Sales Forecast

A sales forecast is an estimate of how much revenue your business will generate over a defined future period - typically the next 30, 60, or 90 days. It draws on the value of quotes currently in progress, your historical win rate, and any known repeat orders or contracts. For project-based businesses, a reliable forecast is not just a planning tool: it drives decisions about when to take on new jobs, whether to bring in extra capacity, and whether to hold off on large materials purchases. Without one, those decisions are made on instinct rather than data.

How to Build a Simple Sales Forecast

For most small to medium-sized businesses (SMBs), a working forecast combines two inputs. The first is pipeline-based: take the total value of all open quotes, then apply your typical win rate. If you have £80,000 of open quotes and historically win 35% of them, your pipeline contribution to this period's revenue is £28,000. The second input is historical trend: review the same period in the previous year and adjust for known changes in team size, seasonal patterns, or newly won contracts.

Update the forecast weekly rather than monthly. Companies tracking their pipeline on a weekly cadence achieve 87% forecast accuracy on average, compared to 52% for those reviewing it irregularly (Digital Bloom, 2025). The difference is not access to better data - it is the discipline of updating the forecast before it drifts out of date. A monthly review leaves three to four weeks for the gap between projection and reality to compound.

For a simple format, use three columns: revenue source (pipeline, repeat orders, confirmed contracts), projected value, and probability. Multiply value by probability to get the weighted forecast. Revisit it at the same time each week.

Where Sales Forecasts Break Down

The most common failure is treating the full quote pipeline as reliable revenue without applying a realistic win rate. A pipeline of speculative enquiries - where no budget was confirmed and no decision timeline was set - inflates the forecast and leads to over-committing on capacity or materials.

The second failure is ignoring repeat orders. For many project-based businesses, 40-60% of monthly revenue comes from returning accounts that have not yet had a formal quote raised. Because they do not appear in the quote pipeline, they are invisible to the forecast - and the month falls short without an obvious explanation.

The fix for both: track active quotes and expected repeat orders as two separate lines in your forecast. For repeat accounts, use the historical average order value and adjust for any known changes to that customer's buying patterns.

Zigaflow's Quotes and Leads modules give you a live view of open quotes and their total value, making it straightforward to calculate the pipeline-based half of your forecast. Syncing to Xero, QuickBooks, or FreeAgent lets you compare forecast figures against actual revenue at period close.