Accelerating Basket Building
Using personalisation to reduce friction and drive first order completion
+9pp
increase in first order conversion
+11pp
more users reached minimum spend
-23%
reduction in time to build a basket
Context
First-time shoppers are highly motivated but many fail to complete their first order.
The biggest drop-off happens after users start building their basket.
Problem
Building a complete basket is slow and effortful.
Users can quickly find and add their first items, but struggle to continue:
Progress slows as decisions accumulate
Too many options increase cognitive load
Many users abandon before reaching minimum spend
The challenge is not helping users start shopping, but helping them finish their basket efficiently.
Role & Collaboration
Led the end-to-end design of the basket-building acceleration system, working across product, data, and domain teams to align on a scalable personalisation approach.
My role
Refined the problem framing: shifted focus from “personalisation” to basket-building friction
Translated research and data into a clear product strategy
Designed the core experience (onboarding, filters, nudges, discovery)
Prioritised interventions based on impact on conversion
Partnered closely with PM and data to define experiments and success metrics
Cross-functional alignment
Personalisation touched multiple parts of the platform (search, browse, merchandising, recipes, promotions), each owned by different teams.
To align these, I facilitated a cross-functional workshop with:
Product managers (Search, Browse, Offers, Shopping tools)
Merchandising and tagging teams
Data and engineering leads
Workshop outcomes
Defined where personalisation should happen first (homepage and search)
Aligned on filters and tags as the core system enabler
Identified dependencies and constraints (e.g. inconsistent tagging, cookies)
Prioritised high-impact use cases across domains
Established a shared roadmap for rollout
This alignment was critical to move from isolated features to a coherent system across the journey.
Objective
Increase first-time shopper conversion by reducing the effort required to build a complete basket.
Discovery
Approach
We designed a basket-building acceleration system that intervenes at the moments where users struggle.
Principles:
Act early → First 1–3 minutes are critical
Reduce choice → Narrow options to relevant products
Guide continuation → Help users move from “1 item” to “complete basket”
Balance control → Allow users to override personalisation
Key product decisions
Focus on early and mid-journey
Use filters as primary intent signal
Trigger interventions behaviourally
Keep onboarding lightweight
What actually drove impact
The onboarding quiz enabled the system.
Contextual nudges and pre-applied filters drove conversion.
Estimated contribution:
Contextual nudges: 40–50%
Pre-applied filters: 25–30%
Personalised ranking: 15–20%
Onboarding quiz: 5–10%
Impact
Funnel performance
Metric
Before
After
Impact
First order conversion
Reach min spend
Time to min spend
Supporting signals
+30% continuation after first add
+20% faster discovery
-15% early drop-off
+12% basket value
+9% repeat rate
Why it worked
1. Solved the real bottleneck
Focused on basket-building, not discovery
2. Reduced cognitive load
Filters and ranking simplified decisions
3. Intervened at the right moment
Nudges targeted behavioural drop-offs
4. Balanced automation and control
Users could override preferences, building trust