10 Metrics to track for a more accurate revenue forecast

Ever delivered a forecast to your board only for it to prove… embarrassingly inaccurate?

Trust us, you don’t want to.

But if you want to deliver a revenue forecast you can actually rely on, it all comes back to tracking the right metrics.

At our recent Revenue Forecasting Summit, we sat down with two experts to nail down exactly what these metrics are, so you can get your forecast right the first time. (And avoid the embarrassment of missing the mark.)

Our experts:

• Bayley Fesler, Head of RevOps, Xactly
• Stephanie Schall, Platform Optimization Advisor, Forecasting

1 - Deal strength

Even when you know how to do a revenue forecast, you still need to arm yourself with knowledge of the metrics that'll guide you towards success.

And, according to Bayley Fesler, Head of RevOps at Xactly, the first question to ask when considering your data is: “Should this deal even be a part of the conversation?”

Meaning, should a given deal even be a part of your forecast?

To answer this question, score the strength of each deal and account. Make the scoring criteria objective, and start to tie deal strength to win rates.

The closer you can tie these metrics together, the better you’ll be able to predict how much revenue you’ll generate in a given quarter. Not only based on the quantity of deals in your pipeline and their projected values, but also the quality of the deals in your pipeline. This can drive forecast accuracy way higher.

Bayley recommends scoring deal strength according to the following:

1. Number of stakeholders: The more people involved in the buying process, the more complex it becomes. The more complex it becomes, the more likely it is to go wrong. This doesn’t necessarily mean a lower quality deal, but it can. Bayley advises being aware of the impact the number of stakeholders you’re dealing with has on win rates.
2. Stakeholder seniority: If you’re dealing with an executive-level stakeholder or decision-maker, you have that much more influence to close the deal quickly and cleanly. These make for higher-quality deals.
3. Time since last interaction: The less engaged your points of contact are, the colder the deal is getting. If you just spoke with them last week, or yesterday, the deal is likely of higher quality.
4. ICP match: A customer that doesn’t match your ICP is probably a poor fit for your product or service. It’s also unlikely that your teams have the internal know-how to close them as effectively as those that check all your usual boxes. This, of course, means a lower quality deal.

Thinking about resources and ROI, it doesn’t make sense to pursue low-quality deals. You need to be having the right conversations at the right times if you’re to maximize your revenue.

With this in mind, gauging the strength of the deal as early as possible once it enters the pipeline is critical to forecast accuracy.

2 - Total pipeline (coverage)

Assessing the quality of your deals as they come in is the first step.

But the second is to gauge the quantity.

Of course, you need to know how many deals you have in the pipeline at any given time.

But, while crucial, Bayley says just knowing the quantity of deals you have in the pipeline is not enough. You also need to know how realistic it is that you’ll close the deals in your pipeline.

This question of realism is what ties total pipeline to deal quality. You need the right deals in place in the pipeline, and enough of them, to maximize the likelihood that you can hit your target.

Stephanie Schall, Platform Optimization Advisor for Forecasting at Xactly, puts it like this: “You can have 10x pipeline, but if it’s not clean, and healthy, and filled with the right opportunities, you’re still not going to hit that number.”

This doesn’t just help you gauge the likelihood of you hitting your revenue target. It gives you critical feedback on what you should be doing differently next quarter.

Bayley says you should be sure you’re asking, “Where are we overstated? And, of the deals we’re bringing in that look great, what are we doing to make sure we get more that look like that?”

3 - The “commit” forecast

Your forecast should include one number that is not aspirational. This number, the “commit” forecast, should be deal-backed.

Think of it as a worst-case call. This is the number that, no matter what, you should be able to hit. And you need the data to back this call up.

Bayley says, “[The forecast call] should be conservative but realistic, knowing that you have additional deals in your pipeline.”

In part, this will be based on historical data: your past win rates for deals that exist in the pipeline going into a new quarter. But the commit call is always tied to specific deals that exist in your pipeline right now.

If one of these deals gets delayed, pushed into next quarter, or lost entirely, you need to know how this affects your forecast as a whole.

4 - In-period created and closed (IPCC)

This metric tracks the deals that don’t exist at the beginning of the quarter, but are likely to both enter the pipeline and close within the same quarter.

Your IPCC is hugely helpful for a couple of reasons.

First, deals that enter the pipeline and close within the same period are almost always essential for hitting revenue targets, which is “why you should always stay on top of those top-of-funnel efforts, and make sure everyone’s driving towards those pipeline targets… these are the things that will come to impact your forecast and ultimately your bookings targets.” - Bayley Fesler

Second, it reveals seasonality.

Here’s an example…

You might know that pipeline is always a little light at the start of Q2. But, you might also know that clients have always moved quickly in Q2. Lots of deals open and then close before the end of the quarter.

Armed with this knowledge, you can boost morale if reps feel despondent about their lack of pipeline. You can also show them, in black-and-white, what they’ve achieved in the past.

This is important because, as Stephanie highlights, “Sales reps get defeated sometimes. But if you know their conversion rate on pipeline from certain sources is always good, you can show them exactly where they can go to build their pipeline and get it closed in the same quarter. Then, they not only hit their number, but it sets the business up with new pipeline for future quarters as well.”

But remember, you shouldn’t count on your IPCC “because you don’t have visibility at the start of the quarter,” says Bayley. Your IPCC “shouldn’t be a part of your committed forecast.” But you should be aware of it at all times.

5 - Best-case call

So, you’ve got a worst-case forecast number, which is your Commit forecast.

You’ve also got a sense of the number of deals that usually enter and exit the pipeline within the same quarter, these are crucial, too.

But it’s also standard industry practice to forecast a best-case call.

Deals that fit into your best-case call typically have more unknowns associated with them. It’s harder to gauge their quality, or the likelihood they’ll close in a given quarter.

For that reason, while you don’t want to count them out entirely (they’re still in-pipeline deals, after all), you don’t feel confident, based on historical data, asserting that they will close this quarter.

Bayley walks us through what to think about:

• They might be outside our ICP.
• They might be verticals we don’t work with as often.
• For some other reason, we might suspect sales cycle time will be longer.
• It might be a big logo customer who’s worth the investment, but whose procurement processes we’re not as familiar with.

Whatever it is, there are some real intangibles around the deal and its outcome.

You’ll use these deals to create a best-case call. Crucially, says Bayley, this is an “educated” forecast. “There is a path to closing this deal – maybe even a path to making it a committed deal. It’s just not committed yet.”

Stephanie ties this back to the first metric we listed: deal quality.

“And that’s where being able to understand the strengths and weaknesses of the deal, and the ICP, is so important: so you can automate this process, too. Not only having input on your own, but understanding which deals fall into this category, so you can understand exactly what that best case number should be.” - Stephanie Schall

6 - Risks and pipeline gaps

As we mentioned in our discussion of the practical challenges of revenue forecasting, if you want a more accurate forecast, you should combine multiple forecasts.

The easiest way for most businesses to do this is to combine bottom-up and top-down approaches. In other words, you have each of your reps forecast their own booked revenue for the quarter, and you have sales leaders forecast their own number.

The discrepancies between these numbers are usually telling. They reveal hidden risks and gaps in your forecast, as Bayley explains:

“We have some reps who are very excited about some of their deals. They might be committing a lot of their pipeline, but then their coaches and managers might not be committing the deal.” When this happens, you want to understand why the discrepancy exists.

These are also important coaching conversations for sales leaders to have with their reps. Understanding them won’t just help you improve forecasts over time, it’ll also make your teams understand what really wins deals. Managers can understand exactly what makes reps feel so confident, while reps can learn more about the likelihood of particular accounts closing.

7 - Potential pull-forward deals

As the quarter wears on, circumstances change. The deal that once seemed like a sure-thing now seems impossible to close.

What do you do?

At some point, you reach an inflection point. The probability of a previously committed or best-case deal closing in this quarter is now lower than that of another deal, originally slated to close next quarter.

So look for those deals which are going better than expected. Because at this point, the ROI shifts, and reps should spend their time pursuing the highest probability opportunities.

Stephanie brings us back to focusing on deal quality, “Because of scoring, you can identify a low-risk opportunity that has momentum that you can pull forward.”

However, it’s crucial that you’re looking for these deals before need them. This is time-sensitive. If you want to be reactive enough, as soon as a deal slips, you need your reps to be able to switch their attention to it immediately.

But Bayley emphasizes, “Hope is not a strategy. This is not wishful thinking. Is it realistic to think, if you get things right, if the on-site or the demo goes well, that you could get through the paperwork in time?” If not, then the deal should not be a part of the pull-forward call.

8 - The AI projection

So, how can you use AI to improve your outcomes?

The first use case is as a sense check for each of your forecast numbers. Generate additional predictions using AI, and line these numbers up alongside your own forecast projections.

“[AI is] great in keeping us real, and keeping us honest. If there’s a deal that has been kept around too long, [the AI] won’t include it in its forecast.”

Crucially, this is just a check. And Stephanie highlights an unusual benefit that stems from competitive, human nature: “Leadership sometimes says, ‘I want to prove this wrong, because I think this deal can close.’” That burst of enthusiasm to close a deal when you think the AI is betting against you can, in measurable terms, lead to you closing more deals than you otherwise would have.

At the same time, the AI will keep you honest, and force you to reflect on the deals you’re committing to. Alongside the discrepancies between deals your reps and your sales leaders are committing to, an AI gut check on each number usefully highlights other risks in your forecast.

“Just because the AI is calling a deal out doesn’t mean that it can’t win. But it forces you to ask, ‘What are we missing?’” - Stephanie Schall

9 - Past performance tied to current pipeline

Your AI projection isn’t the only sense check you should have in place to gauge whether your forecast is realistic. You should also be backing up your forecast numbers with historical data.

Some historical metrics Bayley suggests you look at:

• Opportunity aging
• Cycle time
• Win rates for industries
• Win rates for your segments
• How often are you missing these win rates?

Historical data helps you confirm that your calls are realistic. The basic premise? “It’s happened before, so it can happen again.”

Remember, once you’re tracking the right things, it’s all about sense checking your numbers and keeping an eye out for human errors, slipping deals, and risks to your pipeline that could require you to take action or amend a number.

10. Deal velocity & sales efficiency

The last thing Stephanie and Bayley suggest you look at to unlock a more accurate sales forecast is deal velocity.

Look at the number of days you’re spending in each stage of the opportunity. Where you’re spending more time in a particular deal stage than you’d like, ask “Why?”

What is it you’re doing in those stages? Why do they continually get stuck? There’s almost always something you and your team could be doing more efficiently. There are processes you can automate, tools at your disposal you could leverage, an AI tool that you could begin using…

This doesn’t just improve rep performance. It improves the accuracy of your forecasts. Time spent stuck in a particular deal stage introduces elements of uncertainty that confound your forecast. 

When you stamp these out as much as possible, you effectively minimize uncertainty, boosting the accuracy of your forecast.