System/Integrations/Integration
Demandbase
Intent & enrichment
Account intent stops sitting in a separate ABM dashboard nobody checks daily. Demandbase tracks that intent alongside firmographic data, and Revenue Labs reads it into account state, so market signal shows up next to the CRM activity a rep already sees.
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From source record to operating state
01 | The tool on its own
Intent tracks accounts researching topics.
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02 | With AI bolted on
Intent scoring uses Demandbase data.
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03 | A system that learns
Intent sits with account evidence.
The tool alone > AI bolted on > AI-native
What changes when Demandbase feeds a system that learns
Three jobs Demandbase already does, and what each becomes when its evidence joins live company, contact and deal state.
01 | The tool on its own
02 | With AI bolted on
03 | AI-native
Intent and keyword sets
Intent tracks accounts researching topics.
Demandbase uses account lists, keywords, and activity to show which companies may be interested. A marketer still sets the keyword set, checks context, and decides whether it is relevant.
Intent scoring uses Demandbase data.
Demandbase uses AI and language processing to detect context and relative activity. The score remains a Demandbase view without the full deal or outcome trace.
Intent sits with account evidence.
Demandbase topic activity sits with CRM, conversation, and contact evidence in the account state.
Buying stages and journeys
Buying stages organise account activity.
Keyword sets, journey stages, and engagement points give teams a way to group account movement. The team still chooses thresholds and reconciles the view with sales reality.
Buying-stage mapping stays in Demandbase.
The model categorises accounts from Demandbase data, but the account categories lack the cross-tool evidence behind a deal and leave reasoning elsewhere unchanged.
Stage changes redirect the next step.
Account-stage change can move the relevant capability from research to preparation or action.
Audiences and campaigns
Audience tools activate account intent.
Demandbase can build audiences and campaigns from account intent. A marketer still selects the audience, message, and destination and checks what happened afterwards.
Audience recommendations stay in Demandbase.
Demandbase's recommendation uses its signals alone, with no learning from the campaign's pipeline outcome or view of another tool's evidence.
Selection learns from deal results.
After each deal result, the system updates which intent and audience patterns should shape the next selection.
Runs on it
Capabilities that act on connected evidence
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