Heap
Analytics
Heap auto-captures every click and session across a product without any manual tagging by a team. Revenue Labs reads that record and turns it into account-level signal, and what a user did in the product joins everything else already on file for the account.
Website
Adoption·8 adoption reads this week
Reading Ravensmoor Analytics… ›
TriggerProduct usage · Ravensmoor Analytics - reporting workspace down this week · Same week as last quarter's seasonal dip
Deploy agentDeploying Adoption agent on the account
Use skillLoading skill · Adoption Analysis · Value Realisation Assessment · Customer Health Assessment
Reference memoryReading memory · Adoption · Products · Customer Outcomes
ReasoningRavensmoor Analytics' usage dipped the same week it did last quarter - seasonal on its own, except this time the stakeholder who drove it, Wren Halloway, left the company two weeks ago; this one gets flagged, last quarter's didn't
ActionCompose adoption read → surface inside Customer Meeting Preparation ahead of the call
✓Read in 6 seconds ›
Surfaces inCustomer Meeting PreparationviaSlackTeams
Revenue LabsAPP1:37 PM
LIVE
CUSTOMER MEETING PREP: Ravensmoor Analytics | Check-in Call
WHAT'S CHANGED
Reporting workspace usage dipped the same week it did last quarter, seasonal on its own
Wren Halloway, who drove that usage, left the company two weeks ago
STAKEHOLDERS
Gideon Park · Ops Director · [Primary contact]
ADOPTION & VALUEADOPTION
4 use cases assessed this cycle · 1 gap flagged for the call
Reporting workspace behind expected pace since Wren Halloway left; confirm who owns it now
RECOMMENDED DISCUSSION
Confirm the new workspace owner and reset the adoption pace with Gideon Park
Join MeetingView AccountView Adoption Detail
The tool alone > AI bolted on > AI-native
What changes when Heap feeds a system that learns
Three jobs Heap 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
Autocaptured product events
Clicks, sessions, and events recorded automatically.
Heap autocaptures interactions and organises them as accounts, users, sessions, page views, and events. Product analysts still decide what matters commercially.
Illuminate surfaces key behaviour.
Illuminate finds patterns inside Heap's behavioural data. The finding does not attach the signal to a company or deal outside the analytics view.
Product behaviour becomes account state.
Event and session evidence joins account history, giving calls, tickets, and stages one product signal.
Session recordings
A session can be replayed around the moment of friction.
Session replay shows clicks, inputs, errors, and the path a user took. A product manager still watches the relevant session and decides what it means.
Sense summarises analytics questions.
Heap answers help explore Heap data, but Heap does not tell the account owner what changed or connect the replay to a deal outcome.
Session evidence reaches the deal.
Repeated errors or abandoned paths join the account context, where every capability can read the product signal.
Funnels and conversion paths
Funnels show where users drop or convert.
Heap funnels show conversion paths and can link a drop-off to a replay. Product teams still compare that behaviour with the commercial outcome.
Illuminate suggests important events.
Heap suggestions remain a Heap insight. They do not test the event against renewal, expansion, or loss outcomes.
Path signals follow outcomes.
Closed outcomes show which product paths preceded them. Future account reviews use the patterns the system learned.
Runs on it
Capabilities that act on connected evidence
Customer Success
Adoption
Active
›
Adoption gaps are named by use case
Usage and stakeholder behaviour are compared with the customer's goals and use case.
↑
Early usage is read against its stage
Lifecycle requirements separate a normal ramp from adoption that is already slipping.
−
The QBR starts with an adoption picture
Use-case and stakeholder gaps, with likely causes, are assembled before the meeting.
+
Usage dips are weighed against the customer
The customer's adoption pattern and goals distinguish disengagement from a familiar lull.
The CSM receives traceable adoption gaps so effort reaches customers falling short.
Customer Success
Customer Health
Active
›
The health read stays live
Customer Health Memory is applied to Customer State as new evidence arrives.
↑
Conflicting signals are weighed together
Product, support and relationship evidence explains a move from Healthy to Watch.
−
The current read is ready for review
Health, evidence and confidence are attached to the account before the CSM prepares.
+
Managers see only changed exceptions
Managers see which accounts changed and why instead of scanning the whole base.
Reconciled health evidence lowers churn and reduces manual portfolio inspection.
Customer Success
Expansion Identification
Active
›
The candidate starts with an evidenced thesis.
It checks the use case against expansion, product and value logic.
↑
The threshold is checked against fit and goals.
It tests product fit, customer goals and commercial logic.
−
The stakeholder map shows what changed.
It shows whether the new person adds authority, budget or urgency.
+
The review opens with ranked candidates.
Each candidate carries evidence and confidence for CSM review.
Humans decide whether to introduce the commercial conversation.
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