What Is Your Conversion Funnel Analysis Telling You and What Should You Do About It?

The name of the eCommerce game is to increase conversions. Get more customers to purchase (or purchase more). You might be doing a fantastic job driving potential customers to your site with marketing and advertising, but if they don’t buy, you’re not getting value from your marketing spend. 

Customers don’t come to your site and instantly check out and pay. They typically go through five stages from when they land on your site to when they purchase. This is called the eCommerce conversion funnel. Analyzing the conversion funnel is trying to understand what compels or deters customers from moving from one stage to the next. This information is critical for helping you increase conversions.  

Understanding how your customers progress through these stages can help you identify problems, such as technical issues with your site, friction points in the customer experience, and opportunities for conversion funnel optimization from one stage of the funnel to the next. Even small increases in conversions between stages means lower CPA and CPO and higher ROAS—and potentially a big difference in revenue. 

Consumers typically go through five stages in their conversion path on an eCommerce site, from when they land on the site to when they complete their transaction. 

This post will help you understand how to do a conversion funnel analysis in order to both identify and fix issues in your conversion funnel. What should you look for in your analytics dashboard? What do these numbers tell you? How do you use this information to improve your business?  

What should you look for in your eCommerce analytics dashboard? 

You’ll want to do both a macro and micro conversion funnel analysis. First, you need to know your overall conversion rate.

Then, you’ll want to look at your conversion rates as customers move from stage to stage in the conversion funnel: i.e., 1) enter the site, 2) go to product pages, 3) add product(s) to cart, 4) reach checkout, and 5) purchase. 

Each stage in the conversion funnel indicates something about customer behavior. It’s up to you to figure out what. For example, you might see that customers aren’t adding products to the cart at the rate you would expect. Why not? Or, you might notice a surprisingly high abandoned cart rate. Why might that be?

In addition to total traffic, it can be insightful to break out your analytics several different ways to see if you can find patterns and trends that provide more information about what may be causing certain behaviors. A deeper understanding can lead to big improvements in conversion funnel optimization. For example: 

• By device: You may want to monitor conversions via mobile device versus desktop to see a clearer picture of where customers might be getting stuck or where you can optimize. Conversion rates are typically lower for mobile, but that’s changing. While the average add-to-cart rate is similar for mobile and desktop (Sale Cycle), there is a greater chance of friction at mobile checkout, where it can be more difficult to add shipping and payment information on a small screen. ‍
• By audience: Segmenting audiences, such as new visitors versus returning visitors, can give you more information about why a customer might exit the funnel or not convert. ‍
• By marketing channel: It can be helpful to analyze conversions at each stage of the funnel by how customers came to your site. You can see if different channels bring in better traffic that converts at a higher rate and has a lower CPO; use different attribution models to see different views of this data. 
  

What do these numbers tell you?

How do you analyze a conversion funnel? It isn’t useful to judge your numbers as good or bad (though really low conversion rates are generally bad, let’s be real). What’s really key to look at are trends. Are your conversions getting better or worse over time, especially as you add more traffic? 

At a macro level, if you look at conversion rates at each stage in the funnel over the last thirty days versus the last six months, is this month better or worse than last month? What about compared to the same time a year ago?

At a micro level, look at trends to identify problems—specifically, where you see a significant drop-off between stages. For example, you may see that customers aren’t adding products to the cart. Or they add products to the cart but don’t check out. Although your average conversion rates between each stage will be specific to your brand (i.e., dependent on factors like industry/sector, product/service, pricing, etc.), you generally don’t want to see huge changes or drop-offs from one stage to the next.   

If you do see significant drop-off, that means it's time to investigate. Is there a technical error in how you have your funnel set up in Google Analytics (e.g., an invalid link or a missing page)? Is something broken on a web or mobile page? Those issues can be quickly fixed. If that’s not it, you have to dig deeper. 

How do you use conversion funnel analysis to improve your business? 

Digging deeper means figuring out how to optimize your site to reduce drop-off between stages in the funnel and increase conversions. There are many factors that could be affecting conversions. Some are simple, while others can be more complicated. 

To start, pick the most likely culprit that could be causing the issue, and form a hypothesis, such as: 

• Changes were made to the UI, pricing, or marketing content
• Product photos aren't clear enough or of a high enough quality
• Site loading speeds are slow
• Promo code(s) are not working, or not working as expected
• Product was out of stock so customers couldn’t add to cart
• Customers are surprised by shipping costs, tax, and fees in the cart
• Customers expect free shipping but don’t get it
• Something on the mobile checkout page is broken
• Customers can’t read the product page on mobile
• Checkout is too complicated
  

Once you form your hypothesis, you have to test it. Use testing software to run A/B tests (e.g., make changes to forms, buttons, colors, calls to action, etc.) and see if your conversion rates improve. You can also use tools like heatmaps to enhance your understanding of your customers' experience on your site.

In the Daasity dashboard, we give our merchants high-level suggestions for conversion funnel optimization. For example, if you see low conversion rates, you can check the following visualization to see the stage where people may be leaving:

An ongoing conversion funnel optimization process 

It’s a good idea for DTC brands to analyze their conversion funnel at least monthly—and maybe weekly, depending on the size of your business. The bigger you are, the more impact small conversion funnel improvements will have on total revenue. 

If you’re using our recommended metrics six-pack, it will help you keep on top of potential issues day-to-day because issues likely will result in a drop in the overall conversion rate. If you see that red flag, it’s time to go take a closer look at the conversion funnel metrics. 

Daasity saves you time and makes it easy for you to dig deeper into your conversion funnel analysis by providing segmentation by marketing channel and customer, in addition to the basic conversion funnel metrics you get in Google Analytics. If you're interested, let us show you! Contact us for a demo.