What Can You Use Salesforce Custom Forecasting Data For?
Salesforce Custom Forecasting Data answers one question: what numbers, other than quota, should show up next to a forecast?
Most teams, if asked directly, can rattle off four or five. They’re the numbers that sit in a spreadsheet because “Salesforce couldn’t hold them” — and because they lived in a spreadsheet, they never quite made it into the forecast conversation.
Here’s what teams actually put in Custom Forecasting Data once they have a practical way to manage it.
Stretch goals
The most common use. Quota is the floor; the stretch is the reach. Leadership commits against the stretch at SKO and then watches it disappear from daily view because it wasn’t in Salesforce.
Loaded as Custom Forecasting Data, the stretch number shows up on the forecast page next to quota. Every attainment calculation in Workbench, every Oonu answer, every deal review can reference it. “Who’s above stretch?” becomes a real question with a real answer.
Previous year actuals
Last year’s booked revenue by period. It’s the single most-cited comparison number in any forecast conversation — are we ahead of where we were last year at this point? — and it almost never lives in Salesforce natively.
Load it as a reference field and the question stops requiring a spreadsheet. Managers see current-period forecast alongside the same period a year ago. Reforecasts get grounded in actual history instead of vibes.
New logo targets
Not every number belongs on quota. Sales leaders often carry a separate commitment for new business — new logo ARR, new customer count, net-new bookings — that’s tracked alongside, but not inside, the primary quota.
Custom Forecasting Data lets you set a new-logo target on the New Business forecast type while keeping Opportunity Revenue clean. Two targets, one hierarchy, no spreadsheet reconciliation.
Finance’s plan or budget
The forecast number sales is committing to and the plan number finance is carrying are almost never the same. The sales forecast is what the team believes. The plan is what the business is spending against.
Load the plan as Custom Forecasting Data. Now every forecast call can show both: sales says $4.2M, plan says $4.5M, gap is $300K. The conversation that used to require a CFO to pull up a separate tab happens inside the forecast.
Ramp plans for new hires
A rep who started two months ago doesn’t owe full quota in Q1. But their full-quota number is still what’s loaded in Salesforce. The ramped number — the one you’re actually expecting — lives somewhere else.
Custom Forecasting Data can hold the ramped expectation per period. When a manager reviews that rep’s forecast, the relevant target (the ramped one) is right there next to the quota. Performance conversations stay honest.
Capacity-based targets
For teams that forecast bottom-up from capacity assumptions — number of reps × average deal size × close rate — the derived capacity target is another number worth seeing on the forecast page. Load it once, watch it move as the assumptions change.
Partner-sourced or channel goals
Direct sellers have a direct target. Partner-sourced goals are usually tracked separately and never show up in the forecast. Loaded as Custom Forecasting Data, they can — either as a standalone column or filtered into the forecast type that matches partner-driven revenue.
Pacing benchmarks
How much should we have closed by now? What’s the historical close rate at this point in the quarter? These are the “are we on track?” numbers that used to live in a slide deck. Load them per period as reference data and they show up on the forecast page as a pacing column.
Useful variant: the average of the last three years’ closed revenue by month. Instant baseline against which the current pace is obviously ahead, behind, or roughly where it should be.
A calculated column you can’t live without
The reference-data side gets the attention, but calculated columns are part of Custom Forecasting Data too. A few that show up often:
- Gap to stretch —
Stretch - Forecast. Visible tension, every week. - Days to close — the average time from current stage to closed-won for deals in pipeline.
- Commit coverage —
Pipeline / Commitfor a quick read on whether the commit is supported.
Salesforce ships Gap to Quota and Pipe Coverage by default. Everything else is up to you, up to five columns per forecast type.
The pattern
Most teams end up with a short list — maybe three to six fields — that answer the questions they actually get asked in forecast calls. The list is different for every team, but it usually includes at least:
- A stretch target
- A historical comparison (previous year)
- A plan or budget
- A pacing benchmark
Once those four numbers are visible on the forecast page, the conversation changes. It stops being “what does sales think” and starts being “where are we against the several things we’re being measured on.”
What it takes to actually use this
Salesforce gives you the data model — the Forecasting Custom Data object and the column structure. What it doesn’t give you is a good way to load and edit the data. The documented path is Data Loader with a CSV keyed on User ID and Forecast Type ID. That works once. It doesn’t work every week.
Akoonu’s Custom Data Manager is the editor that makes it practical to keep these numbers current. Inline editing, multi-select bulk updates, guided import from Excel without User IDs, fiscal-year copy. Same muscle memory as Quota Manager, applied to any number you want on the forecast page.
If you’ve got a list of numbers living in a spreadsheet because Salesforce “couldn’t hold them,” they can. Schedule a demo and we’ll show you what your forecast looks like once they do.
