1 / 3Diagnosis
First, an honest look at where the listing stands. Tick the symptoms you recognise — then we cover why the usual fixes fail.
Tick what sounds familiar0 of 7 — room to grow
Common approaches that fail
Only a handful do it; the rating shifts over months
They remove a review only if it breaks the rules
Templated text; moderation cuts it en masse
A disproportionate wave is obvious to both the algorithm and the buyer
Doesn't look natural, conversion doesn't recover
You lose all the history and positions
2 / 3Method
What we do about it step by step, what the scope covers, and which services the solution is assembled from.
A 5-step process
- Negative diagnostics
We count the bad reviews by type (defect / expectations / service / attack).
- Mitigation plan
How many positive reviews, and in which formats, are needed to bring the average rating back.
- Building the review mass
Aged buyer accounts, varied pickup points (PUPs), realistic text, photos and video in a natural setting.
- Working on conversion in parallel
We boost click-through, add-to-cart actions, and trust signals.
- Control and lock-in
We monitor throughput, average rating, and conversion until you're out of the red zone.
Scope of work
- Text reviews tuned to use cases
- Photo reviews with natural presentation
- Video with unboxing and product use
- Aged buyer accounts
- Natural distribution across time and pickup points (PUPs)
- Moderation throughput monitoring
- Transparent rating reporting
How we assemble it
3 / 3Terms
What it costs, what it has already done for others, and how the work starts.
From free audit to full package
Get a «Negative mitigation» plan in 24 hours
We'll size the buyouts and reviews, forecast the effect.