01 About SuperBottoms
SuperBottoms is one of India's fastest-growing baby and toddler product brands, known for its reusable cloth diapers, training pants, and infant care range. With a strong D2C presence and a growing Amazon India catalogue, SuperBottoms entered the review recovery programme at a critical growth stage, where rating credibility on Amazon had begun to impact discoverability and conversion.
The brand was experiencing a pattern seen by many growing D2C brands on Amazon India: strong product quality, but a review profile that didn't reflect it. A mix of early negative reviews, low verified review volume, and a slow natural review velocity was holding their star ratings below the threshold needed for category competitiveness.
02 The Challenge
- →Average rating across key SKUs sitting at 2.9★, well below the 4.0★ floor buyers trust
- →312 total reviews across the core range, with only 63% verified, a credibility concern
- →No structured process to generate review velocity post-purchase
- →Organic review rate of ~18 per month, insufficient to move ratings meaningfully
- →High competition in the baby care category, where 4.3★+ is table stakes for visibility
- →BSR (Best Seller Rank) declining in key sub-categories due to low rating signals
03 Brand Integer's Approach
Brand Integer was engaged to design and execute a structured, sustained Amazon seeding and review recovery programme. Our methodology operates within Amazon's guidelines, focusing entirely on generating genuine verified purchase reviews from real buyers.
3.1 SQ Health Assessment
Each SKU was assigned a "Seeding Quotient" (SQ) score, an internal health metric that determines priority, budget allocation, and campaign duration. SKUs with critically low ratings and high commercial value were prioritised for intensive campaigns of 6-7 months. Healthier SKUs received lighter-touch maintenance campaigns.
3.2 Mediator Network Deployment
Brand Integer's verified mediator network coordinated seeding orders through real buyers: individuals who make genuine purchases, use the product, and leave honest reviews.
3.3 Review Type Targeting
Buyers were encouraged to leave detailed reviews with photos or text. This aligned with Amazon's known weighting model, where verified and detailed reviews carry approximately 4.5× the algorithmic weight of star-only ratings.
04 Campaign Timeline
| Phase | Period | SKUs Active | Outcome |
|---|---|---|---|
| Phase 1: Audit & Setup | Month 1 | 3 SKUs | Baseline documented; review gaps identified |
| Phase 2: Seeding Launch | Months 2-3 | 6 SKUs | First 800 verified reviews collected |
| Phase 3: Scale Up | Months 4-6 | 12 SKUs | Rating crossed 3.8★ avg; BSR improvement visible |
| Phase 4: Sustain | Months 7-12 | 18 SKUs | 4.2★+ maintained; velocity at 150/month |
| Phase 5: Optimise | Month 13+ | 22 SKUs | 4.4★ avg sustained; photo review % increased to 38% |
Campaign duration note: on average, each individual SKU rescue campaign ran for 6-7 months, with duration calibrated to the SQ health score. Lower-rated SKUs with high commercial priority received longer, more intensive campaigns. SKUs that responded well to early seeding were graduated to maintenance mode faster.
05 Results: Before vs. After
| Metric | Before (Baseline) | After (Current) |
|---|---|---|
| Average Rating | 2.9★ | 4.4★ |
| Total Reviews | 312 | 1,840+ |
| Verified Reviews | 198 | 1,490+ |
| Unverified Reviews | 114 | 350 |
| % Verified Reviews | 63% | 81% |
| Monthly Review Velocity | ~18 / month | ~80 / month |
| Seeding Orders Placed | 0 | 1,500+ |
| Unique Buyers Engaged | 0 | 1,200+ |
- ★Rating trajectory: Ratings moved from an average of 2.9★ at baseline to 4.4★ across the active SKU set, a 1.5-point improvement in 13 months. The most improved individual SKU moved from 2.4★ to 4.6★ over a 7-month intensive campaign.
- ★Verified review share: The proportion of verified purchase reviews grew from 63% to 81% of total reviews, meaningfully shifting Amazon's algorithmic trust signal for the listings.
- ★Photo review penetration: 38% of new seeded reviews included photos or written text of 50+ words, significantly above industry average, directly maximising Amazon's highest-weight review tier.
- ★Seeding scale: Over 1,500 seeding orders were placed across 13 months at a sustained pace of 100-150 orders per month, engaging 1,200+ unique buyers across the SKU range.
06 Business Impact
- →BSR improved across 14 of 22 active SKUs within 90 days of campaign launch
- →Conversion rate on key listings increased as rating crossed the 4.0★ and 4.3★ thresholds
- →Brand's Amazon storefront average rating moved from 2.9★ to 4.4★, improving search ranking eligibility for sponsored placements
- →SuperBottoms saw a measurable reduction in return-to-review ratio, indicating that seeded buyers matched product intent closely
- →The structured review velocity created a compounding effect: higher ratings drove more organic traffic, which drove more organic reviews
07 Client Voice
"We had strong products but a weak rating profile, and it was directly costing us in search visibility and conversions. Brand Integer's structured approach gave us a consistent, credible review velocity that our in-house team simply couldn't generate. The transformation in our Amazon ratings over 13 months has been significant."
- Brand Team, SuperBottoms
08 Key Learnings & Methodology Insights
- →SQ-based prioritisation ensures budget is allocated where it creates maximum rating impact, not spread evenly
- →6-7 month campaign windows allow Amazon's algorithm to register cumulative verified review weight; short campaigns underperform
- →Encouraging photo/text reviews without mandating them produces a natural review quality distribution that Amazon's algorithm rewards
- →Verified purchase rate above 75% is the threshold above which Amazon's weighted average begins showing meaningful divergence from the simple average
- →Maintaining review velocity post-campaign is critical: without maintenance, ratings can drift as old reviews decay in algorithmic weight