System/Integrations/Integration
Amplitude
Analytics
A feature a buyer keeps opening every week is a signal worth acting on well before the renewal conversation starts. Amplitude records product events screen by screen, and Revenue Labs reads that usage and turns it into account-level signal for the deal.
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From source record to operating state
01 | The tool on its own
Product events, users, and accounts recorded together.
↓
02 | With AI bolted on
Global Agent answers product questions.
↓
03 | A system that learns
Usage enters account state.
The tool alone > AI bolted on > AI-native
What changes when Amplitude feeds a system that learns
Three jobs Amplitude 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
Product event capture
Product events, users, and accounts recorded together.
Amplitude records product events, users, and accounts. Analysts still define the tracking plan and choose which events answer a business question.
Global Agent answers product questions.
An Amplitude answer is built from Amplitude data and remains an analytics result. The answer does not join the call, CRM, or renewal outcome.
Usage enters account state.
Events roll up to the right account. Calls, tickets, and stages can then read the same product state.
Funnel and cohort analysis
Funnels and cohorts show where users convert.
Funnels and cohorts show where users convert, drop, or return. Analysts still choose the steps, segment, and interpretation.
Dashboard Agent builds charts and KPIs.
The dashboard stays inside Amplitude. It offers no account context for the next sales action.
Its path becomes account evidence.
When conversion on a feature path falls, account evidence sits beside the deal context needed to judge the risk.
Retention and outcomes
Retention reports show whether users come back.
Retention reports show whether users return over time. Teams still connect product retention to the commercial outcome by hand.
AI investigates follow-up questions.
It can explore product behaviour, but its analysis is not a learning loop for renewals or expansions.
Renewals teach the usage signal.
Renewals, expansions, and losses show which usage patterns mattered. The system updates what it watches for next.
Runs on it
Capabilities that act on connected evidence
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