Proposal Analytics (Data Lab)

Aggregated data across all proposals, what really works?

Proposal analytics is the aggregated analysis of all your sent proposals together, as opposed to tracking a single proposal. In Proposal Expert this happens in Data Lab. There you see win rates per template, per sales rep and per period, the average reading time and engagement per section, and the points where readers consistently drop off. The engagement score from 0 to 100 that every view receives is averaged and compared here. This way you build your proposals on evidence instead of assumptions.

How does proposal analytics work in practice?

Data Lab collects the tracking data from every shared proposal and sets it against the outcome: won, lost or still open. You pick a period and filter by template, team member or client type. The reports show win rate, average time from sent to signed, and engagement per section on the 0 to 100 scale. From every figure you drill through to the underlying proposals. With your own BI stack, you pull the same data through the REST API.

What do you get out of it?

You see which proposal structure leads to a signature most often, and which sections were barely read in lost deals. That lets you improve templates on facts instead of on the opinion of the loudest colleague. Sales managers see win rate and average engagement score per rep, which is a more concrete starting point for coaching. In a pricing experiment you compare two variants on reading time at the pricing section and on conversion.

What should you watch for?

Aggregates only mean something with enough volume. With ten proposals a difference in win rate is usually chance, with a hundred it becomes a pattern. Compare like with like: a template for small jobs against a template for tenders says little. Mark the status of proposals consistently as won or lost, otherwise the percentages are off. And remember that engagement is a signal, not a cause: a well-read pricing section can also mean the price was too high.

Tracking an individual proposal is useful. Aggregated patterns across hundreds of proposals are where it gets really interesting.

Win rate per template

Which template structure converts best? Which sections correlate with closing the deal?

Drop-off analysis

Where do clients stop reading? Aggregated across all your proposals, per section.

Cohort analysis

See how proposal performance changes over time and per sales rep.

API access for your own BI

REST API for pulling proposal and engagement data into your own dashboarding stack.

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