Sales Cycle Analysis

Academy Study Groups Study Group: Sales Enablement
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If you are concerned about data cleanliness, specifically in Sales Hub, then this one might be for you. The following custom property and reports can help your sales team:

  1. Identify stale deals that have been left open
  2. Identify bad-fit lead generation channels that are muddying your win/loss rates
  3. Better understand your actual sales cycle (from open to win)
  4. Spend less time on lost or unlikely opportunities
  5. Track trends and impact on your sales cycle over long periods of time

This plan outlines how to leverage Sales Hub (Professional or Enterprise) to track, analyze, and optimize your Time-to-Close. By automating the categorization of deal statuses, you can generate precise reporting that identifies where deals are stalling and how sales behavior impacts your cycle.

Step 1: Data Foundation (Properties)

To report on deal duration accurately, we must first normalize how “Open,” “Won,” and “Lost” deals are categorized outside of the standard Deal Stage property.

What to do

  1. Navigate to Settings > Objects > Properties.
  2. Select Deal from the dropdown.
  3. Click Create property.
  4. Label: Deal Status.
  5. Field type: Dropdown select.
  6. Options: Open, Won, Lost.

Step 2: Automation (Workflow Setup)

This workflow ensures the “Deal Status” property stays updated in real-time as Deal Probability changes.

What to do

  1. Create a Deal-based workflow from scratch.

  2. Trigger: Set “Deal Probability is known.”

  3. Re-enrollment: Enable re-enrollment for “Deal Probability.”

  4. Action: Add a “Value equals branch” or “If/then branch” with three paths:

    • Branch 1 (Lost): Deal Probability is equal to 0%.
    • Branch 2 (Won): Deal Probability is equal to 100%.
    • Branch 3 (Open): Deal Probability is between 1% and 99% (inclusive).

  5. Actions per branch:

    • Under Lost, [Edit Record] add “Set property value” → Deal Status = Lost.
    • Under Won, [Edit Record] add “Set property value” → Deal Status = Won.
    • Under Open, [Edit Record] add “Set property value” → Deal Status = Open.

Step 3: Baseline Reporting (Time-to-Close Analysis)

Once the data is populated, you need to visualize the average duration for each status.

What to do

  1. Go to Reporting > Reports > Create report > Single object > Deals.

  2. Filters: Set “Create Date” to “All time” (or a specific fiscal year).

  3. Data: Select “Days to Close” and “Deal Status.”

  4. Visualization: Choose a bar chart or summary table.

  5. Configuration:

    • Y-axis: Average of Time to Close.
    • X-axis: Deal Status.

Why it matters

This chart reveals your “Velocity Gap.” You can now see the average time it takes to win versus how long dead deals are lingering in your pipeline.
You can save additional copies of this report broken down by:

  • Deal Owner
  • Team
  • Deal Type
  • Product/Service
  • Other custom (dropdown/category) property of your choosing

Step 4: Strategic Analysis (The Loss/Win Ratio)

Use the data from Step 3 to calculate your Loss-to-Win Ratio.
Take the average time your teams lose a deal, and divide it by the average time they take to win a deal.

Less than or equal to 1:

Likely good news. Your team identifies bad fit leads quickly and disqualifies them without wasting time.
If its significantly below 1.0 however you may want to confirm you understand why the team disqualifies deals so much faster than they win them.
Is there a lead source with bad fit leads generating opportunities? If so, you may want to disqualify these prior to deal creation as this is artificially deflating your teams/reps win rate.
Is there a sales incentive relating to deal cycle? Your team may be shutting down good leads because their pay is negatively impacted by letting too many bad (and good) deals stay open too long.

Between 0.8 - 1.2

Likely healthy. There may be some optimization available but this is generally not indicitaive of a major outstanding issue.

Greater than 1.2

This is a good time to analyze whats happening. If you have a shorter sales cycle (<75 days) then this may not be an issue. The longer your sales cycle, the more impactful 20%+ extra time could be on the efficiency of your team. Use the reports below to more closely determine what is happening.

Step 5: Advanced Diagnostics (Drill-Down Reports)

If your ratio is high, use these two reports to find the root cause.

Option A: The “Neglect” vs. “Desperation” Test

Create a Calculation Property that measures the time between Last Activity Date and Close Date.

  • If the gap is long: Deals are being won/lost, but the rep isn’t updating HubSpot for weeks (Operational lag).
  • If the gap is short: Reps are actively working “dead” deals until the very last second (Sales strategy issue).

Option B: Rep Performance Breakdown

  1. Duplicate the report from Step 3.
  2. Change the X-axis to Deal Owner.
  3. Break down by Deal Status.
  4. Why it matters: This identifies which specific reps are managing their pipeline lifecycle efficiently and which ones need coaching on disqualification.

Step 6: Iterative Review (Trend Analysis)

To see if your process changes are working, you must view these metrics over time.

What to do

  1. Create a report filtering deals by Create Date to This Year or Rolling 365.
  2. Set the X-axis to Create Date (Grouped by Quarter or Month).
  3. Set the Y-axis to Avg Time to Close.
  4. Break down by Deal Status (Won/Lost).

Why it matters

This tells you how your sales cycle is actually changing period-over-period. If you implement new sales training in 2026, you should see the “Won” bar for 2026 deals decrease compared to 2025.

Miscellaneous Considerations

If your account was created within the last ~3 years OR you know there was a very large import, consider filtering out deals either by an old create date or a deal list of those imported. Imported deals can throw off default properties like Days to Close.
Before interrogating your sales team based on a report, dig into a few deals. As Ted Lasso (and his dad) once said “Be Curious, Not Judgemental”. The point of this analysis is to ensure your sales team is spending time as efficiently as possible. The goal is to help them sell more and ideally that means they make more money. Also as Jeff Bezos has said “When the data and the anecdotes disagree, the anecdotes are usually right.”
If your loss/win cycle ratio is 1.2-2.0+, consider building a simple workflow that notifies a seller when their deal is X% past the avg days it takes to win a deal encouraging them to more critically analyze the opportunity.

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This is a solid framework — especially the Loss/Win Ratio concept in Step 4. Most teams look at win rate in isolation without considering how long lost deals are dragging down the pipeline before someone finally closes them out.
One thing I’d add: the “Neglect vs. Desperation” test in Step 5 is where most of the actionable insight lives, but it’s also where most teams stop. They see the gap between last activity and close date, but they don’t act on it until the pipeline review — which might be weeks later.
The practical fix I’ve seen work: instead of waiting for the retrospective analysis, set up a saved view that shows deals where days in current stage exceeds your average for closed-won deals in that same stage. That gives you a real-time “these deals are drifting” list instead of finding out after the fact.
Your point about filtering out imported deals is underrated too. I’ve seen teams panic over their sales cycle metrics only to realize half their “slow” deals were a bulk import from a CRM migration that never had accurate dates to begin with.
Good write-up — the Ted Lasso quote is a nice touch.