How to proactively diagnose deal risks in your pipeline and increase efficiency

In the last few years, only 23% of sales reps had enough pipeline to meet their quotas. It’s not surprising then that many sales managers and leaders spend hours every week inspecting their teams’ forecasts to uncover what’s at risk, or worse, not real.

As a manager, you’ve likely wondered what’s going wrong, what’s still on track, and how to spot risks before deals slip away. Without full visibility into your pipeline, it’s difficult to see the true indicators of deal health. Instead, you often have to rely on reps’ subjective assessments based on emotion or surface-level signals rather than data-driven insights.

With an increase in distributed teams, there’s no way managers can know every deal inside and out to forecast accurately (let alone which reps need help where), and trying to do that leads to teams feeling micromanaged instead of supported.

What if you had the pipeline visibility to keep deals on track? And what if you could use data to diagnose risks and guide your team to higher close rates?

In this blog, we’ll look at how to:

• Monitor the right buying signals to take the right action to move the right deals forward
• Unlock improvements to sales execution
• Build proven sales playbooks that quickly up-level reps for predictable revenue results

Understand deal health signals

Completing a successful sale means getting many steps right. Skipped or forgotten steps at any stage of the deal reduce your likelihood of closing.

Just do some quick math. Eight reps with 17 deals each in a six-stage sales cycle with two exit criteria per stage results in 544 specific deal attributes to manage. That’s simply not feasible.

Deals generally fall into one of three categories:

• Deals that will close
• Deals that, if you put more time into, will close
• Deals that, no matter how much time you spend, won't close

Outreach’s AI Revenue Workflow Platform empowers sales reps, managers, and leaders with insights that guide them to take the best next actions on deals where attention will unlock the most revenue.

Instead of basing our actions on emotion, we manage deals by capturing and assessing signals across the full decision-making committee throughout the entire buying cycle. These signals inform the right workflows so our sellers and managers can rely on data – not instinct – to manage and drive their entire pipeline.

For insights, we look at deal signals like:

1. How many people are involved in the deal?
2. What’s trending for inbound and outbound communication that shows engagement?
3. Is the next meeting set? When?
4. Are there any open tasks or people in sequence?
5. How recent was the last activity?
6. Are multiple personas engaged?
7. Are we engaged above the decision-making power line?
8. How many days has the deal been in its current stage compared to the team average?
9. How many times has the close date been moved or has the deal value changed?

Proactive risk assessment is about removing subjectivity from forecasting. Managers can’t assess these signals (and many others) for every rep in every deal, and incomplete assessment makes forecasting subjective. The solution is AI-based signal monitoring at scale, leading to objective deal ranking by risk and a more accurate forecast.

Move from subjective to objective forecasting

Every organization has a sales execution gap – the difference between the potential revenue it could generate and the actual revenue it achieves. The sales execution gap has three root causes: inefficient prospecting, weak deal management, and inaccurate sales forecasting.

To clear the hurdle, you must define commit criteria for your teams. You want to take the squishiness out of your forecast categories – make them objective.

Traditionally, forecast categories are applied based on a likelihood of winning a deal, e.g., Best Case means the deal has a 60% or greater chance of being won, whereas Upside means we have a less than 60% chance. The subjectivity around how to measure the likelihood of winning a deal creates massive data inconsistency. At Outreach, we use four categories:

• Commit – there is no risk of the deal closing at the value or in the period the customer has agreed to.
• Best Case – there is risk in the deal, but we know we have a qualified deal, and the customer shared with us when they are making a decision.
• Pipeline – we have a deal; our prospect has a verified problem that we know we can solve. We don’t know when it’s going to close and aren’t ready to formally assess risk.
• Omitted – we don’t know if there’s a deal yet; we haven’t had a meeting or gathered enough information.

With “Best Case” as the category, we further break it into subcategories:

• Green risk – a small risk we can get over to win the deal, so the deal is forecasted.
• Yellow risk – there’s enough risk on the deal that we don’t feel like we can overcome it to win the contract by the decision date the customer has shared with us, so the deal is not forecasted.
• Red risk – there’s so much risk that we could lose it, so the deal is not forecasted.

Use Data to Drive Action and Consistency

Taking the subjectivity out of forecasting makes it easier to stay proactive and keep deals moving forward. By using our revenue operations solution, Outreach Commit, and our revenue intelligence solution, Outreach Guide, we can determine which deals are worth spending more time on and which ones aren’t.

For example, if a seller’s forecast is $1.7 million against a $2 million quota, the $300K difference represents gap coverage – deals not yet in the forecast that could still close with extra focus.

Outreach Guide and Outreach Commit help reps quickly identify these gap coverage deals, assess real-time risks, and prioritize where to spend their effort. A deal health score aggregates all key signals so reps and managers can focus on the most recoverable deals instead of guessing which ones to pursue.

Managers then use Outreach Commit to build a data-backed team forecast. During forecast calls, everyone shares a consistent view supported by clear health indicators, ensuring every projection is rooted in objective data – not intuition.

Using AI to prioritize deal risk at scale

Manual deal inspection doesn't scale. Eight reps with 17 deals each means 544 deal attributes to track. There's no way you're catching every risk signal across your entire pipeline.

This is where AI changes the game.

Outreach’s Deal Agent analyzes conversation patterns and engagement signals in real time, surfacing risk indicators as they emerge. Instead of discovering problems during your weekly forecast call, you get alerts when stakeholder engagement drops, when buying committee members go dark, or when deal momentum stalls.

Deal health scoring evaluates 17+ factors across all opportunities simultaneously (time in stage, sentiment trends, competitive mentions, stakeholder engagement) and ranks your deals by risk level. A rep with 15 active deals can instantly see which three need immediate attention and exactly what actions to take.

For managers, this means less time interrogating reps about deal status and more time coaching on strategy. You're working from AI-powered insights based on thousands of data points, not subjective gut feelings.

The result? Teams achieve a significant increase in forecast accuracy, and your reps focus energy where it actually moves deals forward.

Build repeatable playbooks to reduce risk

Many sales teams grapple with the challenges of rep turnover, scattered and undefined sales training, and ad-hoc individual ways of doing things. This results in a slow onboarding process, inconsistent performance, and ultimately, unpredictable execution across the sales cycle, leading to missed forecasts and underachieved growth goals.

Are you hearing things in passing conversation, like:

“I’m responsible for the results, but I don’t know what messaging, plays, programs, and investments actually drive the growth of the business.”

And:

“What exactly are our A players doing differently than everyone else?”

Or, even:

“It takes too long to onboard and become productive.”

At Outreach, our reps ramp fast and consistently execute best-practice workflows using our sales engagement solution, Outreach Engage. Following proven playbooks, Outreach helps our leaders to coach at scale and our reps to:

• Easily adopt and use our platform to perform the right activities repeatedly
• Implement playbooks and best practices with scalable workflows
• Apply ML/AI built to optimize everything from rep execution to selling processes

Turn pipeline visibility into predictable revenue

Proactive risk management beats gut feelings every time.

When you spot deal risks early with objective health data, your forecast becomes reliable. When AI flags problems automatically, your team focuses on deals that actually need attention. And when you scale proven playbooks across your team, every rep executes consistently.

Outreach connects your sales activities with outcomes through unified data and AI-powered insights, so you can diagnose risks early and act on them strategically.