To improve the relevance of the offers, and provide better insights to the clients, we needed to improve the attribution matching.
Rokt is a technology company specializing in e-commerce marketing, providing personalized transaction moments to enhance customer engagement and revenue. As of 2023, Rokt has over 500 million users and is valued at approximately $2.4 billion. Rokt has partnership with notable companies as Uber, Ticketmaster, Fanatics and Live Nation.
I am working at Rokt as Senior Data Engineer for the last five years. My work consist in developing services in a high-performance, high-availability, and scalable platform that processes billions of transactions per month, to deliver personalized and relevant offers to millions of users worldwide.
Properly attributing the campaign events to the desired outcome is a complex task that requires comparing a high-number of events, applying different attribution rules per campaign ensuring consistency and explainability. Properly measuring how successful a campaign is, is crucial to clients to understand the return on investment. It is also important to guide the machine learning models to better predict and optimize the campaigns.
The new attribution system generates the matching events in a fraction of the time, and with a fraction of the resources. It also provides new features to the clients, such as better explainability, monitoring new events during the customer journey, consume new nurturing events, and the ability to change the attribution rules on the fly. Using the new events, the machine learning models were able to faster learn and optimize the campaigns, improving the return on investment.