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I led a 4-month discovery with IKEA's listing team to define a data-driven, adaptive PLP — surfacing the right content at the right moment for every purchase type, across 10 markets.
Two senior product designers (myself as lead), one UX researcher, one content strategist, two front-end engineers, and embedded stakeholders from category management and merchandising. Discovery ran across 14 weeks with a global remit covering 10 markets.
Whether a customer was browsing a sofa, a kitchen system, or a pack of tealights, the PLP served the same density, the same imagery, and the same supporting content. As IKEA's range expanded across categories with very different decision journeys, this one-size-fits-all template started showing real cracks in performance and customer satisfaction.
Customers shopping a planned purchase like a kitchen needed deep guidance, comparison and supporting services. Customers replenishing a low-consideration buy like storage boxes needed speed and density. The same PLP was failing both, hurting findability for inspiration-led shoppers and slowing down task-led ones.
Before running new studies, we audited 30+ existing research artefacts across the customer experience, search and discovery, and category teams. The picture was consistent: customers expected the PLP to behave differently depending on what they were shopping for, and they were quietly compensating for it with workarounds, third-party tools, and store visits.
Inspirational — the customer is browsing, gathering ideas, often early in a room project. Considered — the customer is comparing options for a known need, weighing services and add-ons. Replenishment — the customer knows exactly what they want and is here to find it fast. Each mode pulls a different set of components into focus.
Across the 10 markets in scope we saw a 22% drop-off after the first viewport on high-consideration categories, an average of 3.4 filter interactions before exit on inspirational journeys, and a long tail of replenishment customers using site search to bypass the PLP entirely. Customer satisfaction scores trailed the rest of the funnel by 11 points.
Designers, researchers, content strategists, category leads, range managers and engineers worked through the data together. We aligned on the three purchase types, agreed on the components in scope, and committed to a single shared model for what an adaptive PLP could look like — before any pixels were drawn.
Across the benchmark we scored each PLP on 42 criteria covering content density, comparison support, inspirational content, services exposure, and replenishment shortcuts. The pattern was clear: best-in-class retailers were already running multiple PLP behaviours behind a shared visual system, while IKEA was running one behaviour across very different categories.
Across an unmoderated open card sort and a closed validation sort we tested 36 PLP content blocks against the three purchase types. Customers grouped components into recognisable bundles — inspiration first, then comparison, then services — and crucially they wanted those bundles to behave differently depending on what they were shopping for.
Wayfair, Argos, John Lewis, Marks & Spencer, Zara Home, Made.com, Crate & Barrel, and West Elm — we mapped how each one let the PLP shape-shift across categories. The strongest patterns combined a stable visual system with category-specific content modules and contextual entry points into services or planning tools.
We left the organisation with a single content framework, three reference templates, a tagged catalogue ready to pilot, a prioritised module backlog, and a governance proposal. The next phase moved into prototyping and live testing on two pilot categories, with the goal of proving the adaptive model before rolling it across the full range.