---
title: "Reviews — pride badge - Flapen"
canonical_url: "https://flapen.com/research/uk/fashion/pride-badge/reviews"
last_updated: "2026-07-31T13:54:45.156Z"
locale: en
meta:
  description: "Niche score 63/100 · £10K/yr market · 42K searches/yr. A failed launch gate (market size, growth, or returns) keeps it on the watch list. Data updated Jul 2026."
  "og:description": "Niche score 63/100 · £10K/yr market · 42K searches/yr. A failed launch gate (market size, growth, or returns) keeps it on the watch list. Data updated Jul 2026."
  "og:title": "Reviews — pride badge - Flapen"
---

# **pride badge**

**Worth a look**

Shows low returns (0.3%), but a failed launch gate (market size, growth, or returns) keeps it on the watch list.

Market size 3Growth 98Conversion 51Competition 84Returns 99Price range 6Avg price 16Brand share 95Review moat 98Quality gap 48

**Returns**

**Incredible****0.3%**

return rate — above 5% kills the launch gate

**Growth**

**Incredible****+210.0%**

90-day search growth — must beat 0% to launch

**Review moat**

**Incredible****46.79**

avg incumbent reviews — the moat a new listing must climb

**Brand share**

**Incredible****39%**

top-5 brand share — no brand owns this niche

**Competition**

**Great****31%**

top-5 click share — an open shelf

**Conversion**

**Good****4.1%**

search→purchase rate — share of searches ending in a sale

**Quality gap**

**Okay****4.5★**

avg incumbent rating — lower means beatable quality

**Avg price**

**Bad****£5.81**

avg listing price — sweet spot $15–$100

**Price range**

**Bad****£2.96–£15.71**

cheapest to priciest tracked listing — scored on the share inside $15–$100

**Market size**

**Bad****£10K**

£10K/yr · 42K searches

**Signals**[** Trending**](https://flapen.com/research/niches?market=uk&signal=trending "Search growth > 100% (90d)") [** No Dominant Brand**](https://flapen.com/research/niches?market=uk&signal=no_dominant_brand "Top brand's click share < 20%") [** Low Review Barrier**](https://flapen.com/research/niches?market=uk&signal=low_review_barrier "Top brand's reviews < 500")