Liking and similarity
We are more persuaded by people who are like us.
Two of the eight page areas.
Five ways to use it, and two to avoid.
- Show reviewer attributes on reviews, such as size, skin type, use case and location.
- Let shoppers filter reviews by those attributes.
- Use relatable customer imagery.
- Tell the founder story.
- Leave reviews anonymous where you cannot match reviewers to the shopper.
- Avoid: showing reviewers who are visibly unlike the shopper, which can reduce persuasion.
- Avoid: displaying reviewer attributes customers have not knowingly agreed to share, as they are personal data.
Similarity strongly predicts liking. On Amazon, identified reviewers were linked to higher sales.
Shoppers assume anonymous reviewers share their tastes.
A meta-analysis of 313 studies found similarity strongly predicted liking (r = .47 actual, .39 perceived), though in existing relationships only perceived similarity mattered. Shoppers assume anonymous reviewers share their tastes and are less persuaded by clearly dissimilar ones. On Amazon, reviews disclosing reviewer identity were linked to higher sales, more so when reviewer and shopper shared a location.
Five sources, each checked.
Last reviewed
Showing reviewers who are unlike the shopper can reduce persuasion. Reviewer attributes are personal data, so collect and display only what customers have knowingly agreed to share.
This is simply a pointer to check, not legal advice. Seek legal advice before you put this principle into action.