What is a good referral and repeat business rate? Benchmarks

There is no credible cross-industry benchmark for a service business’s referral rate, so a good rate is one measured on its own denominator and compared like for like. The nearest published figures: 69% of professional-services clients say they would refer, 72% of buyers say they have not referred because nobody asked, and health clubs averaged 66.4% member retention.

• Referral willingness (professional services): 69% of clients willing to refer; 72% of buyers had not referred their provider because they had never been asked (Hinge’s Inside the Buyer’s Brain research, as reported in Hinge Research Institute, Referral Marketing for Professional Services Firms).
• Repeat rate (gyms and health clubs): member retention averaged 66.4% across 175 companies and 17,000+ facilities in 27 countries (Health & Fitness Association, 2025 benchmarking report).
• Repeat rate (B2B SaaS): median gross revenue retention about 91% below $250k annual contract value and 95% above it, from 1,000+ private companies (SaaS Capital, 2025 retention benchmarks).
• Trades, home services, ecommerce, clinics: no independent public benchmark for referral rate. Compare your cohort with last year’s.
• The trap to avoid: referral share of new business rises when your paid channels fail. Track referred wins per customer instead.

Referral and repeat rate benchmarks by business model

Referral and repeat is the stage that compounds after the sale, and it is the last of the 17 sales pipeline stages and what each one costs. The table below is the whole of what we could verify at source. Each figure measures something slightly different, so the second column matters as much as the number.

The “below par” column is our reading rule, not part of any source. Where a published figure exists it is the line; where none exists, the line is your own previous cohort.

The best-documented referral and repeat benchmarks are retention figures for subscription models; for one-off service businesses, no public referral-rate benchmark survives a check at source.

Why is there no single good referral rate?

Because the phrase covers at least three different ratios, and published figures rarely say which. A survey of what customers say they would do (Hinge’s 69%) cannot be compared with a count of what they did. A retention rate for a monthly membership (HFA’s 66.4%) cannot be compared with a repeat rate for a kitchen renovator whose customers buy once a decade.

The most quoted referral statistic online is a case in point. The line that “83% of satisfied customers are willing to refer, but only 29% do” is attributed to Texas Tech University across dozens of marketing blogs, but the citations circulate without a paper, author, year or sample, so it cannot be checked and is not used here.

A referral rate is only a benchmark if its denominator, window and source of truth are stated; most published referral statistics state none of the three.

Three referral numbers that get confused, with a worked example

Use one cohort, meaning every customer won in one 12-month period, and read it 12 months later. Illustrative inputs; substitute your own.

• Cohort: 200 customers won last financial year.
• Customers from that cohort who referred at least one enquiry in the next 12 months: 15.
• Referred enquiries they sent: 38. Referred enquiries that became paying customers: 24.
• All new customers won in the same 12 months, from every channel: 80.

The same business can truthfully say “30% of our business comes from referrals” and “only 7.5% of our customers refer us”. Both are true. Only the second tells you how much room is left.

Referred wins per customer is the one referral number that cannot be flattered by a change in your other channels.

The referral-share illusion: when a rising share is bad news

The referral-share illusion is our name for a common misreading: a rising share of new business from referrals is treated as proof that referrals grew, when it often means the other channels shrank. In the example, suppose paid acquisition collapses and non-referred wins fall from 56 to 26. Referred wins stay at 24. Referral share jumps from 30% (24 ÷ 80) to 48% (24 ÷ 50). Nothing about referrals improved; the business won 30 fewer customers.

The fix is to report referral share only next to referred wins per customer. If share rises while referred wins per customer is flat, the referral stage has not changed and the problem is upstream. The active-referrer test for referrals that have dried up covers the opposite case, where the referred-wins count itself is falling.

Under the referral-share illusion, a business can watch its referral percentage climb while its total customer count falls.

What is a good repeat business rate?

It depends on whether the customer is on a contract. Subscription models have published figures because renewal is recorded automatically: HFA’s 66.4% annual member retention for health clubs, and SaaS Capital’s ~91% median gross revenue retention for B2B SaaS below $250k annual contract value. Note the SaaS figure is revenue, not customers, so one large renewal can hide several small losses.

For businesses without a contract, such as trades, clinics, agencies and retailers, the repeat rate is customers from a cohort with a second purchase within a stated window, divided by the cohort. Set the window at your normal buying cycle, not a calendar year: a 12-month window flatters a monthly service and punishes a business whose customers buy every three years. We found no independent public figure for these models, and the ecommerce figures in circulation come from single platforms with different windows.

For a business without contracts, a repeat rate is only comparable with another repeat rate measured over the same buying cycle.

How long before my referral rate means anything?

About a year, which is the honest cost of this metric. A 12-month cohort read 12 months later means the first clean number arrives a year after you start recording the source field properly. Until then you are reading partial cohorts.

What it costs to run yourself:

• Data: a referral-source field captured at enquiry, with a named referrer, not just “referral”. Without the name you can count referred wins but not the participation rate.
• Time: a quarterly cohort report is a spreadsheet job of an hour or two once the field exists. Backfilling the previous year from invoices and inboxes is the slow part.
• Noise: at 200 customers and a 7.5% participation rate, the standard error is √(0.075 × 0.925 ÷ 200) = 1.9 percentage points, so a move from 7.5% to 9% is inside the noise.
• Handling: the referred enquiry win rate depends on how fast referred enquiries are answered, which is a staffing question outside office hours.

The levers that move these numbers, ranked by the evidence behind them, are on how to increase referral and repeat rate. If the constraint turns out to be answering referred and repeat enquiries quickly rather than generating them, that is the part an AI appointment-setting service covers; the measurement itself stays with you.

The referral and repeat rate is the slowest pipeline metric to read: a clean 12-month cohort takes a year to mature.

Referral and repeat rate benchmark questions

Is 30% of new business from referrals good?

It depends on your other channels. Referral share of new business is referred wins divided by all new wins, so it rises whenever paid or outbound acquisition falls, even if referrals are flat. Judge it alongside referred wins per customer in a 12-month cohort. If that per-customer figure is rising, the 30% is good news; if it is flat, the share tells you about channel mix, not referral health.

What percentage of customers actually refer a business?

No reliable cross-industry figure exists. In professional services, the Hinge Research Institute reports that 69% of clients are willing to refer, and that 72% of buyers had not referred their provider because they had never been asked (Hinge, Referral Marketing for Professional Services Firms). Willingness is not action, so count your own referrer participation rate: customers who referred at least once, divided by the cohort.

What is a good member retention rate for a gym?

The Health & Fitness Association’s 2025 benchmarking report puts average member retention at 66.4%, from 175 companies and more than 17,000 facilities across 27 countries surveyed between April and June 2025 (HFA 2025 Fitness Industry Benchmarking Report). A club below that average has a repeat problem to fix before a referral programme will pay back.

What is a good retention rate for B2B SaaS?

SaaS Capital’s 2025 survey of more than 1,000 private B2B SaaS companies found median gross revenue retention of about 91% for companies below $250,000 annual contract value and 95% above it, excluding companies under $1M ARR (SaaS Capital 2025 retention benchmarks). Gross retention excludes expansion revenue, so it is the closer match to a repeat rate.

How many referrals should I get per client?

There is no published norm for referrals per client in service businesses. Measure referred wins per customer on a 12-month cohort and compare it with the previous cohort. In the worked example on this page, 200 customers produced 24 referred wins, or 0.12 per customer; your own figure is only meaningful against your own history.