Case Study: E-Commerce Aggregator
Outcome
Preference-driven recommendation engine · gamified feedback · D2C aggregation
An e-commerce app to deliver a personalized shopping experience through gamified engagement.
The Problem
With the advent of e-commerce and direct-to-consumer commerce, consumers are flushed with choices across pretty much every product category. Conventional recommendation engines are inventory-driven — pushing high-margin, high-stock products to consumers rather than what actually fits their preferences.
Our Solution
Parati designed a platform that captures insights around customer preferences, likes and dislikes, and product feedback through a rapid feedback-collection mechanism — specially designed to help businesses make customer-centric design and inventory decisions. This preference-driven recommendation engine helps brands gather relevant data around their products and consumers, while helping customers find relevant products based on their preferences.
Our Approach
Aggregation: create a one-stop shop with products listed from multiple D2C brands and marketplaces.
Personalization: a tailored shopping experience on the app based on each user's preferences.
Engagement: engage customers through a gamified experience and collect product-level feedback in the flow of shopping.
