Filters

Filters play a critical role in helping buyers narrow search results to items that match their preferences. Beginning in 2024, my squad spearheaded this previously underinvested part of the buyer journey and established a foundation for refinement on Etsy.

My role

Led the cross-platform filter strategy for the Search team from a design perspective, translating vision into actionable, incremental improvements.

Impact

Created an end-to-end filter vision, modernized Etsy Search’s filtering experience, brought filtering components up to Etsy design standards, and improved key metrics including CR, PcCR, and filter engagement.

Buyer problems

Filtering on Etsy was inconsistent, poorly organized, often irrelevant, and overly manual.

Outcome statement

As a buyer on Etsy, I can narrow my results effortlessly so that I can browse listings that meet my specific preferences.

The right filters at the right time

Buyers expect relevant refinement. By leveraging ML models to predict what a buyer needs next, we surfaced the most helpful attributes as buyers move up, down, or laterally in their journey. Positioning these suggestions prominently provided fast, intuitive access to narrowing tools.

Refinement pills

Research showed that buyers often rely on listing titles to find the right wording when reformulating queries. Partnering with ML teams, we developed refinement pills—suggested terms buyers can prepend to their queries to get more specific. When launched they increased GMS by +1.08% and AOV by +0.93%.

Better access to filters

Research and analytics both pointed to the same need: filters should be accessible, relevant, and logically organized. Integrating the filter panel into the search grid allowed buyers to immediately see the impact of their selections.

Toggle filter panel

We ran six experiments to launch the filter panel. The panel remains collapsed by default and expands to reveal all available filters.

When buyers used filters, we observed a +1.86% lift in CR and +1.35% lift in PcCR.

This rollout represented months of technical, usability, and UI improvements.

Intuitive design

The filter vision focused on visual and UX consistency while respecting platform-native patterns. We extended the design system where necessary, giving key filters more visual prominence and clearer interaction guidance.

Price slider

We introduced a price slider with the option to input custom price values. This feature increased engagement by +12.21%, and conversion by +2.5%.

Color filter

Adding color swatches increased engagement by +2.0% and showed directionally positive CR and PcCR results. The two-toned swatch design set appropriate expectations given the realities of ML-powered color classification in a marketplace with diverse and unstructured inventory data.

Mobile filter panel

This redesign modernized the iOS filter panel and aligned its components with updated design standards. Filters were reordered based on insights from research and data. While conversion remained neutral, search effort decreased by –0.56%.

Highlights & learnings

Change takes time: Success is the accumulation of many thoughtful, incremental improvements.

Vision requires deliberate planning: Iteration roadmaps help teams tackle complex, multi-layered problems.

Data and design must work together: Solving buyer problems improves data quality, which drives better decisions over time.

← Eli Lilly

→ Etsy Listing Cards

Contact

Email: claire.casaregola@gmail.com
LinkedIn: @clairecas