ASP.NET AI Recommendation Engine for 'Media Adviser' in USA

Client Brief

Media Adviser is a USA-based platform that helps marketers and agencies plan, allocate, and optimize their media investments across various channels using data-driven insights. As the complexity of media planning grew, the client saw the need to modernize their system -selecting media channels and allocating budgets manually was time-consuming and inconsistent. They approached us to build a smart recommendation engine that could automatically generate a list of optimized media plan suggestions based on ranking files and user inputs, allowing their users to review and pick the best options for their final plan.

Our Endeavor

The client wanted to move away from a heavily manual planning process and give their users a smarter, faster way to build media plans - one where the system does the heavy lifting and the user stays in control of the final decision.

We designed and developed the algorithm-based recommendation engine that processes ranking data and user inputs to generate a ready-to-review list of optimized media plan suggestions. Users can evaluate the system's recommendations and select the ones that best fit their campaign goals, making the planning process significantly faster, more consistent, and better informed. The engine runs seamlessly in the background without interrupting the main platform experience. The main building block of recommendation engine is ranking file which holds the ranking of each publisher in different regions so based on that recommendation engine make the recommendations. Also, recommendation engines maintain the important aspects of keeping recommendation under budget and under 100% impression goal.

As a result, what once required considerable manual effort now takes a fraction of the time. Media Adviser's users can build stronger, data-backed campaign plans with greater confidence and the client's platform has become meaningfully more valuable to the marketers and agencies it serves.