Customer journey

To meet these challenges, companies can no longer be content to build massive, one-off marketing campaigns, even when they are based on segmentation. The solution is to use data science to design typical customer paths that will trigger marketing actions. For example, data science has shown, without any preconceived ideas, that after the first purchase on the merchant's website, a purchase in the store at the same time will strongly increase the customer's value in the long term. In addition to data science, the common sense of the marketer remains important. For example, a customer who has expressed dissatisfaction during an interaction is obviously at risk of switching to the competition. Other customer journeys will be triggered by life events (birthday, birth, move). In practice, the idea is to design a few dozen customer paths in this way.

For each customer journey, we write a scenario that makes the customer evolve in a communication universe corresponding to his expectations in terms of offers, communication channels, frequency of contact, or moments of life. These scenarios will also meet the company's objectives. For example, when a customer has made a first online purchase, he will be sent an e-mail inviting him to visit the store nearest to his home. These scenarios will trigger personalized interactions over different channels - phone, email, or web. For example, the scenario will be able to adapt the content of the merchant site when the customer visits it. Potentially, a customer will be able to enter one or more of these paths at any time. These scenarios are then implemented in the marketing platform, which will trigger them whenever it detects a customer or prospect entering one of the paths.