Account opportunity finder

Find the next deal hiding in your accounts.

Whitespace scores every account-and-product combination a customer doesn’t own yet — using what similar customers bought, what tends to be bought together, fit, and engagement — then ranks the plays and says why.

Upload accounts CSV Showing 40 fictional accounts · files stay in your browser

Try it: filter to Healthcare, then raise the Product affinity weight and watch the top plays reshuffle.

Whitespace value

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Open plays

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High-propensity plays

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score 70 or above

Avg. products / account

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Top plays Ranked by propensity × estimated deal size

Whitespace map

Already ownsPropensity to buy, low → high

What gets bought togetherLift: how much owning the row raises the odds of owning the column

Whitespace by productEstimated value of open plays

Scoring model

Peer adoption

Share of other accounts in the same industry that already own the product. If most hospitals bought it, the next hospital probably needs it too.

Product affinity

Lift from co-ownership across the whole base: P(product | owns X) ÷ P(product). Uses the strongest signal among products the account already owns.

Size & fit

Log-scaled employee count, so bigger organizations score higher without drowning out everyone else.

Engagement

Engagement score decayed by days since the last touch. A warm account converts faster than a cold one.

CSV columns: account, industry, region, employees, engagement, last_touch_days plus one 0/1 column per product (data_platform, ai_assistants, automation, security, hybrid_cloud, observability). Deal sizes use illustrative list prices scaled by company size.