Improve Your Business Performance: The Importance of Analytics in Ecommerce

Conversion rate optimization (CRO) and web analytics are two closely connected disciplines. You can't optimize effectively based on intuition alone without using data to support your assumptions. At the same time, if you only collect and review data in an analytics tool without using it to optimize your website or ecommerce funnel, you're missing many opportunities.

CRO is the process of increasing the percentage of conversions on your website or app by continuously improving the effectiveness of its pages and elements. For ecommerce businesses, a conversion may be a purchase, but it can also be defined as generating a lead, downloading content, or subscribing to a newsletter in the case of a publisher.

It involves identifying barriers to conversion and implementing changes to remove them. To find the best solution, CRO involves running experiments to test different versions of web pages or elements and determine which performs best.

It's not just about A/B testing. It's also about understanding how users navigate your website, which actions they take, and what prevents them from completing the desired actions. This is where web analytics plays a crucial role.

Web analytics is the practice of collecting, measuring, analyzing, and reporting web data to understand and optimize web usage. Using dedicated tools such as Google Analytics or Adobe Analytics, it involves tracking and analyzing various metrics—such as the number of website visitors, conversions, and revenue generated—to gain insights into user behavior, website performance, and the effectiveness of online marketing efforts. The goal of web analytics is to provide the data and reporting capabilities you need to make informed decisions and drive continuous improvement in your web strategies.

Based on the definitions of CRO and web analytics, we can see that these two disciplines are deeply interconnected. Below, we'll take a closer look at CRO in practice and the role web analytics plays at each step.

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Improve Your Business Performance: The Importance of Analytics in CRO

1. Research and analysis

The first step in the CRO process is to collect quantitative and qualitative data and analyze it to understand how users interact with your website or app.

For quantitative data, tools such as Google Analytics can tell you how many visitors certain pages on your website receive, how many are downloading content, and how many are moving toward completing a purchase. You can then see whether a significant number of shoppers stop at a specific step instead of moving through the funnel toward your desired end goal.

You can make your tracking as detailed as you want. For example, in addition to tracking conversions such as purchases, you may also want to see how many visitors view cross-sell products and add them to their cart, or how many visitors use a specific coupon code.

Quantitative data can tell you more about what visitors are doing on your website or app, while qualitative data can shed more light on why they take certain actions. For example, you can analyze click maps and heat maps for specific pages and watch session recordings to identify and better understand obstacles in the user journey. By combining qualitative and quantitative data, you'll gain a better understanding of what visitors are doing on your website or app.

This research phase wouldn't be possible without analytics. That's why it's important to have robust tracking based on your business goals before you start experimenting. You could say that analytics is the starting point of the CRO process.

2. Hypothesis development

Web analytics helps you identify areas for improvement on your website. Based on those findings, you can formulate hypotheses to test through A/B testing. Each hypothesis should propose a specific change expected to affect specific metrics, such as conversion rate or revenue per visitor.

Understanding web analytics will also help you choose the best metrics to measure the success of your test and determine whether your hypothesis is valid. For example, if you have a hypothesis about the design of cross-sell products, conversion rate may not be the most appropriate metric for validating it. Cross-sells can interfere with the purchase flow, but while your conversion rate may decrease slightly when you introduce them, revenue per visitor may increase. This is because shoppers may be more motivated to purchase additional products with your new cross-sell design.

3. Prioritizing hypotheses and tests

Evaluate the potential impact of each hypothesis on your key metrics and, ultimately, on your revenue if you run an ecommerce business. To make an informed, data-driven prioritization decision, you can use web analytics to forecast revenue. Use historical data for the metrics relevant to your hypothesis and model how much additional revenue you would generate if, for example, a metric such as revenue per visitor increased by 2%.

Estimate the effort and resources required to run the test and implement the change afterward. You can subtract the cost from the previously calculated revenue gain to determine the potential return on investment of your hypothesis if it proves successful.

Prioritize hypotheses based on their expected impact and required effort, focusing first on website changes with the highest potential return on investment.

4. Testing

The testing phase involves creating A/B tests or multivariate tests to compare the current version of a page (the control) with a modified version (the variation) based on the previously defined hypothesis.

Web analytics helps you set the right goals for measuring the performance of each variation in the test and ultimately declaring a winner. You'll need to establish a primary metric, such as revenue per visitor, that will determine the winning variation.

Depending on what you're testing, you may want to measure additional micro-conversions, such as how many times a product was added to a wish list, how many times a cross-sell product was added to the cart, and how many orders included cross-sells.

Before starting the A/B test, make sure you have the right tracking in place to measure all these micro-conversions. A/B testing tools give you the flexibility to set your own custom conversions and track the revenue generated by orders. However, to better understand how shoppers interact with each variation, you should also monitor the traffic from each test variation in the web analytics tool you use, whether that's GA, Amplitude, Adobe Analytics, or another platform.

This allows you to use all your custom dimensions and events to better understand why a variation is performing a certain way.

5. Analyzing tests and results

Continuously monitoring test performance in both your A/B testing tool and analytics tool gives you the opportunity to validate the data and have greater confidence in your experiment results.

The testing phase involves creating reports regularly. It also requires comparing the performance of the control and variation pages, using statistical analysis to determine whether the changes led to a significant improvement in the primary metric.

Web analytics can help you conduct detailed research to see how your test variations perform in specific countries, for specific products, or across certain traffic sources. Depending on the trends and results you observe, you may choose to implement different variations in specific markets.

6. Implementing the winning variation

Once the A/B test has reached statistical significance and you've identified the winner, you can implement the changes across the entire website. However, the web analytics work doesn't end there. You need to continuously monitor the performance of the implemented changes to make sure they deliver the expected results.

7. Continuous optimization

CRO is an ongoing process that involves regularly developing new hypotheses and running new experiments. As a result, using web analytics to research and gain insights into how visitors interact with your website is also an ongoing effort.

By using data from previous tests and monitoring and analyzing your website's performance alongside quantitative data from surveys, heat maps, and recordings, you'll have a steady stream of hypotheses to test.

Web analytics provides the data foundation that supports the CRO process. By working together, these two disciplines ensure that optimization efforts are data-driven, focused, and effective, leading to better user experiences and higher conversion rates and revenue. Using analytics effectively in CRO results in more personalized, efficient, and successful online interactions, benefiting both businesses and their shoppers.

Conclusion

Conversion rate optimization (CRO) and web analytics are essential partners in the pursuit of digital success. By harnessing the power of data-driven insights, businesses can transform their online presence, improve user experiences, and drive significant revenue growth. Web analytics provides the foundation for understanding user behavior, while CRO turns these insights into actionable improvements.

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