How the customers for promos are selected?
Analysis of transactional history allows you to deeply understand the preferences of each customer. Combining this knowledge with the analysis of promo history, we find the most interested clients under the current actions.
This allows to implement a precisely tarheted campaign instead of "carpet bombing" discounts.
What data is needed for learning algorithms?
The principles of LoyaltyLab.Target
The primary source is the history of shopping in the store. Its analysis allows us at a deep level to understand the preferences of users and create a basis for the formation of recommendations.
Such a synergy of data allows to capture hidden patterns and use them to increase the effectiveness of communications.
Analysis of the history of promotions is needed in order to compare the fact of purchase by the buyer of the goods and shares for this product. This helps to understand the sensitivity of a person to discounts and in the future to choose its optimal size.
We enrich transactional information with> 300 public sources. We take into account everything: from the availability of parking at the store and the weather to the color of the product packaging.