AI-Powered Semantic Search for a PlayTech E-commerce Platform
Our customer is an Indian-based PlayTech e-commerce startup that aims to change the way in which parents, educators, and gift-givers learn about the appropriate toys. The platform is based on both B2C and B2B models as it provides users with the opportunity to buy toys, while allowing the sellers to put their items on sale and sell them within the same ecosystem. The client was highly concerned with learning, skill development, and inclusive play and tried to use AI-driven technology to ensure that the process of toy discovery in their mobile application became more intuitive, personalized, and efficient.
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Industry
Retail -
Country
India
Technologies
Python
Hugging Face
React Native
FastAPI
AWS
Years in Business
Projects Delivered
Enterprise Clients
Countries Served
Business Goals
The client wanted to enhance the experience of shopping as a whole by eliminating the friction in product discovery and making toy search more intelligent and relevant to users. They wanted to
- Imply AI-powered semantic search over fundamental keyword-based searches.
- Enhance toy search according to age, talents, interests, and special needs.
- Enhance the conversions by ensuring that a user finds the appropriate products within a shorter duration.
- Smoothly add superior AI functionalities to the current mobile application without interfering with the operations.
Business Challenges
Limited Search Accuracy
The client was interested in improving its search engine to facilitate the discovery of toys and make it simpler and easier to use. They, however, struggled to go beyond basic keyword-based search because it was not very good at interpreting user intent, detailed queries, and conversational search queries.
Poor Product Discovery Experience
They had a huge toy collection, and it was hard to navigate. The difficulty of filtering options caused many users to get confused and spend more time on searches, and abandon the search without results.
Lack of Personalization
It was not possible to get recommendations according to the age, interests, and learning needs of a child on the platform. Consequently, users were presented with generic results rather than suggestions that actually addressed their needs.
Integration Challenges with Existing Systems
This new enhancement needed to integrate well with the current Shopify system and mobile application. The issue was to introduce superior features without compromising functionality, accuracy of data, and the user experience.
Technical Solution
We focused on fixing what truly mattered. We made search easier, recommendations more relevant, and the overall experience smooth across the app. Our solution was built to feel simple for users while staying efficient and reliable behind the scenes.
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Smarter Search Experience
The emphasis was put on ensuring that the search was natural and easy. Rather than making users use precise keywords, we enhanced the search to be able to read intent and deal with the detailed conversational searches just as people are natural searchers.
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More Relevant Toy Suggestions
We created a recommendation layer that assists users in finding toys according to their actual needs, including age, interests, and learning objectives. This was less time wastage since you could easily browse through options that had no relevance to you.
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Seamless Product Data Sync
We have linked the solution with the Shopify backend to ensure that the information about the products is always accurate. This made prices, availability, and product updates never be out of sync, and all without manual effort.
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Smooth Mobile App Integration
The whole solution was made to blend into the existing mobile application. We created lightweight, scalable APIs and included them in the React Native application without compromising performance and user experience.
Project Glimpse
Key Features
AI-based semantic search
Long prompt and intent-based search support
Personalized toy recommendations
Real-time product data synchronization
Mobile app integration
Scalable cloud architecture
Secure API framework
Results
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01.
More Accurate Search Results
Users were no longer required to make guesses on the appropriate keywords. Even more specific or lengthy search options began to present the relevant toy options, and it became easier to get the toy that they wanted.
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02.
Quicker Toy Discovery
With smarter suggestions in place, users spent less time browsing and more time discovering toys that matched their needs. The path from search to selection became much shorter.
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03.
Noticeable Increase in Conversions
When users found the right toys faster, they were more confident in making a purchase. This directly reflected in higher engagement and improved conversion rates.
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04.
Smoother App Experience
The overall flow of searching and exploring toys felt simple and effortless. Users enjoyed a more engaging and frustration-free shopping experience on the mobile app.
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05.
Lower Manual Effort for the Team
With automated search logic and real-time product updates, the internal team spent less time managing data and more time focusing on growth.
Let’s get in touch!
India
SPEC House, Parth Complex, Near Swastik Cross Roads, Navarangpura, Ahmedabad 380009, INDIA.
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+91-79-26404031, 32-33-34 -
[email protected]
