How Many Steps Does It Take to Find Your At-Risk Deals?

It's Monday morning. Your CRO asks: "Which deals in my pipeline are at risk right now?"

Trick question, because there’s risk on every deal, but you know what happens next.

It typically goes something like this…pulling data from three different places, exporting a spreadsheet, and sending messages to reps who may or may not respond before your next meeting.

I'm Chris Etterman, VP of Customer Revenue at People.ai. I've watched this play out dozens of times. So I want to make the pain concrete -  because once you count the steps, it's hard to ignore.

The Traditional CRM Route for Identifying At-Risk Deals: Counted

Here's what answering that one question looks like in a standard CRM environment:

1. Open CRM
2. Pull up the pipeline view, filter by close date
3. Realize the view doesn't show engagement or activity data
4. Export to a spreadsheet
5. Open your activity report in a separate tab
6. Cross-reference engagement levels against each deal, one by one
7. Check when each deal last had a meeting, email, or call logged
8. Flag the ones that look quiet - then second-guess yourself because you know logging is inconsistent
9. Ping the relevant reps to find out what's actually happening
10. Wait for responses
11. Pull it all together into something your CRO can read in under a minute

Eleven steps. Somewhere between 45 minutes and two hours, depending on how fast your reps respond and how clean your data is.

And you're still not fully confident in the answer. Because it only reflects what got logged.

What This Actually Costs your Pipeline

The time loss is real, but it's not the real problem.

The real problem is that when answering a basic question takes this long, leaders stop asking it as often as they should. They go into forecast calls with an incomplete picture. They make decisions based on rep narratives instead of actual buyer behavior. They find out a deal went dark in week eight, when they could have caught it in week two.

Slow answers don't just cost time. They cost deals.

What Deal Risk Signals Actually Look Like

Deal risk signals are the behavioral patterns that show a deal is heading off track. The most common ones:

• No buyer-side email response in 14+ days
• Missing a key stakeholder in any contact record
• A meeting that was scheduled but never happened
• Engagement dropping from multiple contacts to one
• Close date pushed more than once without a clear reason

Most teams only spot these during a pipeline review call. By then, the window to act has already closed most of the way.

The SalesAI Route: Counted

Type: "Which deals in my pipeline are at risk right now?"

Read the answer.

Two steps. Roughly 15 seconds.

The answer pulls from automatically captured activity - every email, every meeting, every call - not from what a rep entered between their last customer meeting and end-of-day Friday. You see which deals have gone quiet, which ones are missing key stakeholders, and which ones haven't had real buyer engagement in weeks.

No tab-switching. No exports. No waiting.

The Questions That Should Never Require an Investigation

Here are questions revenue leaders ask every week - each one triggering a scramble in most organizations:

1. Which deals have had no buyer engagement in the last two weeks?

Requires cross-referencing activity logs and contact records. Manual, slow, and only as accurate as what got logged.

2. Where did my forecast change since last week - and why?

Most teams rebuild this in a spreadsheet every single week. It's the one that breaks people.

3. Which accounts have gone quiet in the last 30 days?

Only answerable if last-touch data exists in the CRM. Often it doesn't.

4. What's stalling my top three deals right now?

This one gets answered with rep storytelling in pipeline reviews -  which is a polite way of saying guesswork.

Every one of these has a real answer. The issue is where it lives and how long it takes to surface.

Why the Gap Between "Asked" and "Answered" Matters

There's something that doesn't get talked about enough in forecasting: the cost of decision latency.

Not data latency. Decision latency - the time between when a problem exists in your pipeline and when you actually find out about it.

In most organizations, that gap is measured in days. Sometimes weeks. By the time a rep flags a stalled deal in a pipeline review, the window to save it has already closed most of the way.

When you can ask a question and get a real answer in 15 seconds - drawn from actual captured activity, not manual entries - that gap closes. You catch the deal going quiet in week two, not week eight. You walk into Monday's forecast call already knowing which deals need attention today.

That's not a marginal improvement. It changes how you lead.

Try It This Week on Your At-Risk Deals

Want to pressure-test how fast your current setup answers basic questions? Start here:

• Which deals closing this quarter have had no meeting in the past two weeks?
• Which accounts haven't responded to outreach in 30 days?
• What changed in my at-risk deals since last week's pipeline call?

Time yourself. Count the steps. Then ask the same questions in SalesAI.

The contrast tends to be pretty clarifying.

See how SalesAI answers in seconds →