No credible public benchmark exists for long-term lead follow-up conversion. The usable yardstick is arithmetic: where buyers change provider about every five years, roughly 20% enter the market in any year. Follow 400 aged leads for 12 months, win 15% of those who come into market, and expect about 12 conversions: 3%.
- Published benchmark: none with a sample, a window and a denominator for leads aged 30+ days (checked 27 September 2026).
- In-market share: where companies change provider about every five years, only about 20% are in market in a given year and 5% in a given quarter (Professor John Dawes, Ehrenberg-Bass Institute).
- Journey length: 272 days from first touch to revenue on average in Dreamdata’s B2B attribution data; an 11.3-month average buying cycle in 6sense’s 2024 buyer survey. Both are vendor research.
- The in-market baseline: expected 12-month conversion = (12 ÷ your purchase cycle in months, capped at 1) × the share of in-market buyers you win.
- Not the same metric: our Colliers-era database reactivation record (4.4% average, 8.9% peak) measures dormant CRM leads converted to booked qualified discovery calls across several campaigns, with no published window or sample, not open leads followed for a year.
Is there a benchmark for long-term lead follow-up conversion?
No. The figures that circulate for “nurtured leads” rarely state which leads, over what window, converted to what. Here is everything we could verify at source that bears on the question, with what each figure actually measures.
| Figure | What it measures | Source and type | Use it for |
|---|---|---|---|
| 5% in market per quarter; 20% per year | Share of B2B buyers of services changed about every five years (banking, legal, software, telecoms) who are buying at a given time | John Dawes, Ehrenberg-Bass Institute, research for the LinkedIn B2B Institute | The in-market share in the baseline formula |
| 272 days | Average time from first touch to revenue in B2B journeys | Dreamdata LinkedIn Ads Benchmarks Report (vendor attribution data) | How long a long-term follow-up programme must run before it can be judged |
| 11.3 months | Average B2B buying cycle reported by recent buyers | 6sense 2024 Buyer Experience Report (vendor survey) | A second check on read-window length |
| 4.4% average, 8.9% peak | Dormant CRM leads converted to booked qualified discovery calls, averaged across several reactivation campaigns | LeadsNow, Colliers-era campaigns; no window or sample size disclosed | Dormant-database reactivation only, not 12-month follow-up |
| Aged open lead → conversion within 12 months | The metric this page is about | No public source found | Measure your own against the baseline below |
Long-term lead follow-up has no published conversion benchmark because nobody who publishes benchmarks owns both the lead list and the 12 months of conversations that follow it. The honest substitute is a baseline you calculate from your own purchase cycle.
How it works
How to set a benchmark for long-term lead follow-up
Form the aged cohort
Take every lead still open and not disqualified at day 31, grouped by the month it first enquired.
Estimate in-market share
Divide 12 by your purchase cycle in months, capped at 1. A five-year cycle gives 20%.
Calculate your baseline
Multiply the in-market share by the share of in-market buyers you win. That is your expected 12-month rate.
Read the mature cohort
After 12 months divide measured conversion by baseline. Under 0.25 means follow-up is mostly not running.
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Is long-term lead follow-up the same as database reactivation?
No, and mixing them is why figures from one get quoted as targets for the other. Long-term follow-up works open leads that enquired, did not convert in the first 30 days and were never disqualified, with an unbroken sequence running for a year or more. Database reactivation is a campaign aimed at records that went dormant, often for years, with no sequence running in between.
The denominators differ, and so do the numbers. Our Colliers-era reactivation figures of 4.4% average and 8.9% peak measure dormant CRM leads converted to booked qualified discovery calls across several campaigns, and we have not published the window or sample behind them. They are a reactivation record, not a follow-up benchmark. The benchmark evidence for that metric, including the three-denominator problem, is on our page of database reactivation rate benchmarks, and the campaign itself is written up in 4.4% average conversion on dormant leads.
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What conversion should you expect from long-term lead follow-up?
Calculate it rather than borrow it. We call this the long-term follow-up in-market baseline: the conversion you would expect from 12 months of follow-up if your aged leads came into market at random points in their purchase cycle and you won the same share of them as you win of fresh, in-market enquiries.
Baseline = (12 ÷ purchase cycle in months, capped at 1) × your win share of in-market buyers
The first term is the Dawes arithmetic applied to your own cycle. The second is yours: the share of in-market leads, reached in time, that you turn into the outcome you are measuring. Here is the table for common cycles, calculated at three win shares.
| Purchase or replacement cycle | Share coming into market over 12 months | Baseline at 10% win share | Baseline at 15% | Baseline at 25% |
|---|---|---|---|---|
| 12 months or less | 100% | 10% | 15% | 25% |
| 2 years | 50% | 5% | 7.5% | 12.5% |
| 4 years | 25% | 2.5% | 3.75% | 6.25% |
| 5 years | 20% | 2% | 3% | 5% |
| 10 years | 10% | 1% | 1.5% | 2.5% |
Worked end to end: 400 leads enter the long-term cohort at day 31. Your buyers change provider about every five years, so about 80 of them (20%) should come into market in the next 12 months. You win 15% of the in-market leads you reach in time, so about 12 should convert: 12 ÷ 400 = 3%. If the cycle were two years, the same maths gives 200 in market and 30 conversions, 7.5%.
Two biases pull in opposite directions, and you should know both. Leads who enquired were closer to buying than a random buyer, which pushes real results above the baseline. Some of them bought from a competitor inside the first 30 days, which pushes results below it. The baseline is a reference line, not a forecast.
How do you read your long-term follow-up conversion against the baseline?
Divide your measured 12-month conversion for a mature cohort by your baseline. This is our reading rule, not an external benchmark.
| Measured rate ÷ baseline | Example at a 3% baseline | What it usually means | What to check |
|---|---|---|---|
| Under 0.25 | Under 0.75% | Follow-up is not running for most of the year | Touches actually sent after month two, not touches scheduled |
| 0.25 to 0.5 | 0.75% to 1.5% | You are present for part of the cycle and missing the rest | Months with no touch at all; replies answered late |
| 0.5 to 1.0 | 1.5% to 3% | Working: you catch most buyers who come into market | Channel width and reply speed |
| Over 1.0 | Over 3% | Strong, or your leads are closer to market than random | Whether the cycle length you used is too long |
A long-term follow-up programme that converts under a quarter of its in-market baseline is not underperforming; it is mostly not running. Why that happens, and how to confirm which cause you have, is the job of a diagnosis rather than a benchmark. The levers that lift the rate, ranked by effect, are on our guide to increasing long-term lead follow-up conversion.
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How long must follow-up run before the rate can be judged?
At least 12 months, and longer where your cycle is. Dreamdata’s 272-day average from first touch to revenue and 6sense’s 11.3-month buying cycle are both vendor figures, but they agree on the order of magnitude: a follow-up sequence that stops after five emails in the first month is measuring the leads who were already buying, not the ones it was meant to wait for.
Our own operating practice plans for around 30 conversations over 12 months or more on some leads. That is our practice, not a published statistic, and the right number for you depends on your cycle length and how much each touch has to say.
How many aged leads do you need before the rate means anything?
More than most businesses expect, because the rates are small. The standard error of a proportion is √(p × (1 − p) ÷ n). At a true 3%:
- 100 leads: √(0.03 × 0.97 ÷ 100) = 1.7 points, about ±3.3 at 95% confidence. A cohort reading 0% and one reading 6% are both plausible.
- 400 leads: 0.85 points, about ±1.7 at 95%.
- 1,000 leads: 0.54 points, about ±1.1 at 95%.
Below about 400 leads in a cohort, pool several entry months before placing yourself in a band. Measuring costs little once conversions are tagged to the entry month; running 12 months of follow-up is where the hours go, and that is the part our lead follow-up automation service takes on. Where this stage sits in the full funnel is mapped in our sales pipeline stages and what they cost hub.
Frequently asked questions
What is a good conversion rate for long-term lead follow-up?
No public benchmark exists, so compare against your in-market baseline: 12 divided by your purchase cycle in months, capped at 1, times the share of in-market buyers you win. For a five-year cycle and a 15% win share that is 3% over 12 months. Reaching at least half of your baseline means the programme is working.
What percentage of old leads eventually buy?
Nobody publishes a verified figure for aged leads. The nearest evidence is on timing: where firms change provider about every five years, about 20% of buyers are in market in a given year, according to Professor John Dawes of the Ehrenberg-Bass Institute. Most old leads were early, not lost.
How long should I keep following up a lead?
At least one full purchase cycle, and never less than 12 months for considered purchases. Dreamdata’s attribution data puts the average B2B journey at 272 days from first touch to revenue, so a sequence that ends in the first month misses most buyers.
Is a long-term nurture conversion rate the same as a reactivation rate?
No. Nurture follows open leads continuously; reactivation is a campaign against dormant records. Our Colliers-era reactivation average of 4.4% measures dormant CRM leads converted to booked calls, has no published window or sample, and does not transfer to a 12-month nurture cohort.
How many leads do I need to measure long-term follow-up conversion?
About 400 per cohort for a usable reading. At a true 3% rate, 100 leads gives a 95% margin of roughly 3.3 points, wide enough that 0% and 6% are both plausible. Pool entry months if your volume is lower.
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