The Fifth Elephant 2024 Annual Conference (12th &13th July)

Freshmarketer empowers D2C store owners with data-driven marketing solutions tailored to their unique needs. Our approach integrates product recommendation systems into marketing campaigns, addressing various marketing objectives.
Unlike one-size-fits-all solutions, Freshmarketer develops decision engines customized to individual stores, ensuring flexibility across different categories and campaign types. Leveraging machine learning, we enable hyper-personalized recommendations for each customer, handling large prediction volumes efficiently.
Our architecture combines offline and online prediction systems, providing real-time contextual insights. We serve six key recommendation use cases, including similar item suggestions, cross-sells, upsells, user personalized recommendations, popular and trending product suggestions, and event-based suggestions. In this presentation, we discuss our overarching ML system, distributed training for scalability, hybrid offline and online frameworks, and continuous model evaluation.
Attendees will learn how to build scalable ML systems, adopt hybrid frameworks, and track model performance effectively, all at a fraction of the cost of existing solutions like Amazon Personalize

Speaker-1: Shubham (@shubham27)
Speaker-2: Abhishek (@1abhishekpal)

Update:
Who is the audience for this talk?
Marketers and Technical folks working for serving multiple D2c Customers on scale

What is the problem you are trying to solve ?
The solution will help marketers create more focussed and hyper-personalized campaign using Product recommendation block in campaign templates

What is the scope of this talk i.e., what content will you cover in this talk?
we will dive into the system explaining both about the recommendation engine and the serving architecture of the system. we will also also explain various usecases for d2c customers and planning better marketing campaigns.

How will participants benefit from your talk?
Attendees will gain valuable insights into both the practical application of AI in marketing and the technical nuances of system design.