Pipeline Coverage Analysis Template
Three documents and four sheets, covering each segment from its own conversion rate instead of one blended rule for the whole book.
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Coverage by Segment
Kestrel Data Systems, a fictional B2B SaaS company. Q3 2026 quota against pipeline eligible to close in Q3, computed from each segment's own trailing conversion rate.
| Segment | Quota | Conversion rate | Required coverage | Required pipeline | Open, Q3-eligible | Gap |
|---|---|---|---|---|---|---|
| Enterprise | $2,000,000 | 20% | 5.00x | $10,000,000 | $7,200,000 | $2,800,000 short |
| Mid-Market | $1,500,000 | 25% | 4.00x | $6,000,000 | $6,800,000 | $800,000 surplus |
| Blended (summary only) | $3,500,000 | 22.4% | 4.57x | $16,000,000 | $14,000,000 | $2,000,000 short |
| A flat 3x rule, for comparison | $3,500,000 | 33% (assumed) | 3.00x | $10,500,000 | $14,000,000 | reads as covered |
The blended gap of $2,000,000 and the flat 3x rule both understate the real problem. Enterprise is $2,800,000 short on its own conversion rate, and Mid-Market's $800,000 surplus cannot close an Enterprise deal.
Capacity Model
The dollar gap converted to an opportunity count at each segment's own average deal size, checked against the team's demonstrated creation rate over the days actually remaining before new pipeline stops being able to close in Q3.
| Segment | Gap | Avg deal size | Opps needed | Reps | Team rate/week | Weeks left | Expected at pace | Shortfall |
|---|---|---|---|---|---|---|---|---|
| Enterprise | $2,800,000 | $175,000 | 16.0 | 4 | 2.8 | 5.4 | 15.2 | −0.8 opps ($140,000) |
| Mid-Market | surplus | $60,000 | 0 | 5 | 7.0 | 13.3 | 93.0 | spare capacity |
Even if all four Enterprise reps hold their own historic pace with zero slippage for the next 5.4 weeks, the team lands about $140,000 short of the required build. Mid-Market has spare creation capacity sitting idle by comparison.
Required Pipeline Build
Enterprise's week-by-week target, cumulative, ending on June 27, 2026: the last date a new opportunity can open and still have a realistic chance to close before Q3 ends on September 30.
| Week | Dates | New opps target | Dollar target | Cumulative opps | Cumulative $ | Vs. historic pace |
|---|---|---|---|---|---|---|
| 1 | May 20–26 | 3 | $525,000 | 3 | $525,000 | on pace |
| 2 | May 27–Jun 2 | 3 | $525,000 | 6 | $1,050,000 | on pace |
| 3 | Jun 3–9 | 3 | $525,000 | 9 | $1,575,000 | on pace |
| 4 | Jun 10–16 | 3 | $525,000 | 12 | $2,100,000 | on pace |
| 5 | Jun 17–27 | 4 | $700,000 | 16 | $2,800,000 | exceeds historic pace |
Week 5 is the deadline week and the one week the plan needs more than the team's own history has produced, which is exactly the gap the reassigned Mid-Market SDR is meant to close.
Every pipeline coverage template on the market divides total open pipeline by total quota and compares the result to a flat multiple, three times, four times, sometimes stated as one divided by an assumed win rate. A single sales team selling to enterprise accounts and to mid-market accounts does not have one win rate. It has two, and a coverage ratio computed from the blended one is wrong for both segments in opposite directions at once, too loose for the slower one and too tight for the faster one.
This pack computes required pipeline separately for each segment from that segment's own trailing conversion rate, then checks it against open pipeline with a close date that actually falls inside the quarter being covered. A blended total gets stated only after the segment figures exist, labeled as a summary rather than a target, because a surplus in one segment cannot close a deal in a different one. The 3x rule itself traces to a single assumption, a 33% win rate, an assumption that breaks the moment two segments convert differently.
On a worked run for Kestrel Data Systems, a B2B SaaS company, blended Q3 pipeline read $14,000,000 open against a $16,000,000 blended requirement, a $2,000,000 gap that a flat 3x rule would have called covered outright. Underneath it, Enterprise was $2,800,000 short on its own 20% conversion rate while Mid-Market ran an $800,000 surplus. The pack pairs with reweighting a submitted forecast by rule-scored deal quality and with calibrating what a rep's commit has actually been worth.
What's in the pack
Coverage by Segment
Required pipeline computed from each segment's own trailing conversion rate, with the blended total stated only afterward and labeled as a summary, not a target.
Gap to Quota
The segment-level gap cut down to the rep or territory actually carrying it, since one rep concentrating most of a segment's shortfall needs a different fix than a team-wide push.
Capacity Model
The dollar gap converted to an opportunity count at the segment's own average deal size, checked against the team's demonstrated creation rate over the days actually left before the deadline.
Required Pipeline Build
A week-by-week cumulative target ending on the date a new opportunity stops being able to close this quarter, specific enough to hand to demand generation directly.
Coverage Assumptions
The conversion rate, cycle length, quota and average deal size behind every segment, recorded once so next quarter's sheets compute from agreed numbers instead of a re-argued rate.
Gap Action Note
The write-up naming the specific ask: how many net-new opportunities, of what size, by what date, and which team's spare capacity might already be able to source them.
How to use it
- 1
Send the exports
The open opportunity export with segment and expected close date, closed-won and closed-lost history for the trailing four quarters by segment, and quota by segment.
- 2
Compute coverage by segment
Required pipeline from each segment's own conversion rate, the real gap or surplus, and what a flat coverage rule would have said instead.
- 3
Run the capacity check
The gap converted to an opportunity count, checked against the team's own historic creation rate over the days actually remaining before the deadline.
- 4
Get the build plan and the ask
A week-by-week target ending on the deadline date, plus a specific, dated action note naming where spare capacity in another segment might help.
Frequently asked questions
Why not just use a 3x or 4x pipeline coverage rule?
Because it assumes one win rate across the whole book. The 3x figure traces to a 33% win rate assumption from 1990s enterprise software sales, and any two segments converting at different rates need different coverage, not the same flat multiple applied to both.
Our blended coverage looks fine. Why would we run this?
A blended figure can look fine while one segment is genuinely short, because a surplus in a fast-converting segment offsets a shortfall in a slow one inside the total. Kestrel's worked example reads as an 87.5% blended coverage while Enterprise alone is 28% short of what it actually needs.
What if we don't track segment on our closed-deal history?
Add it manually for the trailing four quarters before trusting a segment-specific conversion rate. A company-wide rate applied to every segment defeats the purpose of separating them, and the assumptions doc says plainly which segments have too few closed deals to trust yet.
How is the deadline date calculated?
The quarter's end date minus that segment's own average sales cycle length, from closed-won history. A deal opened after that date has not had the time a typical deal in that segment takes to close, so it cannot reasonably be counted on for the current quarter.
Does this replace a forecast call or a hygiene review?
No. Pipeline hygiene decides which open deals belong in the count at all, and this pack assumes that's already settled. It answers a different question: whether enough of that clean pipeline exists, early enough, to hit the number.
What if capacity is short even after the build plan runs?
That is what the Capacity Model sheet checks. It compares the team's own historic creation rate against the time remaining and states the shortfall in dollars if the pace doesn't change, rather than assuming a plan gets met just because it was written down.
Find out if your coverage is real or just blended
Send an opportunity export, four quarters of closed history by segment, and quota by segment, and get each one's real gap and deadline.
Get the template