---
title: "Trend — back bumper - Flapen"
canonical_url: "https://flapen.com/research/us/automotive/back-bumper/trend"
last_updated: "2026-08-09T19:26:15.028Z"
locale: en
meta:
  description: "Niche score 55/100 · $479K/yr market · 756K searches/yr · $204.28 avg price. Weak search conversion (0.3%) keeps it on the watch list. Data updated Jul 2026."
  "og:description": "Niche score 55/100 · $479K/yr market · 756K searches/yr · $204.28 avg price. Weak search conversion (0.3%) keeps it on the watch list. Data updated Jul 2026."
  "og:title": "Trend — back bumper - Flapen"
---

# **back bumper**

**Worth a look**

Shows no brand lock-in (top 5 brands take 33% of clicks), but weak search conversion (0.3%) keeps it on the watch list.

Market size 59Growth 14Conversion 4Competition 93Returns 42Price range 12Avg price 45Brand share 96Review moat 94Quality gap 86

**Brand share**

**Incredible****33%**

top-5 brand share — no brand owns this niche

**Review moat**

**Great****118.33**

avg incumbent reviews — the moat a new listing must climb

**Competition**

**Great****22%**

top-5 click share — an open shelf

**Quality gap**

**Great****4.1★**

avg incumbent rating — lower means beatable quality

**Market size**

**Good****$479K**

$479K/yr · 756K searches

**Avg price**

**Okay****$204.28**

avg listing price — sweet spot $15–$100

**Returns**

**Okay****3.7%**

return rate — above 5% kills the launch gate

**Growth**

**Bad****-21.9%**

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

**Price range**

**Bad****$5.43–$713.77**

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

**Conversion**

**Bad****0.3%**

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

**Signals**[** No Dominant Brand**](https://flapen.com/research/niches?market=us&signal=no_dominant_brand "Top brand's click share < 20%") [** Low Review Barrier**](https://flapen.com/research/niches?market=us&signal=low_review_barrier "Top brand's reviews < 500") [** High Price**](https://flapen.com/research/niches?market=us&signal=high_price "Avg price > $50")

## Trend