Context: users of the web service must be segmented to personalize the service's offers. This can be done on the basis of cookies since the browsing history indicates the user's interests.
Decision: building a segmentation model using thematic modelling based on cookies in the form of a text description of visited pages.
The pilot project was conducted and integrated into the customer's business process:
- The subjects of 80% of the user's visited pages were identified;
- 70% are interpreted;
- Predicting socio-demographic parameters of the audience;
- The interests of 90% of users by the subjects of visited pages are highlighted;
- 80% of interests are interpreted;
- Увеличение конверсии рекламных кампаний на 10% во время тестирования A / B;
- Changes have been made to 15% of ready-made ad campaigns.
To build the model, we used:
- List of URLs that the user visited;
- Description of URL pages;
- Accompanying information about the user;
- Results of displaying ads to the user.
- A behaviour model for Internet resource users;
- Model for predicting the probability of response to an ad campaign;
- Interpretation of the client base.
Customer: Marketing agency
Technology stack: TopicNet, BigARTM, Python, gensim.