REWIND TO SHELF2025

// CH 01 · E-commerce · Research & UX strategy

Research-led PLP redesign that drove +126% filter engagement

How behavioral research and competitive benchmarking turned a frustrating product-listing experience into a strategic conversion lever for one of Brazil's largest telecoms.

CLIENT
Claro
YEAR
Nov 27, 2025
ROLE
Senior Product Designer (research & UX strategy lead)
SERVICE
End-to-end Product Design
Research-led PLP redesign that drove +126% filter engagement

// TL;DR

  • 01Goal — make filtering and sorting fast and intuitive to improve discovery and conversion.
  • 02What I did — led benchmark research, Hotjar behavioral analysis, and UX strategy for a new filters & sorting model.
  • 03Outcome — +126% YoY filter engagement (131k → 298k); redesigned PLP now in A/B testing.
METRICS · A-SIDE
  • +126% YoY filter engagement (131k → 298k)

  • Redesigned PLP now in A/B testing for conversion & revenue

  • C-level investment secured for PLP as a conversion surface

// SCENE 01

Context & business goal

Claro's e-commerce platform offers a wide range of devices and accessories. The Product Listing Page (PLP) is critical for product discovery, campaign visibility, conversion, and reducing support tickets. The business needed a filters & sorting experience that supported fast, confident decision-making and could scale across categories and devices.

// SCENE 02

The challenge

  • Users couldn't quickly narrow down options.
  • It was unclear which filters were available.
  • Sorting wasn't meaningful or goal-driven.
  • Mobile filtering was inefficient — driving drop-offs and low confidence in the catalog.

// SCENE 03

Discovery & research

  • Competitive & cross-industry benchmark across 15+ platforms (Magalu, Casas Bahia, Mercado Livre, TIM, Vivo, Walmart, AT&T, Vodafone, Kimovil…).
  • Hotjar behavioral analysis — click maps, scroll maps, session recordings of real filter/sort interactions.
  • Mapped misleading affordances, filter-vs-sort confusion, hidden advanced filters, and weak applied-filter feedback.

// SCENE 04

Experience principles

  • Speed over density — fast narrowing beats showing everything.
  • Intent-driven filters — organized around how users decide, not internal taxonomy.
  • Mobile-first — effortless, easily reversible.
  • Clear system feedback — always show what's applied and how to reset.
  • Integrated commercial visibility — promos baked into exploration, not layered on top.

// SCENE 05

Results & impact

  • +126% YoY filter engagement (131,392 → 297,978 interactions, Nov 2024 → Nov 2025).
  • Higher discoverability and stronger reliance on filters for decision-making.
  • Redesigned PLP now in A/B validation for conversion and revenue.

// B-SIDE · STILLS

Benchmarking artifacts from the PLP research
STILL · 01Benchmarking artifacts from the PLP research
New mobile filter experience
STILL · 02New mobile filter experience
NEXT TAPE · VHS · 02▶▶
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END OF SIDE A

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