Obviously, not everyone who lands on your ecommerce store is going to make a purchase. However, even people who are interested in your products might be put off by their experience on your site. Funnel analysis is a tool that helps you to understand the route users take before buying from you. That way, you can identify any bumps in the road that might stop them from completing an order.
Funnel analysis involves tracking customer behavior and creating a funnel chart to identify areas of friction where users may be dropping off in the purchasing process. By making improvements to these areas, you can smooth out the path to purchasing.
What is funnel analysis?
Funnel analysis is a type of data analysis used to analyze the paths taken by customers as they progress through the stages of a marketing or sales funnel in order to identify any areas of friction and improve conversion rates. It is commonly used to assess the effectiveness of an online marketing strategy, helping marketers determine how well their campaigns are performing and where they need to make improvements. In fact, sales/marketing funnel performance is one of the top metrics that marketers track.
It can also be used to identify areas of your website that are preventing users from completing a specific task or goal, like making a purchase. Funnel analysis enables brands to understand user behavior and optimize the user experience so that more people complete the desired action.
Types of funnel analysis
Funnel analysis is an invaluable tool for ecommerce brands looking to understand their customers and optimize the user experience. By analyzing customer behavior and creating a funnel chart, businesses can identify areas of friction that prevent users from completing a purchase. There are many different types of funnel analyses that can be used to gain insight into customer behavior and improve conversion rates.
The most common types of simple funnel analysis are:
Top-of-the-funnel (TOF): TOF analysis – or marketing funnel analysis – focuses on the first stage in a customer's journey, such as generating awareness or attracting visitors to your website. This type of analysis helps you understand what channels (for instance, social media) are driving the most traffic and which ones need improvement.
Mid-funnel: Mid-funnel analysis focuses on the second stage of the customer journey, such as engagement. This type of analysis helps you understand what content, pages, or marketing campaigns are engaging customers and leading them further down the funnel.
Bottom-of-the-funnel (BOF): BOF or conversion funnel analysis focuses on the final stage in a customer's journey, such as completing a purchase or signing up for a service.
Funnels in ecommerce
On an ecommerce site, funnel analysis examines the customer journey from landing on a product page to making an actual purchase. This could involve several stages, such as researching products on the site, adding items to the cart, proceeding to checkout, and ultimately completing the order. At each stage, there are multiple variables that can influence a consumer's decision to continue or abandon their purchase. Funnel analysis can be used to pinpoint what is stopping people from completing a purchase, allowing the ecommerce brand to make adjustments accordingly.
Benefits of funnel analysis for ecommerce sites
Funnel analysis allows brands to gain a deeper insight into customer behaviors and identify any points of friction in the user experience. That then means they can make necessary improvements to increase conversion rates.
It is important for ecommerce brands to understand their customers as well as possible so they can know how people are using their website and what might be causing them to leave without making a purchase. Funnel analysis is an important tool that helps ecommerce brands to get more information about customer behavior.
For instance, funnel analysis might reveal that customers reach your product pages, but many don't add anything to their carts. That teaches you that your customers need more information to feel confident about buying from you – you need to better highlight why your products are worth buying or add more info to your product pages. Or perhaps, the people you're attracting to the site aren't the right audience for your products.
Identify points of friction
When customers encounter a problem or issue at any stage of the funnel, it can significantly reduce the chances of them completing their purchase. Funnel analysis can help you identify these areas of friction so that you can optimize the user experience.
For example, if many customers add items to their carts but drop off before completing checkout, there may be an issue with the checkout process, such as a lack of payment options or a confusing interface. By analyzing the funnel data and identifying this area of friction, you can make changes to the checkout page and improve conversion rates.
Optimize for conversions
By understanding consumer behavior and identifying areas of friction in the user experience, ecommerce brands can make changes that will improve conversion rates. Optimizing for conversions will help ecommerce brands to maximize the value of each customer and increase their overall ROI.
Funnel analysis can also be used to A/B test elements of an ecommerce website. That analysis will help you identify the best design, images, and copy that lead visitors to take the desired route through your site and ultimately convert.
Read our guide to conversion funnel analysis
How to use funnel analysis to improve your ecommerce site
The first step in funnel analysis for ecommerce websites is to collect data on how users interact with your website. This can be done by tracking user behavior, such as what pages they visit, how long they stay on each page, and actions, such as adding items to their cart or completing a purchase.
Use a funnel analysis tool
Google Analytics is a popluar web analytics solution, but there are also various other specialized funnel analysis tools you can use, such as OptimizePress and Plerdy. Funnel analytics is slightly different in the Universal Analytics version of Google Analytics compared with the newer version (GA4). While UA does have 'enhanced ecommerce' features that allow you to specifically analyze things like checkout and shopping behavior in a Google Analytics funnel, they're tricky to set up. In the new version, you can build funnels based on the paths you think your users take and visualize funnel data in the platform.
The second step is to analyze the data you have collected and identify any areas where customers might be dropping off or having difficulty. Do this by creating a funnel chart. A funnel chart will show you how many users have progressed through each step of the funnel and where they drop off. This can help you pinpoint any points of friction in your website that may be preventing users from completing their purchases.
Once you have identified the areas of friction, you can make changes to improve the user experience and reduce abandonment rates. This could involve making minor adjustments, such as adding additional payment options or simplifying the checkout process.
The fourth step is to monitor the results of your improvements and determine if they are having a positive impact on conversion rates. Monitoring the data over time will help you determine if your changes are effective and identify any other areas of friction that may be preventing users from completing their purchase.
Get a comprehensive view of your ecommerce site
Funnel analysis is a great way to start to understand how people behave on your ecommerce site. But, to get a more comprehensive view, you'll have to go further and look at other analytics metrics. We've created a guide to help you understand more about website analytics – including key terms and best practices. Read Website Analytics 101.