GTM AI Index
Index Marketing ABM › Apollo.io vs Demandbase
Account-based marketing platforms · September 2026 Edition

Apollo.io vs Demandbase

Zero of twelve models named Apollo.io first on the direct prompt; zero named Demandbase. Apollo.io was named by ten of the twelve models and Demandbase by twelve and Apollo.io carries 15 labels and Demandbase 60, so the shares are not directly comparable.

Apollo.io

accepted challenger

San Francisco, United States, founded 2015. Named in twenty categories this edition.

Demandbase

criticized challenger

San Francisco, United States, founded 2006. Named in eighteen categories this edition.

First-choice share4%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate13%42%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#6A position in a field of 11; printed, not drawn.
Labels1560A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Apollo.io reading right to left. Rank and label count are printed, not drawn.AdRoll ABM was named alongside these two in twelve of the twelve direct answers. AdRoll ABM vs Apollo.io · AdRoll ABM vs Demandbase · HubSpot ABM vs Apollo.io

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the account-based marketing platforms page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
Apollo.ioFirst choices, of twelve modelsDemandbase
Direct003 against Demandbase
Paraphrase006 against Demandbase
Comparative09
Budget-constrained206 against Demandbase
Scale-constrained021 against Demandbase
Negative002 against Apollo.io · 9 against Demandbase
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Across every category in the September 2026 Edition, Apollo.io and Demandbase were named in the same answer 179 times, of the 858 answers naming Apollo.io and the 610 naming Demandbase. In those answers Demandbase took the first choice three times and Apollo.io seventy-three.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Apollo.io and Demandbase stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
Apollo.io Demandbase first choice named as an alternative argued againstblank: not namedEach cell is one answer, Apollo.io on the left and Demandbase on the right.

The direct prompt

The plain question, one answer per model, grouped by where Apollo.io and Demandbase stood in it.

Neither was the first choice, one was named

7 of 12 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 mini6sense alternatives: AdRoll ABM, Demandbase
Perplexity SonarAdRoll ABM alternatives: 6sense, Demandbase
Grok 4.1 FastAdRoll ABM alternatives: Demandbase, HubSpot Marketing Hub, Terminus
Llama 4 MaverickAdRoll ABM alternatives: 6sense Revenue AI, Demandbase, Metaflow AI, ZoomInfo MarketingOS
Qwen 3.7 FlashAdRoll ABM alternatives: 6sense, Demandbase, Terminus
GLM 4.7 FlashXAdRoll ABM, HubSpot ABM alternatives: 6sense Revenue AI, Demandbase
MiniMax M2.5AdRoll ABM alternatives: 6sense Revenue AI, Demandbase, Terminus

Neither was named

5 of 12 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5AdRoll ABM, ZoomInfo alternatives: 6sense
Gemini 3.5 FlashAdRoll ABM alternatives: 6sense, Abmatic AI, HubSpot ABM
Mistral SmallAdRoll ABM alternatives: Factors.ai, HockeyStack, HubSpot Native ABM, Terminus
DeepSeek V4 FlashAdRoll ABM, Terminus alternatives: HubSpot ABM
Kimi K2AdRoll ABM alternatives: 6sense, DemandScience, HubSpot Marketing Hub

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Apollo.io leads by sixteen points.
Apollo.io16%#3 of 13
Demandbase0%#13 of 13
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Apollo.io4%#5 of 11
Demandbase4%#6 of 11
The full mid-market standing →
Enterprise
The order flips: Demandbase leads at enterprise.
Demandbase47%#1 of 8
Apollo.io0%#– of 8
The full enterprise standing →

What the models said about Apollo.io

No label in this category carried a quote.

What the models said about Demandbase

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of five in this category shown.

“What to Avoid for Mid-Sized Companies: Demandbase & 6sense - Enterprise pricing ($60K-$300K/year) typically too high” Mistral Small · paraphrase prompt · hard negative
“### Demandbase - Pricing Opacity: Complex, non-transparent pricing structure ... Technical Debt” GLM 4.7 FlashX · negative prompt · hard negative
“the most suitable ABM platforms are likely to be Demandbase, 6sense, or RollWorks, which are designed for mid-market to enterprise companies” Llama 4 Maverick · scale prompt · first choice
“Demandbase One | Balanced GTM orchestration, sales-marketing alignment | $50K–$200K/yr | Unified workflows; strong for complex cycles” Qwen 3.7 Flash · scale prompt · first choice
“Enterprise companies with complex buying committees often choose 6sense or Demandbase for their deep account intelligence” Claude Haiku 4.5 · comparative prompt · first choice
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.