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Referral Program

A referral program is a structured system for rewarding existing customers who bring in new customers, typically tracked through a unique referral link or code and paid out in credit, cash, or product perks.

What is a Referral Program? How to Design One That Works

A referral program turns your existing customers into an acquisition channel, and because the referrer is vouching for the product to someone they know, referred customers usually convert faster and churn less than customers acquired through ads. What makes a referral program work: a reward valuable enough to prompt action, a moment in the product where the user is happy enough to refer (right after a win, not at signup), and a frictionless way to share, one link, not a form to fill out. Two-sided incentives, rewarding both the referrer and the new customer, tend to outperform one-sided ones. Example: PayPal's early referral program paid $10 to the referrer and $10 to the new signup, an aggressive incentive that cost the company tens of millions of dollars but drove rapid daily user growth and helped PayPal reach critical mass before competitors could. Referral programs work best once you already have engaged, satisfied customers. Launching one before you have product-market fit just pays people to refer a product their friends will churn out of, which burns the reward budget without building lasting growth.

Examples

A B2B SaaS tool gives existing customers one free month for every paid referral who sticks around 60 days, tying the reward to retention rather than signup, so it only pays out for referrals that actually work.
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Related Terms

CAC (Customer Acquisition Cost)

CAC is how much it costs to acquire one paying customer. Calculate it by dividing total sales and marketing spend by the number of new customers acquired in that period.

Churn Rate

Churn rate is the percentage of customers who cancel their subscription in a given period. It's the silent killer of SaaS businesses—you can't grow faster than you're losing customers.

Network Effects

Network effects are a dynamic in which a product becomes more valuable to each user as more people use it. A product with strong network effects gets harder to compete with over time, because a challenger has to convince users to switch to a less valuable, less populated network.

Viral Coefficient

Viral coefficient measures how many new users each existing user brings in. A coefficient above 1.0 means exponential growth without paid acquisition—each user recruits more than one other user.

A/B Testing

A/B testing (split testing) means showing two versions of something to different users and measuring which performs better. Version A vs. Version B. Data wins, opinions lose.

Account-Based Selling

Account-based selling is a sales strategy that targets a curated list of specific named companies individually, tailoring outreach and pitch to each one, instead of casting a wide net across anyone who might vaguely fit.

View all terms