At first, Showroomprivé turned to an external predictive analytics tool to create the groups of users for each brand. However, the team realized that they had all the data and the skills to create Targetor themselves, so for several months, Showroomprivé tested versions of Targetor built in the out-of-the-box predictive solution, built with Dataiku, and built by hand (i.e., building data pipelines from scratch without a data science and machine learning platform — this was quickly scrapped as the results were not on par with the other two solutions).
In the end, though the initial results of the project using the out-of-the-box predictive solution and using Dataiku were similar, they ultimately understood that pivoting to Dataiku — one of the world’s leading AI and machine learning platforms — would allow for more granular control in the long run and could provide them with a data product that was a real differentiator for the business and in the market.
Following these initial tests, marketing started to work completely with Targetor and with Dataiku right away, thanks to the platform’s usability both on the data science side (with complete flexibility for coders) and on the business side (with webapps, a point-and-click interface, and other features for non-data practitioners). The marketing and data teams were even able to make improvements for a second iteration of Targetor that provided a ranking of users instead of just a homogenous group, allowing marketers to better prioritize their campaigns.