- What is Referral Rate?
- How Does Referral Marketing Work?
- How to Structure a Referral Program
- How to Track Referral Conversion Rate
- How to Calculate Referral Rate
- Referral Rate Formula
- Referral Marketing vs. Affiliate Marketing: What is the Difference?
- Referral Rate Calculator â Excel Template
- Referral Rate Calculation Example
What is Referral Rate?
The Referral Rate is the percentage of new customers acquired via referred purchases through recommendations made by existing customers.
By tracking the referral rate—the proportion of new customers acquired from referrals from existing customers relative to the total number of new customers—a company’s marketing team can determine the effectiveness of a referral marketing program.
- The referral rate measures the percentage of new customers acquired via “word-of-mouth” marketing by existing customers.
- The calculation of the referral rate yields a percentage that reflects the effectiveness of a referral program.
- A higher referral rate percentage implies a more effective referral program since more referral conversions occurred in the given period (and vice versa).
- The target outcome of a referral program is to create a customer acquisition funnel where existing customers promote the product or service organically.
How Does Referral Marketing Work?
The referral rate is a metric used to determine the effectiveness of referral strategies and better understand which promotional incentive resonates with the target end market.
The referral rate is of particular importance in industries where word-of-mouth marketing significantly contributes to customer acquisition strategies.
First and foremost, the company must offer a product that satisfies the needs of its customer base to establish an effective and successful referral program and marketing campaign.
In short, the perceived value received from a customer’s perspective must be sufficient for it to be worth sharing with their network of friends, family, and co-workers.
If the aforementioned condition is not met, the company should return to the drawing board and shift its focus to its existing customer base instead of employing tactics to convince them to promote on their behalf.
The optimal outcome of a referral program is to convince existing customers to share and promote the product to their friends, family, and colleagues at scale via word-of-mouth marketing.
In effect, the company incurs fewer costs to acquire new customers, contributing to more from the increase in satisfied customers and more cash on hand to allocate toward product development and market research.
Why? The less reliant a company is on its internal marketing efforts, the better, as the burden placed on the sales and marketing (S&M) team to facilitate sales and expand brand recognition reduces.
Referral Program Example (Source: Dropbox)
How to Structure a Referral Program
The standard structure of an effective referral program comprises offering existing customers an incentive to improve the odds that more customers will promote the product to their network.
Therefore, the value of the product by itself is not enough. While certain customers who are satisfied with a particular product or service will indeed discuss it positively with their network, other customers need to be handed an incentive post-purchase, too.
While a broad range of potential referral incentives can be offered, the most common type is a reward-based system. For example, a company could offer $100 in credit per referral conversion to each of their existing customers.
The one risk inherent to offering an incentive to existing customers, however, is that the promotion can easily come across as “inorganic” if the message comes across as an artificial method to benefit themselves.
In such cases, the referral promotion can cause reputational damage to the company, creating the necessity to ensure that such behavior is penalized.
For instance, referral links with a unique discount code repeatedly shared across social media, like reddit, can be perceived as spam-like conduct to potential customers, causing the promotion to be viewed as disingenuous (and devalue the company’s branding).
Why is Word-of-Mouth Marketing Effective?
The promotion of the product or service seemingly “takes off on its own” in word-of-mouth marketing, resulting in significant cost savings for the company.
The value of word-of-mouth marketing and a robust referral network stems from the fact that the promotion is deemed “organic.”
In other words, there is pre-existing trust between existing customers and their respective network, hence the higher conversion rate with regard to generating referrals, especially if more than one customer mentions the product in a positive sentiment to the same person.
Hence, an increase in word-of-mouth marketing and strong referral rates is often viewed as an indicator of product-market fit (PMF).
How to Track Referral Conversion Rate
The referral rate of a company can only be tracked at the macro level, and much of the campaign’s effectiveness is out of the company’s control.
Of course, the company can structure the campaign to be optimal, but most of its influence drops off once it is actively running. Instead, the existing customer base becomes responsible for the effectiveness of the implemented plan, which a company cannot (and should not) attempt to dictate.
The referral rate reflects how persuasive and influential the existing customer base is, which is a variable that cannot be directly altered from the company’s perspective.
Nonetheless, a company should still track the average referral rate, perhaps segmented into cohorts – albeit the constraints within the data set must be understood.
For example, a company that sells products online could implement measures to track the number of clicks on a specific user’s shareable link via UTM parameters but not the total number of people in their network that viewed the link.
On the other hand, a company that sells physical products at in-person stores could have close to no data to work with (i.e., a referral sale could occur without the company or even the referrer themselves being aware of the transaction).
In 2024, the rising usage of automated discount code finders, such as Honey, and the controversy around privacy and cookies can further complicate matters (and skew data).
Automated Coupon Finder — Chrome Browser Extension (Source: Honey)
How to Calculate Referral Rate
The method by which the referral rate is measured and periodically monitored is contingent on the campaign’s structure.
In order for the referral rate to provide practical insights, a systematic approach must be implemented to collect customer data.
At the bare minimum, the capability to track the number of new customers acquired over a specific period and separate the new customers referred by existing customers from those brought in through other marketing initiatives is needed.
The referral process also requires setting up systems and tracking parameters to record referral conversions, such as referral codes, unique tracking links (i.e. UTM parameters), or customer surveys that specifically ask new customers about how they heard about the business in the first place.
By analyzing the collected customer data and insights, businesses can determine the proportion of new customers coming from referrals, thereby measuring the success (or failure) of specific referral programs.
Companies often incentivize referrals by offering rewards, discounts, or exclusive offers to those who successfully refer new customers. In such cases, the total number of conversions is much more reliable since there is a straightforward method to track the referral sales.
The most common method most companies use to track the number of referral conversions is to calculate the ratio of the number of referrals and new customers acquired to the total number of transactions that occurred in a given period.
The steps to calculate the referral rate are as follows:
- Step 1 ➝ Count the Number of Referral Sales
- Step 2 ➝ Count the Total Number of Transactions
- Step 3 ➝ Divide the Number of Referral Sales by Total Number of Transactions
- Step 4 ➝ Multiply the Result by 100 to Express in Percentage Form
Referral Rate Formula
The formula for calculating the referral rate consists of dividing the number of referred customers by the total number of new customers.
Where:
- Number of Referred Customers ➝ The number of conversions where the source is identified to be an existing customer (e.g. unique discount code was applied at checkout)
- Total Number of New Customers ➝ The total number of new purchases that occurred in a given time frame, inclusive of referral and non-referral sales.
For example, a company with a 5% referral rate in the past month implies that 50 purchases out of 1,000 in total were facilitated through its referral program.
Referral Marketing vs. Affiliate Marketing: What is the Difference?
On the subject of referral marketing efforts and affiliate marketing initiatives, the two strategies are distinct yet often conflated strategies within digital marketing. Both methods aim to leverage external partners to drive sales or generate leads, but each tactic operates differently and serves different purposes.
By understanding the nuances between the two customer acquisition strategies, businesses can employ the strategy considered most appropriate (and with higher conversion rates).
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Referral Rate Calculator — Excel Template
We’ll now move to a modeling exercise, which you can access by filling out the form below.
Referral Rate Calculation Example
Suppose the marketing division of an eCommerce company is tasked with reviewing the effectiveness of its current initiatives to drive referral sales.
In Q1–2024, the total number of new orders was 20k, of which 400 were referrals by existing customers.
By inserting the number of referral orders and total new orders into the referral conversion rate formula, we can calculate the referral rate as 2.0%.
- Referral Rate (Q1–2024) = 400 ÷ 20,000 = 2.0%
In response, the marketing team decides to increase the referral incentive from a 10% discount to a 20% discount starting in Q2–2024.
The outcome? The total number of new orders was 25k, of which 1k were referrals by existing customers.
- Referral Rate (Q1–2024) = 1,000 ÷ 25,000 = 4.0%
Therefore, the referral rate increased two-fold from Q1-24 to Q2-24 after the increase in the discount incentive offered to new customers.
The company’s net sales grew from $1,996,000 in Q1-24 to $2,480,000 in Q2-24, a quarterly growth rate of 24.2%.
- Net Sales (Q1-24) = [$100.00 × (1 – 10%)] × 20,000 = $1,996,000
- Net Sales (Q2-24) = [$100.00 × (1 – 20%)] × 25,000 = $2,480,000
- % Differential = 24.2%
Of the company’s net sales, the portion attributable to referral sales increased from $36k to $80k.
However, the trade-off is that the eCommerce store’s average selling price (ASP) is reduced.
For illustrative purposes, we’ll assume that the average selling price (ASP) was $100.00 per product in both periods.
The gross sales, which excludes discounts, were $2 million in Q1-24 and $2.5 million in Q2-24.
- Gross Sales (Q1-24) = $100.00 × 20,000 = $2 million (Net Loss = $4,000)
- Gross Sales (Q2-24) = $100.00 × $25,000 = $2.5 million (Net Loss = $20,000)
The net loss from the increased discount offered as part of the updated referral program increased from $4k to $20k from Q1-24 to Q2-24.
However, note that the net loss is not an actual loss incurred (i.e., foregone income), whereas the improvement in net sales is tangible.
In closing, the effectiveness of the referral program seems to have improved substantially from a birds-eye view, considering the referral rate doubled while net sales grew by 24.2% from the prior quarter.
However, a comprehensive analysis of the referral program benchmarks the company’s historical data, and operating performance is necessary to determine if the referral program improved and if the trade-off was a profitable decision worth continuing.
