The Most Important A/B Tests to Run in 2025: Our Research Revealed

We analysed over 9,000 A/B tests from 800 businesses to discover which types of experiments really boost referral performances. 

By tweaking aspects like the text, rewards, and images in referral offers — and measuring results when tests were statistically significant — we now know the most impactful tests to run in 2025.

We also used Generative AI to analyse parts of our referral offer designs, combining these findings with our historic A/B test results to see which imagery captivates customers the most.

So, which design elements spark referrals? Are simple offers or detailed promotions better for acquiring new customers? 

Read on to find out…

Key Findings: Most Impactful Tests

Our A/B testing experts revealed distinct patterns that impact conversion rates across different industries and types of experiments. Watch our 3 favourite stats from the research below, then read on to see which experiments caused the biggest uplifts.

Our top pick stats

1. 62% of the time, white background offers win vs non-white designs. (1.6x more likely).

2. 60% of the time, human-focussed designs lose vs designs without humans. (1.5x more likely).

3. 59% of the time, product-focussed offers win vs non-product-led designs. (1.4x more likely).

Incentive experiment types results

These are the big hitters. As a median, incentive-based tests boosted conversion rates by an impressive 91%.

For incentive-based experiments, testing scenarios like minimum spend versus no minimum spend, and percentage discounts versus flat amounts, lead to the highest uplifts.

Design experiment types results

Never underestimate the power of good design. Our findings show that imagery that focused on the product can significantly boost engagement vs simply showing a person or lifestyle image, especially in industries like fashion.

We also found that simple, bright, and higher contract images perform better than complex, darker, low contrast images.

Copy experiment types results

Words matter. I’m not just saying that as a copywriter. For A/B testing, concise vs. descriptive language and different lead flows (referee-led vs. referrer-led) produces the highest uplifts.

Sharing experiments results

How do your customers want to physically share referral offers? The list, and particularly the order, of sharing options can have a huge impact.

In our research, we saw the highest sharing rate uplifts when customers adopted Name Share® and placed it first in their share option list.

Key Findings: Most Impactful Metrics

On average, you’ll see the best performance when you run at least five A/B tests. You’ll likely see the uplift much earlier — most likely after the first or second test — but your performance should continue to increase until the fifth experiment.

But which metrics should you measure for success? In our testing, we looked at:

1. Share rate: This tells you how often users spread the word about your offer. Test different messages or incentives to see what gets people talking.

2. Conversion rate: This is the percentage of users who take the action you want, like signing up or buying. Test elements like button text or page layout to boost this number.

3. Purchase rate: This measures how many referrals actually make a purchase. Tweak offers and checkout processes to see more buys.

Our research shows that these metrics improve significantly with continuous testing. 

Key Findings: Industry-Specific Results

From our results, we know that impactful A/B testing varies depending on the industry. Here’s what we found:

- Home, Pets, and Garden: Incentive-led experiments are by far the most impactful.

- Fashion: Design-led experiments are the most impactful, followed by incentive experiments.

- Health and Beauty: Incentive is the most impactful, followed by design.

- Food and Drink: Incentive is easily the most impactful.

Importance of A/B Testing in Referral Programmes

A/B testing is vital to running a successful referral programme — on average, our top-performing brands acquire 4x new customers in just six months of continuous testing. 

Why? Because A/B testing allows you to experiment and fine-tune. Whether you test offers, visuals or messaging, there are many ways to see what actually motivates customers to share and refer friends.

We’ve got the research to prove it.

Tips for Effective A/B Testing

Thought the priceless insights stopped there? Think again. We’ve got a couple quick tips to help you run better, more insightful A/B tests than ever before.

For more A/B testing advice, check out our video or read our blog on the top A/B testing mistakes to avoid.

1. Run simultaneous control and test segments: Ensure that your control and test segments occur at the same time to prevent external factors, such as economic changes or seasonal effects, from skewing your results.

2. A/B test by cohort: Display one variation to a specific group while showing a different version to another group simultaneously provides accurate insights into which variant resonates best with your audience without disrupting their experience.

Conclusion

Our research revealed how A/B testing can redefine the way you design your referral marketing campaigns. We know which tests produce the greatest impact across key industries and how they can introduce enormous improvements in customer acquisition and engagement. 

Let’s recap…

Incentive-driven tests drive the highest impact within the Home, Pets, and Garden industry. In Fashion, design-driven tests were most influential, closely followed by incentive tests. 

Our Health and Beauty results show incentive tests come out on top, with design changes close behind. Finally, incentives came in first for Food and Drink when trying to persuade customers to take action.

Ready to turn insights into action? Start A/B testing now and kickstart 2025 with KPIs and results to be proud of. Contact your account manager today.