Sports assistant
Developed a product card feature that allows users to ask any question about a product or choose from a list of popular and relevant questions
Goals
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Simplify product selection β provide quick and clear answers instead of complex specifications
Build trust β show that the product truly matches the user's needs
Save time β gather all the necessary information directly on the product page
Boost sales β increase purchase confidence and suggest complementary products
Pain points
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Business objectives
- High support load β numerous repetitive questions about product usage and compatibility
- Lack of differentiation β competitor product cards look the same
- Underutilized content β expert guides and blogs exist but are not linked to product pages
- Missed upselling opportunities β no smart recommendations for complementary products
Customer pain points
- Hard to choose β specifications are complex, users don't know what matters for their case
- Low trust β descriptions feel like marketing, reviews are subjective
- Information overload β searching across multiple sources takes too much time
- No personalization β users want advice tailored to their goals ("I run on pavement in winter...")
- Purchase hesitation β unanswered practical questions stop people from buying
Workflow
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- Research
- Analyzed user behavior on the product page (time on page, exit points, add-to-cart frequency)
- Created a detailed user journey: from landing on the product page to interacting with the assistant
- Conducted market and competitor research: studied how competitors use product recommendations and AI assistants, identified best practices and gaps
2.Prototyping and testing
- Developed 3 interactive prototypes of the Sports Assistant with different launch scenarios
- Conducted usability tests to evaluate ease of use, scenario comprehension, and suggestion relevance
- Collected feedback to improve the UX
3.Design
- Refined user interaction scenarios (suggested questions, free input, recommendations)
- Prepared 3 widget interface options and placement variants within the product card (applied the brand color used for all AI-related blocks + added sparkles to maintain consistent AI logic throughout the app)
- Lengthy design approval process with the stakeholder: they had their own vision for the widget, and some elements conflicted with our design system, requiring compromises (settled on the 3rd option)
4.Results analysis
- Conducted A/B testing: product card with the widget versus the standard card
- Collected and analyzed metrics: conversion, engagement, CTR on suggestions, purchase frequency after interaction
Workflow
π
- Research
- Analyzed user behavior on the product page (time on page, exit points, add-to-cart frequency)
- Created a detailed user journey: from landing on the product page to interacting with the assistant
- Conducted market and competitor research: studied how competitors use product recommendations and AI assistants, identified best practices and gaps
2.Prototyping and testing
- Developed 3 interactive prototypes of the Sports Assistant with different launch scenarios
- Conducted usability tests to evaluate ease of use, scenario comprehension, and suggestion relevance
- Collected feedback to improve the UX
3.Design
- Refined user interaction scenarios (suggested questions, free input, recommendations)
- Prepared 3 widget interface options and placement variants within the product card (applied the brand color used for all AI-related blocks + added sparkles to maintain consistent AI logic throughout the app)
- Lengthy design approval process with the stakeholder: they had their own vision for the widget, and some elements conflicted with our design system, requiring compromises (settled on the 3rd option)
4.Results analysis
- Conducted A/B testing: product card with the widget versus the standard card
- Collected and analyzed metrics: conversion, engagement, CTR on suggestions, purchase frequency after interaction
Results
π
After the feature launch to production
- The Sports Assistant implementation led to a 1.3% increase in conversion
- Average order value grew by 8% thanks to personalized recommendations and upselling features
- User engagement increased by 10%, with strong interest in interactive content and assistant suggestions
- Automating answers to common questions reduced support inquiries by 15%
Results
The development of the Sports Assistant widget improved the product page experience by providing personalized recommendations and instant answers. As a result, we saw increased conversion, higher average order value, greater user engagement, and reduced support load. This feature not only strengthened user trust but also created a clear competitive advantage for the business
Conversion
+1,3%
AOV
+8%
Support load
-15%
