Social Shopping

Fermat • Jan-Apr 2023 • Product Designer • UX Researcher

Project Overview

Fermat • Jan-Apr 2023 • Product Design • UX Researcher 
Overview

Fermat Commerce is an AdTech startup building embedded shopping experiences within social media content. At the start of this project, Fermat shops showed high conversion volatility, with performance varying widely depending on product type, influencer, and brand.

I conducted user research to optimize Fermat’s existing embedded shopping experience and designed concepts to expand the experience to better support a wide range of brands. The project spanned early-funnel touchpoints from influencer and content-driven shops to product grids and PDPs.

Outcomes

8.1% Average Conversion

Average shop conversion increased from 1.2% to 8.1% in the three months following the new shop launch.

Stabilized Shop Performance

Design changes reduced conversion volatility across brands, influencers, and categories.

Product Market Fit

Key learnings from the project highlighted market opportunities in funnel optimization prompting a shift from the previous focus of affiliate shopping.

New Feature Opportunities

The learnings from this project highlighted opportunities to expand Fermat’s offerings to embedded shopping experiences in video, blogs, and social profiles.

Skip to Final Designs

Context

USER CHALLENGE

Varied Levels of Intent

Fermat shops were embedded directly within social media content, linking users to storefronts styled to match an influencer or brand. Users arrived in very different frames of mind depending on the content they were engaging with.

This created friction because:

  1. Some users arrived with high purchase intent and wanted to buy quickly.

  2. Others wanted to browse, compare products, and build confidence before purchasing.

The original experience was successful in facilitating fast, high-intent purchases but did not support exploratory shopping well.

business CHALLENGE

Conversion Volatility

Conversion rates varied significantly across Fermat shops, with some performing as low as 0.3% CVR. This variability made it difficult for Fermat to scale consistently across clients and categories.

DESIGN CHALLENGE

How might Fermat’s social shopping experience evolve to deliver more consistent performance and unlock new brand use cases?

Research Process

I used qualitative research methods alongside user research to identify product gaps and design the vision for an end-to-end social shopping experience.

Qualitative Performance Trends

CATEGORICAL ANALYSIS

I analyzed categorical traits of best- and worst-performing Fermat shops and found that conversion success was heavily correlated with shop layout, influencer collaboration, product category.

KEY FINDINGS

Top Performers

  • Influencer-led shops converted more consistently, especially with smaller, curated assortments.

  • Consumables consistently performed well

  • Shops with fewer products consistently converted better

Worst Performers

  • Technical products underperformed without strong education and trust signals.

  • Apparel performed poorly unless it was paired with user-generated content.

Supporting Proven Brand Strategies

STAKEHOLDER INTERVIEWS

I conducted stakeholder interviews with business development partners and clients to understand gaps in the Fermat experience which differed from successful brand strategies.

KEY STRATEGIES

High Impact affiliates

Hero Bread was a top-performing Fermat shop that noted collaboration with a high-impact influencer was important to their conversion strategy.

Repeat Replenishment

Head Kandy’s brand strategy focused on targeting repeat customers who are loyal to a particular consumable product and using upsell to increase AOV.

Trust Signals

Nood, a hair removal device seller, noted the importance of highlighting FDA-approval and money-back guarantees. 

User Friction in the Browse Experience

USER TESTING

I analyzed user interactions across Fermat shops to understand end-consumer behavior and identify where the Fermat experience fell short in supporting browsing and purchase decisions.

TASK FLOW TESTING

Insufficient Information on PDP’s

Task flow analysis showed that users frequently left Fermat shops to visit brand websites to find missing details:

  • 72% sought fit or usage information

  • 48% checked for discount codes

  • 24% reviewed return policies

HEAT MAP ANALYSIS

Curation and Recommendation

Heat map analysis showed that users engaged most with products surfaced through recommendations and visual signals:

  • 60% selected products with promotional tags

  • 36% chose items recommended in influencer content

  • 48% clicked icons to explore additional recommended products

Addressing Product Gaps for Window Shoppers

Synthesizing qualitative performance data, brand interviews, heat map analysis, and task flow testing led me to identify two distinct shopper types within Fermat shops: quick-buy and window shoppers.

I found that while Fermat shops were well suited to fast, low-friction purchases, they did not adequately support window shoppers who needed to browse, compare, and build confidence before buying.

Quick-Buy

Window Shoppers

Shopping intent

Impulse-driven, high intent

Passive, exploratory

Typical categories

Consumables, replenishments, food, personal care

Fashion, beauty, home goods, technical products

Key drivers
Engagement patterns

Context, trust signals, recommendations

Speed, promotions

Browsing, comparing, exploring

Search, direct selection

Final Designs

dESIGN PRINCIPLES

Influencer Connection

Influencer content was successful as a point of inspiration and validation for products, particularly in embedded blog content, but was less successful as an overarching shop format.

Influencer video performed better as PDP imagery than as a standalone influencer shop experience.

Influencer content was most impactful earlier in the journey, during social media discovery rather than within the transactional flow.

For browse-oriented users, influencer recommendations enhanced product discovery and exploration.

Modularity

Modularity was critical in order to support a diverse range of brands.

  • Text-based product “chips” highlighting key benefits allowed PDPs to adapt across industries and brand needs.

  • Rich product detail including fit guides, technical specs, approval tags, and guarantee was essential for building purchase confidence and intent.

  • Strong brand expression reinforced trust, kept users on-site longer, and elevated the perceived legitimacy of the shopping experience.

ORIGINAL PDP
MODULAR PDP

Curation & Recommendation

Curation was essential to embedded shop success in order to reduce cognitive load. Users shopping from embedded social links favored guided, low-effort decision-making.

  • Browse-oriented users responded best to curated experiences rather than open-ended catalogs.

  • Quick-buy users converted 3× faster when products were surfaced through “Best Sellers” or “Previous Purchases.”

  • Branded video shops featuring tutorials increased conversion by 64% for complex or technical product categories (e.g., beauty, makeup).

Results

Based on the research and iterative design process, the redesigned embedded shop experience enabled Fermat to meet and exceed its conversion goals.

  • Average PDP conversion exceeded 7.4%, surpassing the industry benchmark of 6%

  • Results were sustained over the three months following launch

  • Improvements applied across both product detail pages and browse experiences

Key learnings from this work became the foundation for Fermat’s consumer-facing UX strategy.

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