---
title: "Trend — all in one - Flapen"
canonical_url: "https://flapen.com/research/uk/computers-accessories/all-in-one/trend"
last_updated: "2026-07-31T13:21:07.853Z"
locale: en
meta:
  description: "Niche score 52/100 · £107K/yr market · 77K searches/yr · £199.52 avg price. Weak search conversion (0.7%) keeps it on the watch list. Data updated Jul 2026."
  "og:description": "Niche score 52/100 · £107K/yr market · 77K searches/yr · £199.52 avg price. Weak search conversion (0.7%) keeps it on the watch list. Data updated Jul 2026."
  "og:title": "Trend — all in one - Flapen"
---

# **all in one**

**Worth a look**

Shows beatable incumbent ratings (4.0★), but weak search conversion (0.7%) keeps it on the watch list.

Market size 26Growth 20Conversion 9Competition 74Returns 91Price range 14Avg price 46Brand share 82Review moat 73Quality gap 92

**Quality gap**

**Great****4.0★**

avg incumbent rating — lower means beatable quality

**Returns**

**Great****1.2%**

return rate — above 5% kills the launch gate

**Brand share**

**Great****53%**

top-5 brand share — no brand owns this niche

**Competition**

**Good****40%**

top-5 click share — leaders hold, buyers still browse

**Review moat**

**Good****585.07**

avg incumbent reviews — the moat a new listing must climb

**Avg price**

**Okay****£199.52**

avg listing price — sweet spot $15–$100

**Market size**

**Okay****£107K**

£107K/yr · 77K searches

**Growth**

**Bad****-9.0%**

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

**Price range**

**Bad****£8.91–£637.67**

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

**Conversion**

**Bad****0.7%**

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

**Signals**[** 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") [** High Price**](https://flapen.com/research/niches?market=uk&signal=high_price "Avg price > $50")