Checkout Funnel Analysis

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Introduction

No matter the industry, all webshops keep a close eye on the conversion rate. The reason is simple: a lot of effort goes both into marketing to get traffic to the website, and into UX design to make the website easy to use. With both activities, the end goal is to increase website purchases, and conversion rate (what percentage of website visitors end up buying a product from the website) has traditionally been a good metric for tracking that goal. Conversion rate (CR) can be defined in other ways, but since purchases are generally the most important actions on the website, we focus on these types of conversions for the purposes of this article. 

Naturally, we want the conversion rate to be as high as possible. But what is the upper limit? And how to get there? The funnel breakdown feature was developed to help answer these questions, and in this post, we analyze the checkout funnel on the website step-by-step, and offer insights into how to start making improvements. 

 

When dealing with difficult problems, it can be useful to break them down into smaller components, and then deal with each component individually. The difficult problem we are dealing with is getting the most conversions from all the link clicks we generate from Facebook ads. We consider this to be a relevant problem, as Facebook is a significant acquisition channel for many ecommerce businesses, and it’s in the interest of all Facebook marketers running webshops to get as many purchases as possible.

So, how can we break this problem down into smaller parts? After clicking our ad on Facebook, the user needs to enter our webshop through a landing page, add some product to cart, initiate checkout, and finally make a purchase. This can be visualized as the following 5 steps:

  1. Link click,
  2. Landing page view,
  3. Add to cart,
  4. Checkout initiated,
  5. Purchase.

This breakdown is useful for 2 main reasons. To start with, it’s general enough that it can be applied to most if not all webshops. The second reason is that Facebook tracks all of these metrics through the pixel on the website, so the data is available for analysis: if we are interested in how many “initiate checkout” events were in December 2020, we only need to look at the Business Manager.

Let’s assume for the purposes of discussion, that during a certain time range, Facebook reports the following values for these metrics:

 

Event

Link Clicks

Landing Page Views

Add to Carts

Initiated checkouts

Purchases

Count

1,103

1,002

294

93

43

 

The first thing to notice is that these events are decreasing in number, and this is actually what we expect: not all website visitors will add a product to cart as some will drop off. Each of these steps is a potential drop-off point for website visitors, so the number of visitors that reached a certain stage will decrease as we go from a link click to a purchase. This decrease in the number of visitors is the reason why such reports are called “checkout funnel analysis”.

 

Now that we have broken down the checkout process into specific steps, and have commented on how we expect the number of visitors to decrease, we can ask the question how much visitors are we losing on each step? And this is how the big problem of converting Facebook users that clicked on an ad has been broken down into a couple of smaller problems where we are interested in how many users are being lost on each step. Let’s remember that this was done in order to analyze each part of the funnel independently. To do this, we define the following ratios:

  1. Landing page view rate = landing page views / link clicks : out of all link clicks generated by the Facebook ads, how many users stayed on the website long enough for it to load.
  2. Add to cart rate = add to carts / landing page views: total number of add to cart events divided by the total number of Facebook users that stayed until the page was loaded,
  3. Checkout initiated rate: how many checkouts were initiated / number of add to carts events.
  4. Purchase rate: purchases / checkouts initiated: how many checkout initiated events end up with a purchase?

 

For the remainder of the document, we analyse each of these steps individually.

Landing Page View Rate

How is it defined

This is the first step of the checkout funnel, and is concerned with the difference between the total link clicks generated by Facebook ads and the number of website visitors that stayed long enough for the page to load. This first step might sound confusing, as it’s natural to equate the total number of link clicks with the total number of times the landing page was rendered (after all, the landing page is where the link click is leading to). By definition, link clicks on Facebook measure the total number of clicks to selected destinations (for example, landing pages). But someone might have clicked on the ad by accident, and leave immediately before the page was loaded. Or someone might have stayed on the website and waited, but the loading time for the landing page was too slow so the user went away. So in general, link clicks are not equal to landing page views as these examples illustrate. Furthermore, we saw that the difference can arise because of technical problems (loading time too slow) or because of wrong targeting (users misclicking on the ad, and bouncing from the website immediately).

 

So, even though 100% landing page view rate is hypothetically possible (implying that every link click on Facebook ad leads to a fully rendered landing page), some drop-off is to be expected, at least due to the reasons mentioned above. But even with these issues, the rate should still stay above 90%. If the landing page view rate falls below 90%, this should be inspected, because it has a significant impact on “real” CTR. 

Imagine that a certain ad has a CTR (for outbound clicks) of 1%. This is usually interpreted to mean that out of 10,000 impressions given, 100 users will click on the ad, and the website will have 100 visitors. But if the landing page view rate is only 80%, then only 80 out of 100 link clicks on the ad would result in a fully-rendered landing page, implying a “real session” rather than misclick. Taking into account that 20 people are lost due to page load time, the actual CTR is 0.8%, as there will be only 80 sessions on the website for every 10,000 impressions.

What to look for if the rate is below benchmark?
  • What landing pages are being used for ads? What are the load times for these pages?
  • Does the rate change significantly on campaign-level?
  • Which ad sets have the lowest rate? Who is the target audience for those ad sets?
  • How has this ratio changed over time? When was it the best? What kind of targeting was being used then? What about landing pages?

Add to Cart Rate

How is it defined?

Now, let’s move one step further down the checkout funnel, where we have a fixed number of website sessions (counted as the number of landing page views), and we are interested in what percentage of website sessions have triggered an “add to cart” event. 

The rate in this case is expected to be lower than it was in the previous step. This is expected because it’s more likely that a user will wait for the page to load if he had clicked on the ad, but it’s not the case that a user will add some product to the cart if he visited the page.

What influences the add to cart rate?

Unlike the landing page view rate, whose benchmark can be considered universal to a great extent (not impacted by the products on the website itself), the “add to cart rate” depends on the following four factors:

  • Average order value (AOV),
  • Ratio of new/returning customers,
  • Audience coming to the website
  • Website UX.

In general, the higher the average order value, the lower the “add to cart rate” is expected to be. It may take a while for the customer to make a decision to buy an expensive product, while the decision to a cheaper product can be made more easily. Similarly, a webshop where a lot of purchases are coming from existing customers will have a better add to cart rate than webshops where most of the transactions are from new visitors, as returning customers generally have significantly higher conversion rates. Furthermore, the type of audience coming to the website is still an important factor for the “add to cart” rate. When discussing the “landing page view rate”, we mentioned that the audience has great influence because if wrong targeting is being used, the users might quickly leave the website leading to the lower landing page view rate. Add to cart rate is another metric that can be used to determine if the targeting for advertising is appropriate. Users might visit your website, based on the ad they saw, have a look around, and realize that they misinterpreted the offering and leave. This is in line with the general advice in digital marketing that the landing page content should be consistent with the ad text and visual being used in advertising. This way, you can be sure that the users clicking on the ads are interested in the product.

Last, but definitely not the least, website UX has a high impact on all rates in the checkout funnel. A basic example would be the location of the “add to cart” button: Is it clearly visible or is it blended with the site (making it more difficult to locate). Is it below the price? Is it above the fold? A more complicated question regarding the website UX would be: what steps does the user have to go through to get from the landing page to clicking an “add to cart rate”? Can any of these steps be removed, to make it easier? In general, it’s good practice to have a call-to-action above the fold on the landing page. Page speed, mentioned in the previous step, also plays an important role: having smooth and quick transitions between pages can make for better user experience, which ultimately leads to better rates throughout the funnel.

There is one more important way in which website UX impacts the add to cart rate. If someone is to buy something from a website, they need to trust that website, as they will input their credit card and personal information needed for payment and delivery. Professional design can go a long way in convincing the potential customer that their data is secure.

What to look for if the rate is below benchmark?
  • How has this ratio changed over time? When was it the best? What kind of targeting was being used then? And what landing pages? Have there been any major changes to the website in the meantime?
  • What kind of targeting is being used right now?
  • What ads are being used? Are they representative of the products/offerings on the website?
  • Are the landing pages in-line with the ads?

Initiate checkout rate

How is it defined?

Add to cart events can be considered the first strong sign of purchase intent. The second strong sign is the start of the checkout process, during which payment and shipping info is being submitted. To calculate the initiate checkout rate, we start with the total number of sessions with “add to cart” events (so, sessions with explicit signs of purchase intent), and we are interested in what portion of these sessions had users continued to checkout.

What influences the initiate checkout rate?

It can be reasonably argued that all of the factors mentioned as impacting the add to cart rate also impact the initiate checkout rate. Initiate checkout rate is expected to decrease as AOV increases, as users might decide against buying an expensive item after seeing the price in the cart. Similarly, having a larger portion of new customers might also decrease the rate as new users in general have lower conversion rates then returning customers. Finally, audience selection is also important throughout the funnel, as some users just like browsing websites, adding items to cart, but not continuing with the checkout. While all of these may be true at least to some extent, the most important factor for the initiate checkout rate is the website UX:

  • The process through which users can proceed to checkout after adding a product to cart. Generally, it’s considered best to make this step as easy as possible.

Site reliability → same as with the add to cart rate, users are more likely to trust professionally made websites.

What to look for if the rate is below benchmark?
  • How has this ratio changed over time? When was it the best? Have there been any major changes to the website in the meantime?
  • What happens after users click “add to cart”? Are they notified that something was added to the cart?
  • How do users proceed to checkout after adding a product to the cart? Is the button immediately noticeable or do they need to visit the /cart page and then continue with checkout? Is the /cart page easily accessible?

Purchase rate

How is it defined?

This is the final step in the checkout process. If users continued with checkout after adding products to cart, how likely are they to end up purchasing the product?

What influences the purchase rate?

Similarly to the initiate checkout rate, the purchase rate is most influenced by the website UX. When creating a checkout process, the following should be kept in mind:

  • All expenses to the users credit card should be clearly communicated. If “free shipping” is offered under certain conditions, make sure that it’s clear who gets free shipping, and who doesn’t qualify. If a user expects free shipping, but ends up seeing shipping expenses during the checkout process, he might drop-off.
  • Messaging needs to be consistent throughout the website: if the product page promises shipping by a certain date, this should be the same in the “shipping” section of the checkout funnel.
  • Have as few pages in the checkout process as possible. Every new page is a potential drop-off point, so make sure you have a good reason for having an extra page.
  • Ask for only the most important information. You might want to ask your users questions about how they heard about the brand, or what made them purchase, but the checkout stage might not be the best place for that. During the checkout process, the focus should be on only one thing: finishing the purchase.
What to look for if the rate is below the benchmark?
  • How has this ratio changed over time? When was it the best? Have there been any major changes to the website in the meantime?
  • Is there any new information regarding taxes, shipping or other expenses being communicated to the user for the first time?
  • Are users required to fill any unnecessary or confusing information?
  • Can the checkout process be shortened?
  • Is the information in the checkout process consistent with messaging on the website?
  • Do users know why they are being asked to provide this information?
  • Is information security (shipping, billing information) being communicated to the user?

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