Sales forecast review checklist
A sales forecast review checklist for B2B product sellers: check the data, each deal, repeat orders, coverage and assumptions before you commit a number.
By the PromptLab team31 October 20265 min read
A forecast is a promise you make to the rest of the business. Production plans, purchasing and cash all lean on it. When a forecast misses, the maths is rarely the problem. The usual causes are deals in the wrong stage, close dates that nobody has touched and repeat orders assumed rather than checked.
Run this checklist before you send the number. It suits sales leaders at manufacturers and distributors, and works for a month or a quarter. For how to build a forecast, read how to forecast sales and what is sales forecasting. For the deal-by-deal meeting, use the pipeline review checklist.
Check the data before the maths
A forecast built on stale data is only a guess with decimals.
Data hygiene
Test the deals that carry the number
You do not need to review all deals. Review the biggest and the ones closest to the line.
Deal checks
Check the repeat business
For many product sellers, the base of the forecast is customers who reorder, not new deals.
Repeat orders
Test the total
Check the number against some simple tests before you present it.
Totals and coverage
Say your open pipeline for the quarter is $600,000 against a $200,000 target. Coverage is 3x. It looks safe until you find that $350,000 of it is two deals with no next step. The real coverage is closer to 1.25x ($250,000 divided by $200,000), and the forecast should say so.
Agree the number and the actions
A forecast review should end with decisions, not only a figure.
Close the review
The items people skip
- Close dates in the past. They are the clearest sign of stale data.
- Comparing with last time. Without this, you never learn whether your forecast is too hopeful or too careful.
- Double counting. A repeat customer's order appears as a deal and as run-rate.
- The range. One number looks precise and hides how uncertain it is.
How PromptLab helps
Keep every deal in your one pipeline with a stage, owner, estimated value and next follow-up date. Add a custom date field for the expected close date, and save a view of open deals whose close date is before today. PromptLab gives you reports and dashboards on pipeline and revenue, including pipeline by stage and movement over time, and sales orders on the account show the repeat business. The forecast method stays yours: PromptLab's part is the data. Loss reasons are required on lost deals, so you can see why deals dropped out. See the dashboards reference.
Frequently asked questions
What should I check in a sales forecast review?
Check data hygiene first: owners, stages, values and close dates. Then review the biggest deals, look at repeat orders from regular accounts, test the total against pipeline coverage and last period's result, and agree the actions for each risk.
How often should I review the sales forecast?
Many teams review weekly or fortnightly, with a fuller check at the start of each month or quarter. The right rhythm depends on your sales cycle. A longer cycle can be reviewed less often than short repeat orders.
How do I know if my forecast is accurate?
Compare each forecast with what actually closed, period by period. If you are consistently over or under, change your stage weights or how you judge close dates. Keep the comparison, as it is the only honest test.
What is a good pipeline coverage ratio?
It depends on your win rate. If you win about one deal in three, you need roughly three times the target in the pipeline. Use your own history to set the ratio, and count only deals that are real and have a next step.
Why do forecasts go wrong?
Usually because of stale data: deals in the wrong stage, close dates in the past and repeat orders that did not arrive. Big single deals, optimistic weights and double counting add to it. A regular review catches many of these.