Transaction testing, which focuses on increasing the rate of purchases, is a crucial strategy for boosting your website’s revenue.
To begin, it’s essential to differentiate between conversion rate (CR) and average order value (AOV), as they provide distinct insights into customer behavior. Understanding these metrics helps you implement meaningful changes to improve transactions.
In this article, we’ll delve into the complexities of transaction metrics analysis and introduce our new tool, the “Report Copilot,” designed to simplify report analysis. Read on to learn more.
Transaction Testing
To understand how test variations impact total revenue, focus on two key metrics:
- Conversion Rate (CR): This metric indicates whether sales are increasing or decreasing. Tactics to improve CR include simplifying the buying process, adding a “one-click checkout” feature, using social proof, or creating urgency through limited inventory.
- Average Order Value (AOV): This measures how much each customer is buying. Strategies to enhance AOV include cross-selling or promoting higher-priced products.
By analyzing CR and AOV separately, you can pinpoint which metrics your variations impact and make informed decisions before implementation. For example, creating urgency through low inventory may boost CR but could reduce AOV by limiting the time users spend browsing additional products. After analyzing these metrics individually, evaluate their combined effect on your overall revenue.
Revenue Calculation
The following formula illustrates how CR and AOV influence revenue:
Revenue=Number of Visitors×Conversion Rate×AOV
In the first part of the equation (Number of Visitors×Conversion Rate), you determine how many visitors become customers. The second part (×AOV) calculates the total revenue from these customers.
Consider these scenarios:
- If both CR and AOV increase, revenue will rise.
- If both CR and AOV decrease, revenue will fall.
- If either CR or AOV increases while the other remains stable, revenue will increase.
- If either CR or AOV decreases while the other remains stable, revenue will decrease.
- Mixed changes in CR and AOV result in unpredictable revenue outcomes.
The last scenario, where CR and AOV move in opposite directions, is particularly complex due to the variability of AOV. Current statistical tools struggle to provide precise insights on AOV’s overall impact, as it can experience significant random fluctuations. For more on this, read our article “Beyond Conversion Rate.”
While these concepts may seem intricate, our goal is to simplify them for you. Recognizing that this analysis can be challenging, we’ve created the “Report Copilot” to automatically gather and interpret data from variations, offering valuable insights.
Report Copilot
The “Report Copilot” from AB Tasty automates data processing, eliminating the need for manual calculations. This tool empowers you to decide which tests are most beneficial for increasing revenue.
Here are a few examples from real use cases.
Winning Variation:
The left screenshot provides a detailed analysis, helping users draw conclusions about their experiment results. Experienced users may prefer the summarized view on the right, also available through the Report Copilot.
Complex Use Case:
The screenshot above demonstrates a case where CR and OAV have opposite trends and need a deeper understanding of the context.
It’s important to note that the Report Copilot doesn’t make decisions for you; it highlights the most critical parts of your analysis, allowing you to make informed choices.
Conclusion
Transaction analysis is complex, requiring a breakdown of components like conversion rate and average order value to better understand their overall effect on revenue.
We’ve developed the Report Copilot to assist AB Tasty users in this process. This feature leverages AB Tasty’s extensive experimentation dashboard to provide comprehensive, summarized analyses, simplifying decision-making and enhancing revenue strategies.
