Yotpo: Leading eCommerce retention marketing platform enhanced with AI

Yotpo, a leader in ecommerce tech, aims to redefine creative expression through innovative technology. Instead of building their own platform, Yotpo chose Qwak for its flexibility and alignment with their business needs.

About Yotpo

This is some text inside of a div block.

Yotpo is an eCommerce marketing platform that helps brands drive growth by creating engaging experiences to build lasting customer relationships. Yotpo's integrated solutions for reviews, visual User Generated Content (UGC), rewards, and referrals empower businesses to win over new audiences using their customers' voice.

Yotpo

Our data science teams deliver end-to-end AI model services. Building infrastructure, however, is not our business focus, making JFrog ML ideal for our needs.

Challenges

Intensive Engineering Support: Crafting recommendation engine models demanded significant engineering backup.

Infrastructure Scalability: The infrastructure needed to be robust enough to support billions of users concurrently.

Platform Requirements: Yotpo sought a real-time ML model serving platform that was reliable, user-friendly, scalable, and forward-looking.

Flexibility & Autonomy: It was pivotal that Yotpo remained unshackled by specific model structures. They also required a centralized mechanism to seamlessly train, deploy, and access models on a massive scale.

Operational Overhead: Building and maintaining such infrastructure demanded extensive expertise, time, and effort—areas not aligned with Yotpo's primary business objectives.

Implementation

Solutions

Seamless Integration: Integrating with Qwak was a straightforward affair. A simple wrap-around of the Python model and a few lines of code empowered Yotpo with a fully deployed system. Notably, Qwak's platform promises flexibility, facilitating quick implementation of novel features.

Visibility with Qwak Console: A fully integrated UI ensures Yotpo can comprehensively monitor all deployed models. Moreover, this console integrates seamlessly with Opsgenie, Yotpo's primary alerting system.

Scalable Model Deployment: Qwak's solution caters to both real-time and batch model deployment. The inclusion of canary deployment ensures Yotpo can effortlessly handle millions of real-time predictions.

Autonomous Feature Management with Qwak Feature Store: This feature offers a streamlined API for feature extraction and retrieval, granting the data science team autonomy. They can now tweak model inputs without backend modifications. Plus, sharing feature sets among various models and conducting large-scale model training become feasible.

Analytics & Insights through Model Monitoring: It becomes possible to review prediction data and craft intuitive dashboards overlaying real-time data. This provides invaluable model insights for Yotpo's business decision-makers.

Read more customer stories

“Our real-time inference went down to less than 50ms.“

Idan Benaun
Director of ML and Data Science

Enhancing customers' API protection by continuously monitoring ML models and using realtime streaming inference.

Elad Weiss
Data Science Team Lead

“We were able to deploy a complex recommendations solution within a remarkably short timeframe.“

Asi Messica
VP Data Science