+£3.2 million Revenue for Sharps by Adding Local Social Proof

During initial user research, participants asked questions about what the design visit would involve and whether there would be a suitable design expert in their local area. While the website already displayed customer feedback and industry credentials, there was an opportunity to address these more specific doubts by surfacing evidence that other customers in the same location had enjoyed a successful design visit.

We developed a test concept based on behavioural science and the principle of Social Proof. Research shows that when people feel uncertain, they look to the behaviour of others for reassurance. This tendency is most pronounced when an individual strongly identifies with the group they are imitating.

Our hypothesis was that showing users evidence that people like them, in their local area, already trust Sharps would reduce anxiety and increase form completion.

We designed and ran an A/B test on the design visit booking form, using the visitor’s postcode to identify relevant statistics on the number of design visits booked in their local area. We tested two versions of the Social Proof notification against the control to see whether different descriptions of the local area would increase its impact.

• Variant 1 (Town/City): Displayed a message highlighting the number of design visits completed in the user’s specific town or city.
• Variant 2 (Your area): Displayed a broader but more robust message confirming Sharps had completed over 100, 500, or 1000 design visits for customers in the user’s local area.

Both variants were dynamically served based on location data and only shown when minimum thresholds were met. The test ran for 14 days across all users and devices.

Key results included:

• A statistically significant increase in design visit requests occurred when local social proof was shown.
• Positive performance across all devices, with particularly strong uplifts on desktop.
• The uplift translated into a projected £3.2m annualised increase in revenue.

As a result, we recommended rolling out Variant 2 to all users and hardcoding the solution. We also identified further opportunities to refine messaging and placement through future experimentation.