Research
Original measurement of the B2B data and GTM tooling category, with the raw dataset published beside every study. Everything here is released under CC BY 4.0, so you may republish any figure, table or chart commercially, provided you credit Cleanlist with a link.
Cleanlist runs these studies, Cleanlist appears in most of them, and Cleanlist loses several of the metrics. Where that happens it is stated on the study page before anything else. The reason to publish the dataset is so that you never have to take our word for a count: download the CSV and run it yourself. If your number differs from ours, your number is the interesting one, and victor@cleanlist.ai is where to send it.
- 208 queries · 199 AI Overviews
The source-to-mention gap: 208 GTM buyer queries inside Google's AI Overviews
Google's AI Overviews cite cleanlist.ai in 14 of 199 answers and speak the word "Cleanlist" in 2 of them. Apollo is named in 49. Being read and being named are close to unrelated.
Collected September 1, 2026
Read the studyQuery-level dataset, CSV - 827 pages · 1,000 queries · 16 months
What AI Overviews did to our click-through rate: 16 months of Search Console
7,458,554 Search Console impressions returned 40,566 clicks, a site-wide CTR of 0.54%. Dividing each page's clicks by the normal rate for its reported position leaves only 18.5% of that impression pool behaving like human search.
Exported August 31, 2026
Read the studyPage-level and query-level dataset, CSV - 60 vendors probed directly
The GTM MCP server census
45 of 60 GTM and B2B data vendors ship a live MCP server, 39 of them confirmed on the wire rather than from documentation. Cleanlist is one of the 45. Any vendor claiming to be first, Cleanlist included, is wrong.
Probed September 1, 2026
Read the studyPer-vendor probe results, CSV - 38 vendors · 24 rankable
The B2B data pricing index
38 pricing pages fetched on one date and normalised to a cost per 1,000 verified emails. Six vendors publish no purchasable price at all. Across the 24 that can be ranked the range runs $13.00 to $490.00, a 38-fold spread, and Cleanlist is 10th of the 24. Nine vendors are cheaper than we are.
Fetched September 1, 2026
Read the studyPer-vendor pricing dataset, CSV - 38 vendors · every plan page read on one date
The B2B data free-tier census: what 38 tools actually give you free
18 of 38 vendors publish no recurring free plan at all. Among those that do, the median allowance is 40 verified emails a month, and only 7 of the 38 let you upload a CSV in bulk without paying. The advertised credit count is rarely the binding constraint.
Fetched September 1, 2026
Read the studyPer-vendor free-tier dataset, CSV - 411 queries · 4,027 classified results
Reddit owns B2B software discovery
reddit.com ranks on 147 of the 208 GTM queries (71%), and on the broader B2B software set it holds position 1 outright on 30% of them. Rival vendors' blogs take 46.5% of every organic slot measured, while Google's AI Overviews cite YouTube more than any other domain.
Collected September 1, 2026
Read the studyResult-level SERP anatomy dataset, CSV - 120 SERPs · 30 vendors · 2,244 results
The alternatives-page economy in B2B software
Across 120 "[vendor] alternatives" SERPs covering 30 vendors, all 120 carry an AI Overview and all 120 name Apollo. The vendor named in the query ranks top 10 on 67% of its own SERPs and holds position 1 on 12 of the 120. Cleanlist is named on 3.
Collected September 1, 2026
Read the studyResult-level alternatives dataset, CSV - 500 stratified B2B leads
The Cleanlist 500-Lead Enrichment Benchmark, 2026
On 500 stratified B2B leads run through a 25+ provider waterfall, 98% returned a verified email and 85% a direct dial. Single-source providers returned 70% to 80% on email and 30% to 60% on phone against the identical list.
Run July 2026, standing benchmark
Read the studyDataset publishes with the study
How these studies are run
Search results are collected through the DataForSEO SERP API against Google, United States, desktop, in English, unless a study says otherwise. Vendor pricing and plan pages are fetched directly, with a browser user agent for server-rendered pages and headless Chromium for tables that render client-side, and every figure carries the source URL and the date it was captured. MCP servers are probed by sending a real initialize call over the wire rather than by reading a vendor’s marketing page. Our own traffic figures come from Google Search Console exports, not from a third-party estimator. Classification rules are printed on each study page in full, including the ones that make our own numbers look worse.
The limits, stated plainly, because a study that hides them gets cited once and trusted never:
- One snapshot. Almost everything here is a single day. Search results move, prices change, and a re-run a week later will not reproduce every row.
- One country, one device, one language. United States, desktop, English. Results elsewhere will differ, and we do not know by how much.
- AI Overviews are personalised and non-deterministic. The same query can return a different answer, a different set of citations, or no AI Overview at all. Where a study re-pulls queries to measure that instability, it says so and reports the result.
- A parse, not a human read. Brand names and cited domains are matched by code against fixed rules. Code produces false positives and false negatives. The rules are published so you can find ours.
- Sample size and sample choice. Query sets are in the hundreds, not the millions, and they were chosen by us to cover our own category. That makes these samples of one market rather than random samples of Google.
- We are an interested party. Cleanlist sells B2B data enrichment and competes with vendors named in these studies. Several of the vendors measured, including Hunter, Lusha, Wiza, Prospeo, Findymail, Crustdata and ZeroBounce, are suppliers in our own enrichment waterfall. They are measured on the same rules as everyone else.
How to cite
All studies and datasets on this page are licensed Creative Commons Attribution 4.0 International. You may copy, redistribute, adapt and build on them for any purpose, including commercially, as long as you credit Cleanlist and link to the study. No permission email required. Pick a line and paste it.
- The source-to-mention gap: 208 GTM buyer queries inside Google's AI Overviews
Paraschiv, V. (2026, September 1). The source-to-mention gap: 208 GTM buyer queries inside Google's AI Overviews. Cleanlist. https://www.cleanlist.ai/blog/2026-09-01-ai-overview-citation-study-b2b-data- What AI Overviews did to our click-through rate: 16 months of Search Console
Paraschiv, V. (2026, September 1). What AI Overviews did to our click-through rate: 16 months of Search Console. Cleanlist. https://www.cleanlist.ai/blog/2026-09-01-ai-overviews-destroyed-our-ctr-search-console-study- The GTM MCP server census
Paraschiv, V. (2026, September 1). The GTM MCP server census. Cleanlist. https://www.cleanlist.ai/blog/2026-09-01-gtm-mcp-server-census- The B2B data pricing index
Paraschiv, V. (2026, September 1). The B2B data pricing index. Cleanlist. https://www.cleanlist.ai/blog/2026-09-01-b2b-data-pricing-index- The B2B data free-tier census: what 38 tools actually give you free
Paraschiv, V. (2026, September 1). The B2B data free-tier census: what 38 tools actually give you free. Cleanlist. https://www.cleanlist.ai/blog/2026-09-01-b2b-data-free-tier-census- Reddit owns B2B software discovery
Paraschiv, V. (2026, September 1). Reddit owns B2B software discovery. Cleanlist. https://www.cleanlist.ai/blog/2026-09-01-reddit-owns-b2b-software-discovery- The alternatives-page economy in B2B software
Paraschiv, V. (2026, September 1). The alternatives-page economy in B2B software. Cleanlist. https://www.cleanlist.ai/blog/2026-09-01-alternatives-page-economy-b2b-software- The Cleanlist 500-Lead Enrichment Benchmark, 2026
Cleanlist. (2026). The Cleanlist 500-Lead Enrichment Benchmark, 2026. https://www.cleanlist.ai/blog/2026-07-05-b2b-data-enrichment-accuracy-benchmark-2026
Citing the whole programme rather than one study:
Cleanlist. (2026). Cleanlist Research: open datasets on the B2B data and GTM tooling category. https://www.cleanlist.ai/research