Investor engagement analytics

Engagement analytics show the deal team which investors are reviewing the data room, how deeply, and which files attract the most attention. The outcome: follow-up driven by observed investor intent rather than guesswork.

Analytics are data-room-scoped and deal-team only. Investors never see analytics or audit logs. A registered or guest investor cannot view their own engagement score or the file heatmap, and receives no indication that the deal team can see how long they spent on any document. The investor side of the product is deliberately silent on this.

Scope

Engagement analytics appear on the deal team's activity view, scoped to the currently selected data room. Every figure below is a view onto a single data room. Switching the active data room changes the numbers to that deal.

What analytics show

Analytics are organised into four groups, each answering a distinct question.

Investor scoreboard. A per-investor row showing document views, distinct files touched, questions asked, sessions, and a single engagement score that rolls these up. Sort by score to identify the highest-intent investors to contact first.

Document heatmap. The top files ranked by the number of distinct investors who have opened them. A file near the top is driving diligence; a file no one has opened may be one investors cannot find.

Seven-day timeline. Investor activity bucketed by hour over the last week. Activity patterns — such as a burst the night before a call — convey context that a flat total cannot.

Summary KPIs. Headline numbers: active investor count, average files touched per investor, files no one has viewed, and the most and least active investors. This is the at-a-glance state of the deal's diligence.

Engagement score

The score is a single number per investor:

views × 1  +  unique files × 3  +  Q&A × 5  +  sessions × 2

The weighting is deliberate. A raw view is the cheapest signal and counts least. Touching a distinct file is worth more than re-opening the same one, because breadth of review is a stronger intent signal than depth on a single document. A question carries the highest weight: an investor who asks is engaged enough to want an answer, the strongest intent signal in the data room. Sessions sit in the middle — returning is meaningful, but less so than asking.

The score measures intent, not raw activity. This is why an investor who asked two pointed questions can outrank one who clicked through forty pages and asked nothing.

Session definition

A session is bounded by inactivity: thirty minutes of inactivity ends a session, and the next activity starts a new one. A single long review afternoon counts as one session; a brief morning check-in and a deep evening read on the same day count as two. Session count is a proxy for how many times an investor returned to the deal — a signal complementary to total time spent.

Drilling into one investor

Each row in the investor list has an activity link to a filtered view: the engagement data narrowed to that one investor. Use it when the scoreboard flags someone and you need to see exactly which files they read and when, rather than the aggregate.

Freshness

Analytics are served from a server-side cache that refreshes every thirty minutes. They are near-real-time, not live to the second: an investor who just opened a document appears within the next refresh window. For prioritising follow-up and gauging readiness, thirty-minute freshness keeps the view responsive without recomputing a deal's full engagement history on every page load.

Acting on the signal

Three patterns to watch for:

• Cold investors. An invited investor whose score barely moves is a re-engagement candidate — a nudge, a different document, or a conversation.
• Friction. High views and files but zero questions can indicate confusion rather than conviction. Activity with no Q&A warrants a proactive check-in.
• Readiness. A cluster of investors with rising scores and recent questions signals a warming deal — the moment for next-stage outreach.