Running experiments on low-traffic websites can be challenging, but it's not impossible. By following these strategies, you can maximize your chances of success:
Reduce the significance threshold. Normally, you would aim for a 95% significance level when running experiments. However, with low-traffic websites, you can reduce this threshold to 80% or even 70%. This will allow you to run more experiments and identify potential improvements more quickly.
Be open to implementing changes with a positive but not statistically significant impact. Just because an experiment doesn't reach statistical significance doesn't mean it's not worth implementing. If you see a positive trend in the data, it's worth considering making the change even if it's not statistically significant.
Focus on high-impact changes. When you have limited traffic, it's important to focus on changes that have the potential to make a big impact on your conversion rate. This means testing changes that address your website's biggest pain points or that have the potential to attract new customers.
Use Bayesian analysis to analyze experiment results. Bayesian analysis is a statistical approach that takes into account the prior probability of a hypothesis being true. This can be helpful when running experiments on low-traffic websites, as it allows you to factor in your prior knowledge about the website's performance.
Iterate, learn, and adapt as you go. The world of experimentation is constantly evolving, so it's important to be willing to iterate, learn, and adapt as you go. This means being open to new ideas and strategies, and being willing to change your approach based on the results of your experiments.
By following these strategies, you can run effective experiments on low-traffic websites and identify potential improvements that can help you grow your business.
