Why Defining Deal Velocity Properly Matters
If you want to understand what role deal velocity plays in pipeline health, you first need to define and measure it properly.
Many revenue teams talk about “sales cycle length” but:
- Start the clock at different points (first touch, MQL, opportunity creation).
- Move deals between stages based on internal opinion, not buyer action.
- Look only at an overall average number of days that hides critical variation.
The result is that “deal velocity” becomes a vague metric you glance at in a dashboard rather than a practical lever you can use to improve forecast reliability, capacity planning and buyer experience.
This article takes Step 1 in our series and shows you how to define and measure deal velocity in a way that gives you a clearer view of pipeline health and supports the pillar guide on what role does deal velocity play in pipeline health.
What Exactly Is Deal Velocity?
At its simplest, deal velocity is how quickly qualified opportunities move from creation to a decision.
That decision may be:
- Closed-won.
- Closed-lost.
- No decision (for example, the customer does nothing or postpones indefinitely).
You can think of deal velocity at three main levels:
- Overall cycle time
The total number of days a typical deal spends in your pipeline from qualification to outcome.
- Stage-level velocity
How long deals spend in each stage (for example, discovery, solution design, proposal, negotiation).
- Segment-level velocity
How cycle time and stage ageing differ by industry, region, deal size, product line or other relevant segments.
To make deal velocity useful, you must be precise about what counts as the start and end point, and what counts as movement in between.
Decide When the Clock Starts and Stops
One of the most important decisions is when you start and stop the clock.
For most B2B organisations, a practical approach is:
- Start: when an opportunity is created and meets your agreed qualification criteria (for example, ICP fit, clear problem, realistic budget and timeline).
- End: when the opportunity is marked closed-won or closed-lost.
You can also track time from first engagement (for example, first inbound touch or outbound reply), but using a consistent “qualified opportunity” start point gives you a cleaner view of the part of the journey the sales team can most influence.
Be explicit and write this down:
- “In our reports, deal velocity is measured from [X event] to [Y event].”
Share that definition with Sales, Marketing, RevOps and Finance so everyone knows what the number actually means.
Choose the Right Levels of Analysis
If you only look at a single “average sales cycle”, you’ll miss most of the real story.
To make deal velocity meaningful, analyse it at several levels:
- Overall
Useful for a high-level view of how long deals typically take.
- By stage
Shows where deals are actually spending time and where they are most likely to stall.
- By segment
Split by industry, region, deal size, product line or customer type (for example, net-new vs existing).
- By team or rep
Highlights differences in how different teams or individuals progress deals.
This granularity allows you to say things like:
- “Enterprise deals in financial services typically take 180–240 days from qualification to close, with most time spent between solution design and commercial negotiation.”
- “Mid-market tech deals with this product line typically move from qualification to close in 60–90 days.”
Those statements are far more useful than a single number such as “Our average sales cycle is 120 days.”
Use Medians, Not Just Averages
The next decision is which statistical measures to use.
In most B2B environments, deal cycles have a long tail – a few very slow deals skew the overall average upwards.
That’s why focusing on the median (the middle value) is often more informative than the simple average.
For example:
- Average cycle time: 150 days.
- Median cycle time: 95 days.
This tells you that most deals close in around 95 days, but a minority drag on and distort the average.
Practical tips:
- Look at both median and average cycle times to get a sense of the distribution.
- Consider using percentiles (for example, “80% of deals close within 110 days”) to set realistic expectations.
This helps you avoid over- or under-reacting to a few extreme cases.
Measure Stage Ageing to Spot Stalls
Overall deal velocity is useful, but stage ageing often tells you more about where to act.
Stage ageing is simply:
How long opportunities typically spend in each stage of your pipeline.
Track, for each stage:
- Median number of days spent there.
- Percentage of opportunities that stall or die in that stage.
- Differences by segment (for example, enterprise vs mid-market).
This helps you identify patterns such as:
- “Discovery and solution design are moving relatively quickly, but deals are sitting in ‘proposal’ for 40+ days with little movement.”
- “Opportunities for Product X routinely slow down at the security review stage.”
Once you can see where time is being spent, you can design targeted interventions – whether that’s better enablement, clearer next steps, or smoother internal approvals.
Segment Your Velocity by Deal Size, Industry and Region
Deal velocity should not be interpreted in a vacuum. Different types of deals move at different speeds.
Useful segments to consider include:
- Deal size
Small, mid-sized, strategic or enterprise deals will follow different rhythms.
- Industry or vertical
Regulated industries may have longer standard cycles due to compliance, procurement and security checks.
- Region
Local buying practices, cultural norms and holiday cycles can all affect velocity.
- Customer type
Net-new customers may move more slowly than expansions or renewals.
Segmenting your velocity data allows you to:
- Set realistic expectations by segment (“enterprise deals in this vertical take longer, but that’s normal”).
- Spot outliers where deals are unusually slow or unusually fast.
This helps prevent unhelpful comparisons such as judging an enterprise deal by mid-market standards.
Use Cohort Analysis to Track Change Over Time
Cohort analysis groups opportunities by the time period in which they were created (for example, quarter or month) and tracks how they move over time.
This can show you:
- Whether deals created after a specific change (new messaging, new process, new product) are moving faster or slower.
- Whether external factors (for example, economic shifts) are lengthening cycles.
Practical steps:
- Define cohorts such as Q1 deals, Q2 deals, and so on.
- For each cohort, measure median time to key milestones (proposal sent, commercial review, closed-won/closed-lost).
You can then say things like:
- “Deals created since we introduced mutual action plans are reaching proposal stage 15 days faster on average.”
- “Deals created in this region after a regulatory change are moving 20% more slowly; we may need to adjust expectations and support.”
Anchor Movement in Buyer Actions, Not Just Stage Labels
Deal velocity is only as accurate as the data behind it. If reps move stages based on how they feel, your numbers won’t mean much.
To make velocity data trustworthy, define stage movement in terms of buyer actions rather than seller activity.
For example:
- Moving from discovery to solution design might require:
- A documented problem statement agreed with the buyer.
- Confirmation of the key stakeholders involved.
- Moving from proposal to negotiation might require:
- A formal proposal shared with the buyer.
- Feedback from key decision-makers that they are seriously considering your solution.
When stages change only when buyers do something meaningful, your deal velocity measures reflect real progress, not just admin updates.
Build a Simple Deal Velocity Dashboard
Once you have clear definitions, you can create a simple dashboard that brings them to life.
Useful components include:
- Median cycle time from qualification to close, overall and by key segments.
- Stage ageing: median days in each stage and how that compares to your expectations.
- Breakdown of deals by age bands (for example, 0–30 days, 31–90 days, 91–180 days, 180+ days).
- A small set of rep- or team-level views, using velocity as a coaching input rather than a ranking tool.
You don’t need a complex BI project. Even basic reports from your CRM, if configured well, can provide a useful view.
Share this dashboard in:
- Weekly or fortnightly pipeline reviews.
- Monthly sales leadership meetings.
- Quarterly business reviews.
This keeps deal velocity visible as part of how you run the business, not a one-off analysis.
Common Mistakes When Measuring Deal Velocity
As you build your definitions and reports, watch out for common pitfalls:
- Inconsistent start points
Starting the clock at different times for different deals, which makes comparison meaningless.
- Stage changes without buyer actions
Moving deals forward in the CRM just to make the pipeline look better.
- Over-focusing on one headline number
Quoting a single average sales cycle without looking at distributions or segments.
- Ignoring no-decision outcomes
Only analysing closed-won deals, which hides a lot of wasted time in lost or stalled opportunities.
- Not validating data quality
Trusting numbers from a CRM that is rarely updated or updated inconsistently.
Being aware of these traps helps you design a measurement approach that reflects reality.
How Step 1 Supports the Rest of the Deal Velocity Series
Defining and measuring deal velocity properly is the foundation for everything else you do with it.
It gives you the raw material to:
- Spot and diagnose unhealthy deal velocity patterns.
- Redesign stages and criteria for healthier movement.
- Coach deals more effectively and unblock stalls.
- Use mutual action plans to create predictable momentum.
- Apply AI and analytics in a way that reflects real buyer behaviour.
- Embed deal velocity in your operating rhythm and culture.
Use this article alongside the main guide on what role does deal velocity play in pipeline health to set your definitions, align stakeholders and build the first version of your deal velocity dashboard.
From there, you can start using velocity as a practical tool to build a pipeline that is not just big, but genuinely clean, healthy and sufficient.