Account Intelligence

Build a dossier in three steps

Open Account Intelligence, select a connected DataHub dataset, and run the analysis — no setup beyond a quick column mapping. Choose the time period you care about (30, 60, or 90 days, 6 months, a year, or all time) and the engine pulls the records, computes the metrics, and composes the insights for every account.

• Select a dataset and map the columns it should use — account ID, account name, revenue, last activity
• Pick a time period to focus the analysis, from the last 30 days to all time
• Run Analysis computes metrics and composes insights across every record in range

Link the same customer across datasets

Accounts rarely live in one place. A linking column connects the same customer across datasets — CRM, billing, engagement — so the dossier merges everything into one operational view instead of fragmented snapshots. Search for any account by name, ID, or email and select it to generate its dossier.

Read the intelligence brief

Each dossier opens with an AI-written intelligence brief — a concise narrative of how the account is doing — backed by a snapshot of key metrics. From there it breaks out what matters for the team:

• Risk Signals — churn risk and behavior shifts that suggest the account needs intervention
• Opportunities — expansion and growth potential detected from account-level patterns
• Recommended Actions — next best actions for the account team, plus an activity timeline and the distributions behind the numbers

Share it and act on it

Export the dossier to share with the account team, or clear results and run a different account or time window. Because insights are AI-generated, the module reminds you to verify important figures before acting. When you need custom KPI frameworks or full drill-down beyond the dossier, it points you to KPI Analytics or Business Intelligence.

Best practices

• Map the linking column carefully — it's what ties the same customer together across CRM, billing, and engagement data
• Start with a 90-day window for a meaningful balance of signal and recency, then widen to all time for long-term accounts
• Use the revenue and last-activity mappings so risk and opportunity scoring has the context it needs
• Verify AI-generated figures against the source data before acting on a recommendation

Next steps

That completes the Automation track. Next, the Analytics track starts with Business Intelligence — full drag-and-drop analysis on everything you've connected.