How do you test and validate your referral hypotheses and assumptions?

1 Identify your referral goals and metrics

Before you start testing your referral hypotheses and assumptions, you need to define your referral goals and metrics. What are you trying to achieve with your referral program? How will you measure your success? For example, you might want to increase the number of referrals, the conversion rate of referrals, the retention rate of referred customers, or the lifetime value of referred customers. You also need to choose the right metrics to track these outcomes, such as referral rate, referral coefficient, referral revenue, or net promoter score. Having clear and relevant goals and metrics will help you focus your experiments and evaluate your results.

2 Generate your referral hypotheses and assumptions

Next, you need to generate your referral hypotheses and assumptions based on your customer research, your value proposition, and your referral program design. A hypothesis is a testable statement that expresses a causal relationship between a variable and an outcome. An assumption is a belief that you have about your customers, your product, or your market that needs to be validated. For example, you might have a hypothesis that offering a free trial to referred customers will increase the conversion rate of referrals, or an assumption that your customers value social recognition more than monetary rewards. You should prioritize your hypotheses and assumptions based on their impact and uncertainty, and choose the most important ones to test first.

3 Design your referral experiments

Once you have your hypotheses and assumptions, you need to design your referral experiments to test them. An experiment is a structured way of testing a hypothesis or an assumption by changing one variable and measuring its effect on another variable. You should follow the scientific method of setting up a control group and a treatment group, defining a clear and measurable outcome, and running the experiment for a sufficient duration and sample size. For example, you might run an experiment where you split your customers into two groups: one group gets a free trial offer for referred customers, and the other group gets the regular offer. Then you measure the conversion rate of referrals for each group and compare them.

4 Analyze your referral data

After you run your referral experiments, you need to analyze your referral data to see if your hypotheses and assumptions are validated or invalidated. You should use statistical methods and tools to analyze your data, such as descriptive statistics, inferential statistics, or data visualization. You should also look for patterns, trends, outliers, or anomalies in your data that might reveal insights or opportunities for improvement. For example, you might analyze your data and find out that offering a free trial to referred customers does increase the conversion rate of referrals, but only for certain segments of customers or certain types of referrals.

5 Learn from your referral results

The final step is to learn from your referral results and use them to improve your referral program and value proposition. You should document your learnings and share them with your team and stakeholders. You should also use your learnings to generate new hypotheses and assumptions, or to refine or pivot your existing ones. You should also use your learnings to implement changes or improvements to your referral program, such as adding new features, incentives, or channels. For example, you might use your learnings to create a more personalized and targeted referral offer for different customer segments or referral sources.

6 Repeat the referral process

Testing and validating your referral hypotheses and assumptions is not a one-time activity, but an ongoing process. You should always be testing new ideas, challenging your assumptions, and learning from your data. You should also monitor your referral performance and feedback regularly, and adapt to changing customer needs and expectations. By following this simple framework, you can optimize your referral program and increase your word-of-mouth.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?