Segment or individual personalization
The concept of user segmentation was formalized by Wendell Smith in 1956:
“Segmentation is a technique of segmenting the market by isolating groups of consumers with homogeneous behaviours or purchasing habits. In this way, the market is divided into groups of customers with similar needs and preferences (so-called market segments), enabling the company to better adapt its marketing policies to the target market. “
This concept is widely adopted for marketing strategies because the human mind can easily reason on only a few elements.
It is used by the pioneers of pesonalization because it greatly simplifies the computer treatments in three stages:
- Definition of the characteristics of each segment or cluster. The number of segments is often limited to ten.
- Assign a segment to each user.
- Select a pre-defined content for all users in the segment.
By adopting this approach, the E-commerce must therefore regularly review its business strategies for the different segments. Such an operation is costly and tedious to apply.
On the other hand, when a user is classified into a segment, he receives the same responses as all other users in that segment. The personalization service cannot adapt in real time to subtle changes in user behaviour to understand his intentions and offer the most relevant products at any time This is a first step of personalization (personalization ready) and not the full personalization step.
On the contrary, individual personalization consists in creating interactions addressed to each user individually. McKinsey & Company believes that personalization can reduce acquisition costs by up to 50%, increase revenue by 5% to 15% and boost the profitability of marketing expenses by 10% to 30%.
Therefore, MyDreamMatch has engineered from the very first day an engine based on the concept of individual or 1 to 1 personalization. This engine is certainly more complex to design but it is simpler to implement by the merchant and it offers richer services.
The architecture of the MyDreamMatch personalization engine allows to discover the intentions of each user at every moment to present the products that really match at a precise moment. The user feels better understood, he is quicker able to buy on the site and becomes more loyal to the site and brand.
Software engineer from Supélec Paris, I worked as a developer, architect and then manager for many years at the Research Center of IBM and then in the Cisco European organization.
Passionate about Artificial Intelligence, I decided in 2015 to create my company MyDreamMatch in order to make personalized recommendations accessible and easy to use by the largest number of web sites.