| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Data warehouse and reverse ETL for marketing | GTM data and infrastructure | 40% | 1 of 83 | 9% | 80 | endorsed leader | ▼−4Since September 2026: 42% → 38%, −4 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Customer data platforms | GTM data and infrastructure | 20% | 2 of 61 | 5% | 42 | accepted challenger | ▼−1Since September 2026: 20% → 20%, −1 point. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Data management platforms | GTM data and infrastructure | 12% | 2 of 159 | 0% | 18 | accepted challenger | ▼−4Since September 2026: 11% → 6%, −4 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Customer intelligence and data science | GTM data and infrastructure | 2% | 10 of 142 | 0% | 7 | under 10 labels · led by Amplitude at 18% | =heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| AI marketing agents | Marketing | 0% | 130 of 157 | 0% | 1 | under 10 labels · led by HubSpot Breeze at 24% | |
| Marketing automation and campaign management | Marketing | 0% | 37 of 59 | 0% | 1 | under 10 labels · led by HubSpot Marketing Hub at 63% | newNew since September 2026: not ranked then, 0% now. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| DMP | 11% | 6% | ▼−4Since September 2026: 11% → 6%, −4 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 2 of 159, unchanged |
| Warehouse & ETL | 42% | 38% | ▼−4Since September 2026: 42% → 38%, −4 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 1 of 83, unchanged |
| CDP | 20% | 20% | ▼−1Since September 2026: 20% → 20%, −1 point. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 2 of 61, unchanged |
| Customer intel | 2% | 2% | =heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 10 of 142, unchanged |
| AI marketing agents | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 130 of 157, unchanged |
| Marketing automation | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 37 of 59, unchanged |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 4 | 3 | 2 | 0 | 9 |
| GPT-5.4 mini | 7 | 1 | 1 | 0 | 9 |
| Gemini 3.5 Flash | 11 | 3 | 3 | 0 | 17 |
| Perplexity Sonar | 3 | 4 | 1 | 1 | 9 |
| Grok 4.1 Fast | 6 | 4 | 3 | 1 | 14 |
| Mistral Small | 5 | 0 | 1 | 2 | 8 |
| DeepSeek V4 Flash | 5 | 6 | 2 | 1 | 14 |
| Llama 4 Maverick | 0 | 2 | 6 | 0 | 8 |
| Qwen 3.7 Flash | 5 | 4 | 0 | 0 | 9 |
| Kimi K2 | 5 | 4 | 2 | 1 | 12 |
| GLM 4.7 FlashX | 3 | 6 | 0 | 0 | 9 |
| MiniMax M2.5 | 5 | 1 | 0 | 1 | 7 |
| GPT-6 Luna | 8 | 2 | 1 | 1 | 12 |
| Muse Glimmer 30B | 5 | 3 | 3 | 1 | 12 |
Verbatim evidence the judge attached to positive labels.
“The Winner: Hightouch ... Choose Hightouch if you already have a Snowflake or BigQuery instance and want a long-term, scalable, secure customer data platform.” Gemini 3.5 Flash · DMP · direct prompt · first choice
“Hightouch: Free tier for testing/small syncs (~10k rows/month)... No-code audience builder, 300+ destinations—marketer-friendly.” Grok 4.1 Fast · Warehouse & ETL · budget prompt · first choice
“Hightouch is the default recommendation for most marketing and growth teams with an existing Snowflake or BigQuery warehouse” Claude Haiku 4.5 · Warehouse & ETL · comparative prompt · first choice
“Hightouch is usually the safest default when the warehouse is the source of truth and marketing needs audience activation.” Muse Glimmer 30B · Warehouse & ETL · paraphrase prompt · first choice
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“Hightouch documents that operational data such as sync logs and row-level status may be stored; review the details against your own requirements” GPT-6 Luna · Warehouse & ETL · negative prompt · soft negative
“Hightouch if your warehouse data model is immature or your team lacks SQL resources, because setup can stall before activation work begins.” Perplexity Sonar · CDP · negative prompt · soft negative
“Pricing concerns: Users report it can be expensive, particularly for large contact volumes, with some sudden price changes” MiniMax M2.5 · Warehouse & ETL · negative prompt · soft negative
“user feedback flags cost and support issues: "The per-destination pricing model makes it hard to scale for smaller use cases"” Muse Glimmer 30B · Warehouse & ETL · negative prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 363 of the 390 answers that named Hightouch and are not a share of its labels.
920 of the 1,079 domain citations in answers naming Hightouch came from somebody else's page.
Pages are listed as the models cited them.
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 539 | 12 | 2026-09-24 | ||
| Conference or event | 127 | 0 | 2026-06-17 | ||
| Report or ebook | 125 | 0 | 2025-03-03 | ||
| Comparison | 74 | 0 | 2026-05-22 | ||
| Case study | 48 | 0 | 2026-06-23 | ||
| Glossary or explainer | 40 | 2 | 2026-09-24 | ||
| Webinar or virtual event | 10 | 0 | 2024-10-10 | ||
| Podcast or video | 2 | 0 | 2022-10-28 | ||
| Template or tool | 1 | undated |
As the event pages on hightouch.com state them, read September 28, 2026.
Every page hightouch.com exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
What Hightouch's own pages state, read September 28, 2026: hightouch.com, hightouch.com/pricing, trust.hightouch.com, hightouch.com/platform-privacy, hightouch.com/customers. A claimed page can correct any of them.
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Hightouch's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Hightouch, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for Hightouch by email, built from the raw record of the edition. It shows:
AI models recommend Hightouch first in Data warehouse and reverse ETL for marketing this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
Hightouch is among the products AI models recommend first in Customer data platforms this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
Hightouch is among the products AI models recommend first in Data management platforms this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
Badges read on light and dark pages. Alt text carries the claim, the category, the edition and the index, so it stays a citation where the image does not load.