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How to run AB Testing for low volume traffic site

Donald Ng
June 4, 2023
5-star rating
Reviews on Capterra
How to run AB Testing for low volume traffic site

As the product owner, your primary goal is to convert visitors into customers or subscribers. A/B testing is a powerful technique to optimize your website's conversion rate, but what if you have a low traffic website? How can you perform meaningful A/B tests and improve conversions? 

It's a common concern that low-traffic websites don't have enough data for A/B testing. But, fear not - it's entirely possible to implement effective A/B tests with low traffic. In this article, we'll discuss how low traffic websites can still perform A/B testing, backed by stats, factual data, and industry practices.

Understanding A/B Testing

A/B testing (also known as split testing or bucket testing) involves comparing two or more versions of a webpage, email, or ad, determining which version performs better, and measuring their impact on desired metrics (e.g., conversion rates, click-through rates, or revenue). These tests help identify the most effective design, layout, content, or other elements contributing to your primary goal.

Why A/B Testing is Important for Low Traffic Websites

For low traffic websites, converting each visitor becomes even more critical. The underlying principle behind A/B testing - making data-informed decisions - is essential for websites with limited visitors, as it enables you to improve and optimize your website based on actual user behavior.

Challenges of A/B Testing for Low Traffic Websites

The challenge faced by low traffic websites stems from the reduced sample size, leading to slower results. Industry standards recommend having a specific number of visitors (sample size) for each test variant, depending on factors like baseline conversion rate, desired statistical power, and significance level.

Traditional A/B testing requires larger sample sizes to produce statistically significant results, but for low-traffic websites with a few hundred or thousand visitors per month, reaching this level may take weeks or even months.

To provide a rough estimate of the sample size needed, let's assume your website's current conversion rate (baseline) is 5%, and you want to detect a 20% increase in that rate. With a 95% confidence level (significance level of 0.05) and 80% power, you would need approximately 1,100 visitors per variation for your A/B test using a standard A/B testing calculator.

For low-traffic websites, gathering a sample size of around 1,100 visitors per variation might take longer, but it's essential to have a statistically significant sample to make accurate decisions.

Overcoming A/B Testing Challenges and Optimizing Conversion Rates

Fear not - it's still possible to perform A/B testing with low traffic websites. Here's how you can overcome these challenges and optimize for conversions:

1. Set realistic expectations: Smaller sample sizes mean that test results will take longer to achieve statistical significance, so be prepared to run tests for more extended periods. You may also have to adjust your expectations in terms of the minimum detectable effect.

2. Prioritize your tests: Focus on identifying and testing hypotheses with the highest potential impact on conversions. This can help you make meaningful improvements faster.

3. Run tests for longer durations: Since it takes longer for low-traffic websites to accumulate enough data for statistically significant results, be patient and run your tests for a more extended period.

4. Leverage alternative techniques: For low traffic websites, you may consider using alternative testing methods such as sequential monitoring, Bayesian statistics, or multi-armed bandit algorithms. These techniques allow for more flexibility in analyzing tests with smaller sample sizes but come with their pros and cons concerning accuracy, interpretability, and ease of implementation.

5. Optimize your traffic: While focusing on A/B testing, don't forget to keep working to increase your website traffic. More traffic means more data, faster results, and more significant improvements in conversions.


A/B testing for low traffic websites may seem challenging, but it's essential to make data-driven improvements to optimize conversion rates. By setting realistic expectations, prioritizing tests, running them for extended periods, leveraging alternative techniques, and continuously working on increasing traffic, website owners can maximize their conversion rates even with limited visitors. So, don't let low traffic hold you back from optimizing and improving your website – be strategic and data-driven to achieve the best results.

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