demographics, we defined customer groups with a clustering algorithm.
Algorithm determines per customer group, or ideally even per customer, what relevant products are and what the optimal moment is. The entire process is automated through a direct connection with the marketing automation platform.
Algorithm determines the campaign planning. The mailings and promotions within the campaign are chosen based on the strategy and inventory positions.