Personalized Shopping Page

This case study explores the design and development of a Personalized Product Listing Page (PLP) tailored to enhance user shopping experiences. The PLP leverages user preferences and behavior to curate a selection of products that align with individual tastes, adapting in real-time for a dynamic, ever-relevant experience.

 

UX Goals

Enhance Product Discoverability
Make it easier for users to find relevant products quickly by tailoring product listings based on browsing history, preferences, and behavior.

Increase Engagement & Time on Page
Encourage deeper exploration by showcasing relevant product collections, trending items, or restocks based on the user’s past interactions.

Recommendations enhance the user experience by combining implicit and explicit feedback.

• Explicit behaviors, like past purchases and items saved to a wishlist, directly shape recommendations, aligning with specific styles or brands.

• Implicit behaviors, such as browsing patterns and engagement with different categories, inform broader thematic suggestions, creating diverse yet targeted recommendations like "Inspired by Your List" or "New for You, Styles You’ve Never Seen." This blend of data-driven insights allows for a dynamic, highly tailored experience that evolves with the user’s tastes and seasonal needs, seen in sections like “Sunny Days in the Forecast.”

Entry points & discovery throughout the shopping journey on Aritzia.com

Our personalization strategy includes multiple entry points to guide customers toward tailored recommendations seamlessly throughout the site.

A “The Personal Edit” option in the main menu, marked with a “New” subscript, serves as a prominent access point.

On the homepage, users can explore “Picked Just for You” sections, with a “See All” link that deepens their engagement with curated products.

“Yeah, I would visit for sure now that I've seen it and noticed it there.”

-Emily R. User Research Study

When asked to navigate to the destination that houses their personalized recommendations on Aritzia.com, 3/6 navigated to the "personalized picks" L1 in the MM

User Research Study

Segmentation and Personalization Strategies

Our goal is to craft an intuitive, engaging, and seamless shopping experience that feels uniquely tailored to each user.

For new customers, we focus on discovery—leveraging localization and a strong brand POV to introduce them to Aritzia’s aesthetic and curated collections. This approach helps create a guided, inspiring first impression.

For existing customers, we prioritize relevance—surfacing personalized recommendations based on past purchases and browsing behavior. This ensures a seamless, efficient shopping experience that feels intuitive and tailored.

“Well, I like that it lets you sign in to your account because that way I feel like it kind of like track what you like over time and I feel like your picks become better.”

User Research Study

Leveraging the Existing User Experience

For existing customers, personalization is about creating a shopping experience that feels familiar, relevant, and effortless. By leveraging explicit user actions like past purchases, favorites, and browsing history, we surface smarter recommendations that anticipate their needs.

Key personalized touchpoints include:

  • "Because you bought X, you might like Y": Suggesting complementary products based on previous purchases.

  • "Inspired by your Favorites": Curating new arrivals that align with saved or favorited items.

  • "New for You": Highlighting newly launched products tailored to past behaviors.

  • "Add these to your [Collection]": Encouraging customers to build out personal collections or style edits they've already engaged with.

  • Weather-Based Recommendations: Offering seasonally and regionally appropriate suggestions to stay both stylish and practical.

“It feels more authentic that like you saw my purchase history as to why you're recommending certain things versus just like recommending things to make a sale”

Guiding the New User Experience

For new customers, the goal is to create a welcoming, curated experience that introduces them to Aritzia’s brand while encouraging exploration. Since we have limited behavioral data at this stage, the personalization strategy leans into high-impact, contextual cues to drive engagement and discovery.

Key personalized elements include:

  • Localized Recommendations: Showcasing products based on the user’s geographic location and climate to ensure seasonal relevance and regional appeal.

  • Log In Prompt for Better Recommendations: Gently encouraging users to create or sign into an account to unlock deeper personalization and save their preferences.

  • Shop the Feed: Integrating real-time, brand-driven content into the PLP to inspire and inform—allowing users to shop directly from editorial imagery, lookbooks, and style moments.

Measurement Plan

Goals:

-Improve product discovery and engagement.

-Increase relevance of PLP content across user segments.

-Drive conversion and retention through personalization.

KPIs:
-CTR on Personalized Recommendations

-Add-to-Cart Rate from Personalized PLP

-Log In Conversion Rate

-Repeat Visit Rate / Session Frequency

Tools & Data Sources

  • Analytics: GA4

  • Personalization Engine: Dynamic Yield

  • Behavioral Tools: Hotjar

  • Qualitative Feedback: Lookback qualitative user testing