Introducing AI-powered personalization
to Canadian Tire's Weekly Deals

Web & Mobile · 2025

My Role

Led end-to-end product design for the Weekly Deals experience across web and mobile, collaborating closely with PMs, engineers, researchers, and business stakeholders to improve personalized product discovery.

What is Canadian Tire & Weekly deals?

Canadian Tire is one of Canada’s largest retailers, offering a wide range of automotive, home, and sporting goods products

Canadian Tire's Weekly Deals page drives 57% of daily clicks and is a primary revenue source — but 48% of users couldn't find what they were looking for.

Our project introduced an AI deals assistant to improve the sale items search experience and help users discover relevant deals faster. This was crucial because the Weekly Deals page, which features over 2,000 items updated weekly and drives about 57% of daily clicks, is a key revenue source for Canadian Tire.

Results

Total Revenue

+6M

Product Detail Page Views

Total Revenue

+30.4%

+12.3%

AOV

User Engagement

+22.3%

Add-to-Cart

+13.1%

The Problem

48% users having hard time finding products they are looking for due to a broad categories

Discovery

Most users came with a specific product in mind but the page was built for browsers

Insight 1

48% users use categories to find a specific product they are looking for

The current categories offer only 5 different menu and the rest of the categories are not easy to navigate since it's located in the filter.

Insight 2

80% users consider 30% off+ as a good deal

To be able to apply 30% off filter was hidden under the filter.

The Target Group

Specific sale shopper

Our research revealed that 61% of users visited Weekly Deals with a specific purchase intent rather than exploratory browsing behavior.

61% of users were actively searching for particular sale items, while only 39% browsed more generally.

61%

Specific sale shoppers

39%

General sale shoppers

The Goal

Help specific sale shoppers find the right deal faster without forcing them to browse everything

Understanding the Business Goal

Transforming the traditional search UX to AI Search

The long-term vision was to create an AI-assisted discovery experience that could help users:
1. Find products faster
2.Discover more relevant deals
3.Compare options more efficiently
4.Reduce navigation friction across large inventories

Discovering items faster

Better product categories

compare options more efficiently

AI deal assistant

Design Direction

Introducing an AI deals assistant to help users find specific sale items faster and discover relevant ones

MVP Prioritization

Due to limited resources, we scoped MVP to lightweight personalization patterns

• Highlight 30%+ deals within personalized recommendations
• Replace static categories with behavior-based entry points

The MVP Goal

Introduce personalization to the page to help users to discover weekly deals items easier

Solution Exploration

Solution 1 : Highlight 30%+off products within personalized recommendations

Hypothesis
Highlighting highest (From 30%+) discount products will increase engagement & sales

Hypothesis
Highlighting highest (From 30%+) discount products will increase engagement & sales

Users Insight
80% users consider +30% off deal is a good deal

Users Insight
80% users consider +30% off deal is a good deal

Solution 2 : Replace static categories with personalized discovery entry points

Hypothesis
Dynamic categories based on shopping and browsing behavior would help users discover relevant products faster and reduce navigation friction.

Hypothesis
Dynamic categories based on shopping and browsing behavior would help users discover relevant products faster and reduce navigation friction.

Users Insight
48% users have difficulty navigating to find the products and 61% users shop based on their specific needs.

Users Insight
48% users have difficulty navigating to find the products and 61% users shop based on their specific needs.

Final Solution & Design

Introduced a curated carousel of 30%+ off items, with categories personalized to each user’s behavior

Next Steps

Allocating more resources to build it out in the next year
Following positive MVP performance, the business team planned future investment into more advanced AI-driven recommendation capabilities.

Prioritizing future enhancements through Kano analysis
To guide incremental updates to the AI feature, the research team is running a Kano survey to prioritize features.

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Introducing AI-powered personalization to Canadian Tire's Weekly Deals