These two charts live under the Analytics page:
Analytics > Focus on High Urgency Accounts
Analytics > Uncover White Space Opportunities
They give you a quick way to spot which accounts need attention, and why. This article walks through what each chart measures, how to read it, and what to do about an account depending on where it lands.
Note: The guidance below reflects the out-of-the-box experience. If your organization has a CRM integration connected, this data can be further enriched, so check with your enablement team if you're not sure which version you're seeing.
Viewing the analytics charts
Each chart's View report button takes you to the full, account-level detail behind that chart: the underlying list of accounts, their individual scores, and the signals driving them. Use the chart to spot the pattern, and the report to drill into the specific accounts and figure out next steps.
Focus on High Urgency Accounts
This chart plots your accounts by Propensity to buy (x-axis) against Active days (y-axis).
What the axes measure
Propensity to buy: a 0 to 5 score reflecting how ready an account looks to buy right now, based on the account signals Databook has surfaced for it (things like buying signals, strategic priorities, financial case for change, and other account intelligence).
Active days: how many days the account has shown activity in Databook, for example engagement with shared content or account materials. Higher on the y-axis means the account has been actively worked more recently and more often.
The time window for active days can be adjusted and is as follows: Last 30/60/90 days, Last 12 months, and Year to date. Cumulative all-time versus a rolling window changes what "high urgency" means.
How to read the clusters
Top right (high propensity, high active days): These are your best-worked, best-timed accounts: they're genuinely ready to buy, and they're being actively engaged.
Bottom right (high propensity, low active days): This is the cluster to watch. These accounts look ready to buy, but there's little recent activity against them.
Top left (low propensity, high active days): Another cluster to watch. This indicates time being spent on accounts that aren't showing strong buying signals, regardless of activity level.
Bottom left (low propensity, low active days): Accounts in this cluster are the ones that ideally need to be deprioritized.
What to do about it?
An account with high propensity and low active days is a hot account going cold, and it needs re-engagement. It's worth figuring out why the account has gone quiet: is it a stalled deal, a deprioritized account, or one that's simply fallen off the radar?
Uncover White Space Opportunities
This chart plots the same Propensity to buy on the x-axis, but pairs it with # Strong use cases on the y-axis.
What the axes measure?
Propensity to buy: the same 0 to 5 score used in the chart above.
# Strong use cases: the number of well-supported use cases Databook has identified for that account. A higher number means the account has more validated angles for your product or solution to be relevant.
Similar to Active days, the time window for this can be adjusted and is as follows: Last 30/60/90 days, Last 12 months, and Year to date. In the same way, cumulative all-time versus a rolling window changes what "high urgency" means.
How to read the clusters?
Top right (high propensity, many use cases): Accounts that are both ready to buy and have a rich set of relevant use cases mapped: strong, well-rounded opportunities.
Bottom right (high propensity, few use cases): This is your white space. The account is showing strong buying signals, but only a narrow slice of how you could help them has been identified so far.
Top left (low propensity, many use cases): Lower priority, regardless of the multiple relevant use cases.
Bottom left (low propensity): Accounts in this cluster are the ones that ideally need to be deprioritized.
What to do about it?
An account with high propensity and few strong use cases is an opportunity to expand the use case conversation with the account: what else is this account dealing with that your solution could address?
Using these charts in practice
Treat these charts as a starting point, whether you're reviewing your own accounts or someone else's, not a replacement for digging in.
Before a 1:1 or pipeline review: Pull up both charts and look for accounts sitting in the bottom right of either one. Those are your highest-leverage accounts to dig into.
When you dig in: Ask why a specific account landed where it did. Bottom right on "Focus on High Urgency Accounts" points to re-engagement plans. Bottom right on "Uncover White Space Opportunities" points to what other use cases might apply.
As a pattern, not a one-off: If accounts consistently land in the bottom right of either chart, whether across your own book of business or someone else's, that's a signal for a broader theme (re-engagement discipline or use case discovery) rather than a single account fix.
A useful mental model: Some teams find it helpful to think of the four corners of a propensity-vs-activity chart as rough zones: accounts you're working well, accounts you're neglecting despite strong signals, accounts worth double-checking for fit, and accounts that are rightly deprioritized. Databook's charts don't label these zones explicitly, but the same logic applies: read the quadrant an account sits in, then decide the action.
For managers and enablement teams
Introduce these two charts alongside the existing Tracking Adoption of Your Assets article: the pattern for reading Account View and Seller View data carries over here.
When training your team, walk through a few live examples from your own org's Analytics page rather than relying on hypotheticals. Actual account names and clusters will land better than an abstract explanation.
Set expectations that these charts flag where to look, not a verdict on the account owner. The follow-up conversation with the account is what determines the real story.