Archive · Home & commercial service
Referral and review management web application
TradieReviews automates review collection for tradespeople, where 95% of customers check reviews before they call.
This is earlier work, kept here because people still find it. The role titles below describe each engagement at the time. Olively today is an AI product consultancy — if that is what you are after, start with the AI Reality Check or the readiness scorecard.
The problem
What the work was actually for.
Roughly 95% of customers check social media and online listings before contacting a service provider. For a tradesperson running short jobs back to back, chasing each of those customers for a review is a task that never gets done.
TradieReviews automates it. The product's job was to turn review collection from something a tradesperson knows they should do into something that happens without them.
I ran this one as both product manager and designer, in a team of three.
The outcome
What actually changed.
Referrals rose 36% and leads 16%. One user reached a 4.8 rating on Google My Business inside a month, from 162 reviews — for a trade business, that is the difference between being called and being scrolled past.
The decisions
Three calls that shaped it.
Route low ratings privately, publish high ones
Reviews under a threshold go to the tradesperson instead of the public platform, so they can fix the problem. Higher ratings get actively encouraged onto social. The system improves the reputation and the service at once.
Pull contacts from the spreadsheet people already use
Research showed tradespeople keep clients in Excel and Google Sheets and invite by copy-paste. The add-on reads the list directly, which removed the step that was killing adoption.
Referrals without a login
A user can refer up to ten friends by entering an email. Every forced sign-up between a person and the thing they want costs conversions, and here the thing they want takes ten seconds.
What was hard
Onboarding was losing people. Analytics showed drop-out in a single long form; splitting it helped, but the larger fix was moving logo upload to the end and letting people skip it, because it was failing on mobile.
Worth pointing at
A few decisions that held up.
Bad reviews never reach the public
Low ratings are routed to the tradesperson instead of published, so they can fix the problem. High ratings get actively encouraged onto social platforms. The system improves the reputation and the service at the same time.
Bulk invites from a spreadsheet
Research showed tradespeople keep contacts in Excel and Google Sheets and invite clients by copy-paste. The add-on pulls the list in and sends the requests, which removed the step that was killing adoption.
Referrals without an account
A user can refer up to ten friends by entering an email address, no login required. Every forced sign-up between a person and the thing they want costs conversions.
Onboarding split into steps
Analytics showed people dropping out of a single long form. Breaking it up helped; moving the logo upload to the end and letting people skip it helped more, because it was failing on mobile.
The work
What it looked like.
The work
The product had two audiences with opposite needs: tradespeople who want this to take no time at all, and their customers, who need a reason to bother leaving a review.
What I do now
Most AI projects are theatre. I help you build the ones that aren’t.
An AI Reality Check scores every idea on your roadmap and hands back three lists — what is real, what is theatre, and what is blocked. One week, fixed price.