Right product, first time

Evolving search capability and results relevancy across 120k product portfolio

Overview

Time-poor customers and distributors were overwhelmed by large result sets in categories exceeding 30,000 products, with low engagement with attribute filters. Despite entering specific queries, users were presented with broad results, slowing decision-making.

For the business, an inefficient search constrained conversion and increased abandonment and avoidable product replacements under guarantee.

Role

• Defined problem using customer feedback and insight data:
  Time-poor users overwhelmed by broad, high-volume results

• Quantified behaviour: users engaged with ~20 results despite much larger result sets

• Defined “positive friction”: slightly more input upfront for quicker downstream decisions

• Set UX direction: evidence-led discovery with relevance over volume

• Led UX and UXR delivery with Product and Engineering to de-risk rollout and measure impact

Risks

• Introducing friction into revenue-critical search journeys

• Disrupting high-volume, habitual researcher behaviours

• Over-engineering filters that historically showed <4% adoption

• Delivering experience change during a broader platform and brand transformation

• Scaling globally across B2B2C and distributor contexts without fragmenting journeys

Priorities

• Customer to find the right product, first time, in a single session

• Reduce result volume while increasing relevance and confidence

• Introduce positive friction only where it demonstrably reduced downstream effort

• Maintain commercial performance while modernising search behaviour

• Anchor UX decisions to measurable revenue and satisfaction outcomes

Direction

Search was repositioned from a passive results engine to an active decision-support system.

The strategy focused on shifting effort earlier in the journey, helping researchers clarify intent before results were returned—rather than relying on complex post-search refinement that users consistently ignored.

Key leadership decisions included:

• Prioritising relevance over volume

• Treating product views as a primary proxy for revenue

• Using behavioural data to challenge long-held assumptions about filters

• Designing search as augmentation, not disruption, of existing habits

Outcomes

Search journeys evolved from broad, overwhelming result sets to focused, confidence-building exploration.

Researchers were exposed to essential product attributes earlier, enabling faster elimination of irrelevant options and deeper engagement with genuinely suitable products. Search sessions became more deliberate but shorter overall, with reduced backtracking and fewer unnecessary product page visits.

The experience supported both expert users with precise intent and broader searchers without risking revenue-critical pathways.

Impact

Customer

• Reduced cognitive load

• Faster product discovery

• Higher confidence in choices

Business

• Strong correlation between Product Description Page (PDP) engagement and revenue signals

• Lower operational cost through fewer avoidable returns

• Sustained conversion during significant UX and architectural change

Key metrics

• Search → PDP engagement: +30% (1.2 → 1.6 pages/session, ≈2.8M additional PDP sessions/year)

• Customer satisfaction: Up from 3.2 to 4.3 / 5

• Bounce rate: Stable despite added positive friction

• Filter usage: Remained <4% validating strategy to reduce dependency

• Zero-result searches: Improved by 7% through targeted keyword and matching workstreams

Learnings

• Relevance beats optionality, fewer results outperform broader choice

• Filters are not a planning tool for time-poor researchers

• Small, intentional friction upstream saves significant effort downstream

• In a blended on/offline model, product views are a stronger revenue signal than raw conversion alone

• Phased rollout is essential when evolving revenue-critical journeys