---
title: "Search terms — pool table - Flapen"
canonical_url: "https://flapen.com/research/uk/sports-outdoors/pool-table/search-terms"
last_updated: "2026-07-31T20:24:13.872Z"
locale: en
meta:
  description: "Niche score 54/100 · £1.2M/yr market · 842K searches/yr · £320.13 avg price. Weak search conversion (0.4%) keeps it on the watch list. Data updated Jul 2026."
  "og:description": "Niche score 54/100 · £1.2M/yr market · 842K searches/yr · £320.13 avg price. Weak search conversion (0.4%) keeps it on the watch list. Data updated Jul 2026."
  "og:title": "Search terms — pool table - Flapen"
---

# **pool table**

**Worth a look**

Shows beatable incumbent ratings (3.8★), but weak search conversion (0.4%) keeps it on the watch list.

Market size 81Growth 24Conversion 6Competition 54Returns 87Price range 7Avg price 28Brand share 42Review moat 97Quality gap 97

**Quality gap**

**Incredible****3.8★**

avg incumbent rating — lower means beatable quality

**Review moat**

**Incredible****58.52**

avg incumbent reviews — the moat a new listing must climb

**Returns**

**Great****1.4%**

return rate — above 5% kills the launch gate

**Market size**

**Great****£1.2M**

£1.2M/yr · 842K searches

**Competition**

**Good****53%**

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

**Brand share**

**Okay****80%**

top-5 brand share — brands hold most of the demand

**Avg price**

**Okay****£320.13**

avg listing price — sweet spot $15–$100

**Growth**

**Bad****-2.8%**

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

**Price range**

**Bad****£38.33–£986.09**

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

**Conversion**

**Bad****0.4%**

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

**Signals**[** Low Review Barrier**](https://flapen.com/research/niches?market=uk&signal=low_review_barrier "Top brand's reviews < 500") [** Quality Gap**](https://flapen.com/research/niches?market=uk&signal=quality_gap "Avg rating < 4.0") [** High Price**](https://flapen.com/research/niches?market=uk&signal=high_price "Avg price > $50")