How much pipeline does each channel produce per dollar? Forecasting pipe-to-spend by channel for 2027
Pipeline per dollar, or pipe-to-spend, is your average deal size divided by the channel’s cost per qualified opportunity, reduced by the months the channel takes to produce its first pipeline. So the forecast for 2027 needs two inputs per channel from your own CRM: cost per qualified opportunity and lag. With a $60,000 deal size, $500K on search at $3,000 per opportunity creates far more in-year pipeline than $500K on LinkedIn at $6,000, but LinkedIn’s pipeline arrives later and often influences deals search later captures, so judge both on a full-window view too.
Key takeaways
What is pipe-to-spend, and why do boards ask for it?
Pipe-to-spend is marketing-sourced pipeline divided by program spend over the same period. A pipe-to-spend of 10x means every program dollar created ten dollars of qualified pipeline. Cost per qualified opportunity is program spend divided by the opportunities sales accepted. The two are linked: pipe-to-spend equals average deal size divided by cost per qualified opportunity.
Boards ask for both. Dave Kellogg’s list of board-level questions on the marketing budget asks whether the plan shows pipe/spend and cost/oppty ratios, and asks for demand generation analysis by channel. A plan that shows spend by channel without the pipeline each channel is expected to create answers neither question.
How do you forecast pipeline per dollar for each channel?
Use five inputs per channel, all from your CRM except the planned spend. The formula for in-year pipeline from a channel funded evenly through the year is spend divided by cost per qualified opportunity, times the months left after the lag divided by 12, times deal size.
- Pull program spend by channel for the last four quarters, the same way finance books it.
- Pull qualified opportunities by original source and channel for the same quarters. Divide spend by opportunities: that is cost per qualified opportunity by channel.
- Measure lag: the months between spend starting in a channel, or a step change in it, and the first opportunities it sourced.
- Use average first-year deal size by channel if it differs; enterprise ABM deals are often larger than inbound search deals.
- Apply the formula to the 2027 spend by channel, then add a higher cost for any spend above what the channel has absorbed before.
The marketing budget channel planner runs this formula for six channels at once and shows the coverage of your target.
Worked example: $500K on LinkedIn vs $500K on Google
This is a worked example with stated assumptions, not a benchmark or a client result. Both channels get $500K spread evenly across 2027, and the average deal is $60,000.
| Line | Google search | LinkedIn Ads | How it is calculated |
|---|---|---|---|
| Spend in 2027 | $500K | $500K | Assumption |
| Cost per qualified opportunity | $3,000 | $6,000 | Assumption from CRM history |
| Months before first pipeline | 1 | 3 | Assumption from CRM history |
| Full-year opportunity rate | 167 | 83 | Spend divided by cost per opportunity |
| Opportunities inside 2027 | 153 | 63 | Rate times months after the lag, divided by 12 |
| Pipeline inside 2027 | $9.2M | $3.8M | Opportunities times $60,000 |
| In-year pipe-to-spend | 18.3x | 7.5x | Pipeline divided by spend |
| Pipe-to-spend once the lag has passed | 20x | 10x | Deal size divided by cost per opportunity |
On this view search wins easily. Before moving LinkedIn money to search, check two things. First, can search absorb another $500K at $3,000 an opportunity? Search volume is finite, and the marginal dollar test usually shows the next dollar costing more. Second, how many of the search opportunities came from accounts LinkedIn reached first? If priming feeds capture, cutting it raises search costs a few quarters later.
Bring your 2027 target. In 30 minutes we map the pipeline gap, the first 90 days and what to fix before January.
Why do channels differ so much on pipeline per dollar?
Because they do different jobs on different clocks. Search captures demand that already exists, so it converts fast and its cost per opportunity is low until volume runs out. LinkedIn, ABM and content mostly prime accounts that will buy later. Published data shows how long that later can be.
| Finding | Source | Published |
|---|---|---|
| 281 days on average from the first LinkedIn ad impression to revenue; 214 days from first ad conversion | Dreamdata 2026 LinkedIn Ads Benchmarks Report (vendor research on its customers’ journeys) | March 2026 |
| Return on ad spend of 121% for LinkedIn against 67% for Google Search, on multi-touch revenue attribution | Dreamdata 2026 LinkedIn Ads Benchmarks Report (vendor research) | March 2026 |
| LinkedIn at 41% of total B2B ad budgets among the companies in the data set | Dreamdata 2026 LinkedIn Ads Benchmarks Report (vendor research) | March 2026 |
| Average B2B buying cycles about 10 months in 2025, down from about 11 months in 2024; survey of more than 4,000 buyers | 6sense 2025 Buyer Experience Report (vendor research) | November 12, 2025 |
| Awareness and conversion objectives take 62.6% of total media spend | Gartner 2026 CMO Spend Survey, 401 marketing leaders | June 8, 2026 |
The Dreamdata figures are vendor data from its own customers and use its attribution model, so treat them as direction, not as your numbers. They make the point that matters for the forecast: a channel judged only on in-year pipe-to-spend can look poor while it shapes revenue a year later. That is why the long sales cycle article recommends judging priming channels on leading indicators before closed-won.
Which pipe-to-spend view should go in the 2027 plan?
Show two views per channel. The in-year view, with lag, is what the budget buys in 2027 and is the one that must cover the target. The full-window view, deal size divided by cost per opportunity, is what the channel produces once it is running, and is the fair basis for comparing channels.
| View | Formula | Use it for |
|---|---|---|
| In-year pipe-to-spend | Pipeline created inside 2027 divided by 2027 spend | Coverage of the 2027 target, board commitments |
| Run-rate pipe-to-spend | Deal size divided by cost per qualified opportunity | Comparing channels once the lag has passed |
| Marginal pipe-to-spend | Extra pipeline divided by extra spend, from a test | Deciding where the next dollar goes |
The third view comes from tests, not history. The next $50K marginal dollar test shows how to run one per channel before you commit the 2027 increase.
What are the common mistakes in pipe-to-spend forecasts?
- Using platform-reported leads instead of CRM opportunities. Costs per lead are not costs per opportunity, and the gap differs by channel.
- One blended pipe-to-spend for the whole budget. It hides which channel is carrying the plan.
- No lag. A plan that assumes every channel produces from January overstates 2027 pipeline, most of all for content, ABM and events.
- Average instead of marginal costs. The last dollar in a channel is the expensive one.
- Comparing channels on different deal sizes without saying so. Enterprise ABM deals can carry a higher cost per opportunity and still win on pipe-to-spend.
How we help
PlanConversion builds 2027 channel forecasts from your CRM, with cost per qualified opportunity and lag by channel, and connects qualified stages back to Google Ads and LinkedIn Ads so bidding learns from pipeline.
Start with the 2027 B2B marketing planning hub for every planning step, with the calculators for each.
If you want a second opinion on the forecast, talk to our team about a pipeline plan review before the budget goes to finance.
Frequently asked questions
What is a good pipe-to-spend ratio for B2B?
There is no reliable public benchmark that fits every deal size. Pipe-to-spend equals deal size divided by cost per qualified opportunity, so a company selling $200,000 contracts and one selling $20,000 contracts can both be efficient at very different ratios. Compare each channel with its own last four quarters and with the coverage your target needs.
How much pipeline should I expect from $500K on LinkedIn?
Divide $500K by your LinkedIn cost per qualified opportunity, keep only the months after LinkedIn’s lag, and multiply by deal size. In our worked example ($6,000 per opportunity, three-month lag, $60,000 deals) that is about 63 opportunities and $3.8M of pipeline inside 2027. Your numbers will differ.
Why does LinkedIn look worse than Google on pipe-to-spend?
Because in-year pipe-to-spend rewards channels that capture existing demand. LinkedIn mostly primes accounts that buy later; Dreamdata’s 2026 vendor data puts the average at 281 days from first LinkedIn ad impression to revenue. Judge LinkedIn on leading indicators and a longer window, not only on in-year pipeline.
Should I use pipe-to-spend or ROAS?
For planning a B2B budget, pipe-to-spend and cost per qualified opportunity, because pipeline is known within the year and revenue often is not. Use revenue-based return once enough deals have closed to measure it.
How do I forecast pipeline for a new channel with no history?
Run a capped test first and use its cost per qualified opportunity, or use your closest existing channel with a higher cost and a longer lag. Keep the new channel in the test reserve until it has a quarter of real data.
Sources
- Dave Kellogg, Kellblog: Board-Level Questions On The Marketing Budget (December 2, 2024)
- Dreamdata: The 2026 LinkedIn Ads Benchmarks Report (vendor research, March 2026)
- 6sense via Business Wire: 2025 Buyer Experience Report press release (vendor research, November 12, 2025)
- Gartner: Awareness and conversion account for 62.6% of total media spend (June 8, 2026)
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