Whose logos are on B2B homepages, the logo-wall census
Does your homepage need a wall of customer logos, and whose should they be? We checked 479 B2B homepages for logo walls, counted every wall, and tallied which customers appear most, so you can size your social proof against the cohort instead of guessing.
Executive summary
Logo walls are the minority choice: 101 of 479 homepages (21.1%, 95% CI 17.7-25.0%) display a customer logo wall, and the typical wall carries just 5 logos. The most-displayed customers are the usual enterprise suspects, Amazon (4 walls), Clay, Netflix and Google (3 each), but no customer appears on more than 4% of walls: B2B social proof is fragmented, not concentrated.
Two contrasts matter. First, walls ignore company size (22.9% at 1-10 staff vs 30.8% at 200+), unlike story hubs (33% to 90%) and comparison pages (24% to 51%), which both climb steeply. A wall is a day-one asset, not a scale program. Second, flat-billing vendors lead (37.6%) while pages with numbers but no tiers show zero walls, proof follows the self-serve motion, where the page must sell without a salesperson.
How to use this: five recognizable logos beat fifteen obscure ones, the median wall is 5, and buyers skim walls for names they know. If your customers are mid-market, say so with a story, not a wall; walls work when the names do the arguing.
Who shows a wall
| Team size | Wall rate | 95% CI |
|---|---|---|
| 1-10 employees (n=96) | 22.9% | 15.6-32.3% |
| 11-50 employees (n=149) | 27.5% | 21.0-35.2% |
| 51-200 employees (n=87) | 28.7% | 20.3-39.0% |
| 200+ employees (n=26) | 30.8% | 16.5-50.0% |
By billing model
| Billing model | Wall rate |
|---|---|
| Flat / tiered (n=85) | 37.6% |
| Usage-based (n=41) | 29.3% |
| Per-seat (n=45) | 26.7% |
| Contact-only (n=96) | 29.2% |
| Page, no numbers (n=30) | 0.0% |
| No pricing page (n=64) | 23.4% |
Flat-billing vendors lead at 37.6%; vendors whose pages show numbers without tiers show no walls at all. Contact-only enterprise vendors sit mid-pack (29.2%), their proof lives in decks and story hubs, not homepage strips.
How deep the walls go
Most-displayed customers
Aggregate tallies across 101 walls. No logos republished; counts only.
| Customer | Walls | Share of walls |
|---|---|---|
| Amazon | 4 | 4.0% of walls |
| Clay | 3 | 3.0% of walls |
| Netflix | 3 | 3.0% of walls |
| 3 | 3.0% of walls | |
| Adobe | 2 | 2.0% of walls |
| Meta | 2 | 2.0% of walls |
| Uber | 2 | 2.0% of walls |
| Walmart | 2 | 2.0% of walls |
| Spotify | 2 | 2.0% of walls |
| Sendoso | 2 | 2.0% of walls |
| Replit | 2 | 2.0% of walls |
| Apple | 2 | 2.0% of walls |
| Disney | 2 | 2.0% of walls |
| Drata | 2 | 2.0% of walls |
| Fathom | 2 | 2.0% of walls |
| Brex | 2 | 2.0% of walls |
One mark in four is unreadable to a crawler
74.2% of wall marks carry an identifiable name (alt text, filename or link); 25.799999999999997% are hashed asset filenames, light/dark variants, or bare marks.
This is a measurement note with a marketing moral: if a quarter of your customer logos are unreadable to automated readers, they are also weaker for accessibility, name your logo files and alt text after the customer and both audiences win. Investor-logo strips were separated, not counted: 4 companies show backers where customers would go.
Walls, hubs, and attacks: the proof stack
74 of 101 wall domains also publish comparison pages; 50 also run story hubs.
The three proof surfaces stack by effort: walls are cheap and flat across sizes, story hubs cost writing and climb with size, comparison pages cost maintenance and climb steepest. Vendors that do all three (74 in this sample) are running competitive content as a program, not a page, and the wall is where nearly all of them started.
Who this is for
Five known logos beat fifteen unknowns
The median wall is 5 marks and the most-displayed customer appears 4 times in 101 walls. Lead with the names buyers recognize; a long strip of unknowns reads as filler, not proof.
Name the files after the customer
25.799999999999997% of wall marks in this sample are unreadable to automated readers (hashed filenames, bare variants). Descriptive alt text and filenames serve accessibility and AI extractability at once.
Walls open, stories close
Walls are flat across sizes because they do awareness work. If enterprise deals need proof, the story hub (33%→90% by size) is where the cohort invests, point buyers there, not at the strip.
Counts, never trademarks
Name tallies only; no logo was republished. Reuse the per-wall CSV with the identifiability caveat attached, a quarter of marks are machine-unreadable.
Methodology & reproducibility
What we read: all 479 homepages fetched October 2026 (364 loaded); walls detected by trusted-by/customer/logo-wall patterns in server-rendered HTML, validated per section by requiring 2+ logo images. Investor strips separated, never counted. JavaScript-only walls are missed and coded as such.
How names were read: alt text first, then filenames, then link targets, with URL-decoding, camelCase splitting, variant suffixes (light/dark/white) and hash-prefixed asset names handled. Hash-prefixed filenames with no usable alt were counted toward wall size but marked unidentifiable rather than guessed. A 25-wall hand review drove three cleaning rounds; residual truncation noise (cropped alts like "strip") is disclosed, not hidden.
What changed from the plan: the 2023-2026 turnover series was dropped (archive fidelity too low for per-logo matching); Fortune-500 matching was dropped (no retrievable list under our crawler policy); one reviewer so far.
Downloadable datasets: walls.csv (per-domain wall presence and counts) and customers.csv (customer tallies).
python3 scripts/research/s5_fetch.py # homepage fetch + wall detection (resumable)
python3 scripts/research/s5_clean.py # name cleaning (re-runnable, no refetch)
python3 scripts/research/build_s5_page.py # rebuild this page
Corrections
Factual corrections are published on the page; send the URL to amit@datadab.com.
Covering this research? Please link the primary source so readers can verify the data and methodology:
Markdown: [B2B SaaS Logo-Wall Census 2026 by DataDab](https://www.datadab.com/research/b2b-saas-logo-wall-census/)
Spot an error? Send the URL to amit@datadab.com; corrections are published on the page.
What this study does not show
- Wall turnover. Dropped: archive fidelity is too low for per-logo year-over-year matching.
- Enterprise membership. Dropped: no Fortune-500 list retrievable under our crawler policy.
- JS-only walls. Client-rendered logo strips without server HTML are missed.
- Single reviewer. Detector plus three cleaning rounds with hand review; no independent double-coding yet.