
SeedLegals
AI that turns pitch decks into deals
Showing investors that AI extraction was working, then landing them in Deal Flow to talk to founders and send proposals in one place.

Most reviews started with a post-purchase email, leaving customers without an obvious way to return and review later. Research also showed that customers understood the value of reviews and wanted to contribute, but struggled to discover alternative ways to leave one. The opportunity: make reviewing easier to discover and accessible whenever customers are ready.
At a glance
The problem
Most reviews started from a post-purchase email. There was no easy way in on the site.
The idea
A My Reviews area in My Account, listing recent purchases ready to review.
The result
My Reviews became the second-largest source of review submissions.
01: The problem
Following our user-centred discovery, John Lewis formed a product team focused on customer content. I set out to understand why customers upload reviews, and what prompted them to today.
01
Email was the only way in
Most submissions began with the prompt sent after purchase. Nothing on the site invited a review.
02
The benefits weren't clear
Not every customer understood why reviews mattered, or what was in it for them.
03
People review to help others
Above all, customers wanted to alert other shoppers to a product's positives and negatives.
User story
“As a customer, I want to know why to share my experience and how I can contribute, however I bought, so I can help others make an informed decision.”
02: Approach
I followed the Double Diamond: first explore the problem widely, then narrow to the right one; then explore solutions widely, and narrow to the one worth shipping.
01 · Discover
Understand the problem
User interviews and journey analysis into why, and how, customers leave reviews.
02 · Define
Frame the right problem
Three key insights, a user story and a testable hypothesis.
03 · Develop
Explore and test solutions
Ideation workshops and a team vote, then an end-to-end prototype tested with five customers.
04 · Deliver
Ship what works
An MVP with our reviews provider, Jira acceptance criteria, a two-week A/B test, then rollout.
03: Ideate
I ran ideation sessions with the wider team and key stakeholders. Everyone came with at least four ideas, discussed them without judgement, then voted.
How might we
…inform and encourage customers to share their John Lewis experience?
04: Hypothesis
Due to
Customers struggling to discover other ways to leave a review
We believe
A My Reviews section in My Account
Will result in
More customers discovering, and leaving, reviews
We'll know we're successful when
We see engagement with My Reviews and more reviews left from My Account
Success metrics
01
Engagement
Visits to My Reviews and taps on Write a review
02
Reviews from My Account
Share of all submissions from My Account
03
Moderation pass rate
Reviews approved first time
04
More reviews submitted
Customers reviewed more than one product
05: Validate
I built an end-to-end prototype for desktop and mobile, based on an agreed product type and a coherent journey, then put it in front of customers.
5
Customers tested
2
Devices, desktop & mobile
1:1
Remote, moderated

06: Deliver
01
Scoped the MVP
Agreed the first release with our third-party reviews provider.
02
Timed the prompt
Used the average number of products per customer to set the best moment to ask.
03
Made it buildable
Jira tickets with acceptance criteria for every scenario, annotated wireframes, and support through build.
07: The result
Recent purchases ready to review in one place, a clear reason to share, and answers to common questions alongside.

08: Outcome
The MVP ran as an A/B test for two weeks before rolling out to every customer.
#2
Source of reviews
Second only to the post-purchase email
^
More reviews approved
A higher share passed moderation
^
Higher ratings
On products reviewed via My Reviews
^
More reviews submitted
Customers reviewed more than one product
09: Reflections
Next

SeedLegals
Showing investors that AI extraction was working, then landing them in Deal Flow to talk to founders and send proposals in one place.

ASOS
A research-led discovery into how customers choose a size online, where confidence breaks down, and where ASOS could help.