Demandbase alternatives for account intelligence data

Demandbase sells a platform for account-based marketing and sales: it identifies accounts, measures their interest, runs advertising to them and gives sellers tools to act. This guide is for the marketing operations, revenue operations or data lead who wants the account intelligence itself, as tables in a warehouse, and who already runs the scoring, the campaigns and the CRM on tools the team has chosen. It covers what Demandbase says it offers, what the platform is built for, four other vendors, and a way to assemble an account record from company-level data in your own stack. Statements about other companies rest on their own pages as they stood on 4 October 2026, linked where they are used.

The two are built for different jobs. Demandbase's pages describe an advertising product, the identification of companies that visit your website, contact and buying-group data, and intent drawn from the advertising bidstream. Fokals is the data layer under a stack you already run: firmographic, technographic, hiring and intent data on one company index, every record dated, delivered by REST API and as bulk files.

What Demandbase says it offers

The title of the home page calls Demandbase an ABM platform for B2B sales and marketing, and its Platform menu lists four parts: Marketing, Advertising, Sales and Data.

• Intent. The intent page says Demandbase has its own technology for identifying unknown accounts and combines it with direct access to the bidstream, then applies AI and natural language processing to the signals. Customers create keyword sets, and the page says Bombora, G2 and TrustRadius intent can be imported beside Demandbase's own.
• Account identification. The account identification page describes revealing the companies that visit a customer's website, using Demandbase's IP and cookie data.
• Data. The data page describes firmographic, technographic, buyer and intent data, with person-level intent and buying groups, synced to CRM, warehouse, marketing, advertising and sales systems through APIs and warehouse-native delivery. A separate offering, PoweredBy Demandbase, is described as a platform that technology providers can embed in their own products through APIs and enrichment services.
• Advertising. The advertising page describes advertising aimed at target accounts and buying groups, delivered across display, video, connected TV, social and web.
• Pricing. The pricing page shows no figures and asks you to fill out a form for a customised plan. It says Demandbase is not split into separate marketing and sales solutions, and that the data solutions can be used on their own.

What Demandbase is built for

• One system that acts. In Demandbase, advertising, coordinated marketing programmes and seller tools share one platform and its data.
• Knowing who is on your website. Demandbase identifies visiting companies from IP and cookie data.
• Intent from outside a company's own actions. Demandbase's intent draws on the advertising bidstream and on the keywords you choose, and it can bring in Bombora, G2 and TrustRadius intent.
• People and buying groups. Demandbase's data page describes buyers, buying groups and person-level intent.
• Integrations with the tools around it. Demandbase's platform page names integrations with CRM, marketing automation and sales engagement tools.

Why a team looks for an alternative

Each reason below is a matter of fit and no reflection on the platform.

• Scope. The CRM, the marketing automation and the advertising accounts are already in place. The team needs data, not another place to work.
• Delivery. Scoring runs in a warehouse or a model, which needs rows with a stable company key and a date on each, fetched when the team's own jobs run. Fokals delivers every dataset on one stable company ID, with the observation time on each record.
• Licence fit. Showing data inside your own product, or passing it to clients, is a different licence from internal use. Demandbase has a separate offering for embedding, PoweredBy Demandbase, and any other vendor should be asked the same question. A Fokals agreement is written for internal use, embedding in a product or redistribution.
• A different kind of data. Some buyers work under a sourcing policy that admits only public records and a company's own publications. Others have to show their reasoning: for each signal, its date and the public page or filing it came from. Fokals intent is evidence-backed: every score carries the dated signals behind it.

Demandbase and Fokals side by side

Read the Demandbase column as a summary of the pages linked above, and the Fokals column as a summary of its data dictionary and methodology.

Other vendors to weigh

Each description comes from the vendor's own site, read on 4 October 2026.

• 6sense. 6sense presents intelligence for agentic GTM, built on its own signal data, with predictive models that, as its documentation describes, give each account an intent score and a buying stage. The guide to 6sense alternatives covers it.
• Bombora. Bombora calls itself a data company and not a platform, and delivers its Company Surge intent data, derived from a co-operative of publishers, brand sites and data providers, into the CRM, marketing automation and advertising tools a team already runs. See Bombora alternatives.
• ZoomInfo. ZoomInfo presents an AI platform for go-to-market teams built on contact and company data, and its Data-as-a-Service offering delivers that data into a CRM or a warehouse.
• HG Insights. HG Insights describes a revenue growth intelligence platform with firmographic, technographic, IT spend and intent data, delivered as software and as data for CRMs and other systems.

Fokals intent is built from what a company itself does in public, with the dated evidence attached, and company signals vs third-party intent data sets it beside intent built on behaviour.

Assembling the account record in your own stack

An account page in a platform answers three questions about the company: does the account fit, is it active, and what changed. In your own stack each answer is a dataset, joined on one company ID to the people your CRM already holds.

Match your CRM accounts to the Fokals company ID once, on website domain, and keep the key on the account. Then build the record each week, after the weekly scores are written.

-- accounts(account_id, company_id): CRM accounts matched once on website domain
with intent as (
  select company_id, score, surge, evidence
  from company_intent_weekly
  where week_start = :week
    and topic = 'crm'
),
stack as (
  select company_id, count(*) as tools_added
  from company_tech_events
  where category = 'technology'
    and change = 'added'
    and observed_at >= :from_day
  group by company_id
),
hiring as (
  select company_id, sum(new_postings) as new_postings
  from company_hiring_daily
  where day >= :from_day
  group by company_id
),
news as (
  select company_id, count(*) as announcements
  from company_news
  where at >= :from_day
  group by company_id
)
select
  a.account_id,
  i.score,
  i.surge,
  i.evidence,
  s.tools_added,
  h.new_postings,
  n.announcements
from accounts a
left join intent i on i.company_id = a.company_id
left join stack s  on s.company_id = a.company_id
left join hiring h on h.company_id = a.company_id
left join news n   on n.company_id = a.company_id
where a.company_id is not null;

The week parameter is the Monday of the last closed week, and the start day is 28 days before that week ends. The query filters on the CRM topic: use the topic that matches what you sell. An illustrative row for Acme Robotics, an invented company: a score of 64 with a surge, three tools added, 14 new postings and two announcements, with the evidence naming the dated signals behind the score.

Four properties of the record decide how to read it.

• A matched account with no row was quiet. A matched account with no intent row for a topic was quiet on that topic in that week. Count the accounts that drop out of the domain match separately, because an unmatched domain is not the same as a quiet company.
• The score is per topic. Intent Scores carries one row for each company, topic and week, so the record says what an account is active on. If you sell across several topics, show them side by side.
• A first observation is a baseline. A tool already in place when a website is first observed sets the baseline and writes no event, so the count of tools added holds adoptions and nothing else.
• Every announcement carries its date and its event types. Company News classifies company announcements and regulatory disclosures into 13 event types, so the count can be narrowed to the events that matter to you, such as a leadership change with the role concerned.

Then measure the record on your own pipeline. Mark an account as active in a week when it has a surge, or a score of 50 or more together with at least one change in the window, and compare the share of active and inactive accounts that open an opportunity within 60 days. Weekly rows are written once after the week closes and are never revised, so the test is point-in-time by construction. Each score names its evidence, so a rep or a model reviewer can open the source. The same columns become segments in building account-based marketing segments from company signals. The intent dataset page describes the scores, and the data dictionary defines every column used above.

Frequently asked questions

The queries and code on this page are examples to adapt. Test them in your own environment before you rely on them.

What this page says about the products it names was checked against their public documentation on 4 October 2026. Product and company names are trademarks of their owners. Fokals is not affiliated with them or endorsed by them.