Referral marketing combines personal recommendations with measurable incentives and conversion rules. The available research shows strong consumer trust in referrals, widespread use of double-sided rewards, and meaningful value beyond the first referred purchase. The figures below cover 2024 studies and benchmarks of programs observed from 2020–2023; dates and geography are stated for each result.
Contents
- Referral trust, reach, and influence
- Program structures and reward mechanics
- Conversion definitions and reward timing
- Incentives and reward types
- Benchmarks by industry
- Engagement and downstream economics
Referral trust, reach, and influence
Impact.com’s 2024 report said referral marketing could generate as much as 20% of a company’s new revenue each year, an outlook stated for 2024 and beyond. Its program benchmark analyzed more than 120 global B2B and B2C programs across five industries. Observations spanned 2020–2023, with analysis conducted in March and April 2023. Industry cuts were explicitly based on small samples. (The state of referral marketing report 2024)
Consumer research points to the role of trust behind that commercial potential. In an Australian consumer study conducted in 2024, 81% of respondents said recommendations and referrals were important to their buying decisions. In the same study, 58% said someone they knew personally was their most trusted source of purchasing information, while only 3% selected advertisements as the most trusted source. Among Australian young millennials aged 28–35, 91% valued a referral from someone they knew for a first-time purchase. (The Australian Customer Referral Marketing Report)
Buyapowa reported similarly broad participation, although the page does not state the survey fieldwork date. It reported that 95% of people had referred a friend during the previous year, and 83% of those referrers had done so more than once. Separately, 76% had received at least one referral invitation during the previous year. (Reward Revolution)
Rewards were closely tied to willingness to participate in that Buyapowa reporting. Seventy-four percent said they would be less likely to refer a friend without a reward, and 70% said they would be less likely to act on a referral invitation without one. The page also reported that uninspiring rewards had stopped almost 80% of people from referring at least once. These percentages should be read with the page’s unstated survey period in mind.
Program structures and reward mechanics
Double-sided programs were the dominant structure in Impact.com’s 2020–2023 benchmark: more than 78% of consumer referral programs rewarded both participants. Among SaaS programs, 69% were double-sided, while 96% of single-sided programs rewarded the existing customer who made the referral.
Reward equality was common but not universal. Fifty-four percent of programs offered the same reward to the referrer and the referred person. When reward values differed, 55% offered the higher reward to the referred customer. Tiered structures appeared in 20% of programs, and three tiers were the most common tier count among programs using tiers.
| Program design measure | Share or result |
|---|---|
| Consumer programs that were double-sided | More than 78% |
| SaaS programs that were double-sided | 69% |
| Single-sided programs rewarding the referrer | 96% |
| Programs with equal rewards | 54% |
| Programs using tiered rewards | 20% |
| Most common number of tiers | 3 |
These figures describe observed program designs, not a universal recommendation. The report’s sample covered global B2B and B2C programs, and its industry-specific observations came from small samples.
Conversion definitions and reward timing
Across the benchmark, 62% of programs defined a successful referral conversion as a purchase by the referred person. The purchase definition was more common among transactional businesses, where 81% used a purchase event. Subscription companies showed a different pattern: 43% used a custom event rather than a purchase to define conversion.
SaaS programs were divided between the two approaches. Fifty-five percent rewarded a purchase event, while 45% rewarded a custom event. The distinction matters because a referral program can be optimized for immediate revenue, a qualified signup, an activation milestone, or another business-defined event. The benchmark reports the proportions but does not establish that one definition performs better in every category.
Reward timing also differed by participant. Referrers received their reward upon successful conversion in 96% of benchmark programs. The referred person received a reward immediately after being referred in 78% of programs. This creates a common pattern in which the new customer receives an immediate incentive while the existing customer’s reward depends on a later qualifying event.
The benchmark’s conversion measures covered programs analyzed from 2020–2023 and reported in 2024. They should not be treated as current market-wide shares outside that scope.
Incentives and reward types
Store credit was a leading incentive in the Impact.com benchmark. The report’s chart specified that 50% of programs gave store credit to both the referrer and referred person. Store credit was used for the referrer in 46% of programs and for the referred person in 42%. A percentage discount was used for the referred person in 24% of programs, while gift cards rewarded the referrer in 14% and cash rewarded the referrer in 12%.
The mix changed with program structure. Among double-sided programs, 44% used store credit, 15% used percentage discounts, and 12% used gift cards. Among single-sided programs, 31% used store credit, 30% used cash, and 22% used gift cards.
| Reward type or use | Share of programs |
|---|---|
| Store credit for both participants | 50% |
| Store credit for referrer | 46% |
| Store credit for referred person | 42% |
| Percentage discount for referred person | 24% |
| Gift card for referrer | 14% |
| Cash for referrer | 12% |
Buyapowa reported that referrers and referred friends expected to choose among an average of 3–4 rewards. That result comes from a page whose survey period is not stated, so it is best used as a reported engagement finding rather than a dated benchmark.
Benchmarks by industry
Ecommerce programs in the Impact.com benchmark were double-sided in 94% of cases and rewarded a purchase event in 85% of cases. Thirty-five percent allowed referrers to send reminder emails to referred people, and 44% used personalized links or codes containing the referrer’s name. Seventy-nine percent were built into a brand website or microsite, while 32% of ecommerce companies also offered affiliate programs.
The average value of any reward in the ecommerce benchmark was $27. Among double-sided ecommerce programs, store credit was used by 47%, with an average value of $20. Rewards were unequal in 53% of those double-sided ecommerce programs.
Telecommunications programs had an average reward value of $55 and were double-sided in 80% of cases. Fintech and financial-services programs most commonly used a $50 reward value. In that group, 66% used custom events to define conversion rather than relying on a purchase event.
| Industry benchmark | Reported result |
|---|---|
| Ecommerce programs double-sided | 94% |
| Ecommerce programs rewarding a purchase | 85% |
| Ecommerce programs with personalized links or codes | 44% |
| Average ecommerce reward value | $27 |
| Average telecommunications reward value | $55 |
| Telecommunications programs double-sided | 80% |
| Most common fintech and financial-services reward value | $50 |
| Fintech and financial-services programs using custom events | 66% |
Impact.com cautioned that its industry cuts were based on small samples. These figures therefore provide directional comparisons among the benchmarked programs, not estimates of every company in each industry.
Engagement and downstream economics
Referral value can continue after the first conversion. An article from the American Marketing Association summarized a 2024 Journal of Marketing Research study and was published in 2026. Across multiple field datasets, referred customers made 31%–57% more referrals than customers acquired through other channels. The same summary reported that ignoring secondary referrals caused firms to undervalue a referral’s total worth by 20%–36%. These are field-data findings and are separate from Impact.com’s program-design benchmark. (Referral Contagion: Capturing the Full ROI of Referral Programs)
Consumer-app program data in Impact.com’s 2020–2023 benchmark adds operational detail. These programs generated revenue directly from 81% of their conversion events. They automatically applied the reward at checkout in 43% of cases, and the average store-credit reward value was $35. Fraud-protection guidelines appeared in 43% of consumer-app programs.
The combined picture is practical: referrals can be trusted by buyers, rewards can influence both sending and accepting an invitation, and later referrals can materially change the value of the original acquisition. At the same time, the measures come from different studies, geographies, periods, and samples. The Australian findings describe consumers in Australia in 2024; the Impact.com benchmark describes programs observed from 2020–2023; Buyapowa’s page does not state its survey fieldwork date; and the AMA summary reports field datasets from 2024 in an article published in 2026.