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Get an Instant Checkout Health-check With This One-stop Report

by Tim Leighton-Boyce

Screenshot showing Google Analytics Dashboard with Checkout Abandon RatesSee if anything is wrong with your checkout at a glance with this Google Analytics Custom Dashboard.

Important Update: September 2012 – Combine all data in one chart

If you have an ecommerce web site you know that the performance of the checkout is critical. If anything goes wrong with the checkout it will be costing you money.

That’s why first thing every morning, before I even look at the sales figures, I look at my clients ‘Checkout’ custom dashboards.

It gives me an instant health check. I can clearly see if something has gone wrong with any of the stages in the checkout, such as the payment gateway or the address lookup system. Or if something is wrong with a promotional offer codes and people who use it are unable to buy…

All I have to do is to take a quick look at this one-stop dashboard to see if any of the ‘sparkline’ charts has an unusual looking spike. I can instantly see if something is out of line, and exactly which part of the checkout has a problem. I really like reports like these. They’re what I call ‘read and react‘ reports.

Using Google Analytics to Monitor Checkout Abandon Rates at Each Stage (mp3)

Build a report like this and you’ll find it’s very powerful. You may already have read enough to know what to do, but I’ve explained how to do it below. Follow these instructions and you will be able to spot if there’s anything odd happening with your checkout by looking at one clear report.

Which means that… You can jump in and fix the problem before too much money has been lost.

How To Make Your Read and React Checkout Dashboard

The secret of this technique is to set up a sequence of Google Analytics funnels, one for each stage, and then build a dashboard showing the abandon rate for each of those funnels.

Screeenshot: how to set up Google Analytics goals for horizontal funnel from LunametricsThe idea of using a series of separate funnels has been around since 2010.

The technique is called building a ‘horizontal funnel’ and is mostly used to allow you to use segments with funnel abandon data. This idea was recommended in a Lunametrics article by John Henson: [link opens in a new tab]

The original concept involved using a Google Analytics Custom Report to present the information in a way which made all the important numbers easy to see, but it did not include any visualisation of the abandon rate from the different stages.

But now we can use GA Custom Dashboards to show all the individual abandon rates, trended over time, on a single screen.

Being able to spot the changes in the trend compared to normal performance adds the final touch which transforms ‘detailed analysis’ data into a ‘read and react’ operational report. You also get a bonus of being reminded of the relative abandon rates from the different stages so you can see where the friction points are.

Each time you look at this dashboard you can see what’s going on in a split second. You can instantly tell if you need to fix anything.

At peak periods it’s a good idea to check back later and set the date range to include ‘today’ so you can keep an eye on things.

Once you’ve tried this technique you can apply it in lots of ways. In the example here, I’ve extended the concept to show some extra very useful data which is relevant to checkout problems.

Screenshot: Checkout GA Custom Dashboard

In the first column I’ve got the ‘alarm bell’ step by step abandon rates. These are all ‘metric’ widgets which include the sparklines trend charts which are the key to this technique. I’ve arranged the widgets in order of the likelihood of trouble, not the real life order of the stages. You can just drag and drop them to suit your preference.

The middle column contains a ‘table’ widget which might also provide evidence of something odd, or at least interesting, going on with the checkout. It shows the overall checkout abandon rate by source/medium of the visit. I find it useful to be constantly aware of how some channels bring visitors who are far more motivated to make it all the way through the checkout than others.

In the third column I’ve got some ‘line chart’ widgets because they allow me to compare two metrics. In this example they are comparing the abandon rate from just the cart page with the abandon rate for the rest of the checkout. Or the abandon rate from just the cart page with the abandon rate of the checkout as a whole.

You could extend the idea behind the middle ‘table’ widget further. For example, on many sites it would be useful to have another widget showing the abandon rates from just the cart page, broken down by source. If your cart page contains an offer code box, for example, a sudden spike in the cart page abandon rate from one source is a strong indication that there’s probably a ‘bad’ code being promoted there. In that situation you can either create an extra version of the code which matches the one which people are trying to use, or try to promote the correct code via the same source.

In the video below you’ll see me building another variation on this layout. Once again the first column contains the ‘alarm bell’ sparklines, but the table widgets in the middle can be used to gain a wide range of operational insights which you can use to modify or correct promotional campaigns straight away.

You can include up to 12 widgets on each dashboard. What you choose to show in the tables should be decided on the basis of what you’re actually putting your resources into now. This is a living dashboard: you should change it to align with what matters now and what you can still change.

Can you see the theme there? This dashboard is not just a read and react tool for spotting technical errors. It’s also a very useful tool for getting an understanding of the motivation of the visitors from different channels. The biggest variations in checkout performance, in my experience, have very little to do with the technicalities of the site and everything to do with the strength of people’s desire to buy. Persuasion and motivation can have more influence on abandon rates than the position or wording of the ‘checkout now’ button.

The original Lunametrics post gives you excellent instructions on how to set up the sequence of funnels.

And this video shows how to use those funnels in a custom dashboard like the one above:

The example shows the abandon rates from a Magento one page checkout, as reported using the GoogleAnalyticsPlus Magento plugin from Fooman.

Updates on Checkout Abandon Rate Dashboards in Google Analytics

[September 2012] Major Update: Combine all your checkout abandon rates into one chart!

One of the problems with dashboard widgets is that you can’t control the y axis scale. This means that there’s no easy way of making a visual comparison if the abandon rates from different stages are widely different — for example 40% from the cart page, but 5% from delivery options.

An interesting way round this is to use the abandon rate data from your ‘horizontal funnels’ outside of GA itself, using the GA API.

Here’s an example of a chart which:

1) Uses the same y axis scale for all the abandon rates
2) Combines them all in one chart (even better)

Example of google checkout abandon rates by stage combined in one chart

For full instructions on how to do this see this Google Analytics blog post:

and here’s the video version

The metrics you need will be something like


where the goal number matches the actual goals you have configured on your site.

[January 2012] Someone has just pointed out that it can be extremely useful to look at checkout abandon rates by browser for each stage. At the moment there’s no easy way to do this in the dashboard itself. You can’t use Advanced Segments in dashboards. And even if you could, you really need to be able to segment by browser version, not browser, as this screenshot shows:

screenshot: google analytics cart abandon rate by browser

Having to configure each segment first and only being able to see four browser versions at a time would make using segments tedious, even if it was possible.

So the way I do this is to configure the widget to link through to a Google Analytics custom report containing a tab which allows me to see the abandon rate broken down by browser and then by browser version. I also have a tab showing a source/medium breakdown, which is the one I use more often.

You can import an example of such a report into your own GA profiles by logging into GA and then clicking this link:

This example shows the rates for two goals (14 and 15 in this case) so that it can be used as the link from two widgets. That suits the way I work. This is intended as an example to get you started: you must edit the report to show the goals which you have configured in the relevant profiles.

Resources for Horizontal Funnels and Custom Dashboards

{ 15 comments… read them below or add one }

Jeanette December 23, 2011 at 11:25 am

Thank you Tim for sharing this useful idea.
There’s a problem I see with forms.

GA considers a step as reached when the URL is executed. Given a form (registration, order, etc.) that comprehends several pages, this means that a step = a page is considered as reached, once the page is opened – and such before any fields in this page are filled by the visitor. One would normally consider this step as reached, once all fields are filled and after the user navigated to the next page of the form.

A way out is to use the measures of the following step. This provides the correct number for exits. For the exit rate although there is a problem for all funnels in which there are entries not only for the first step. GA takes the number of visitors from the previous step, adds the entries for the current step and puts the sum in the denominator. Such the numerator (exits) is referred to the “wrong” number (“correct” would be the number without entries of the current step) and results in a deceptive exit rate.

Such I’m using exits (numbers) in the dashboard but not exit rates.

Tim Leighton-Boyce January 3, 2012 at 12:40 pm

Hi Jeanette, thank you for raising these points. I think they’re covered in the discussions on the original Lunametrics, but you’re right: they should be included here too.

On your first point: the key is that each goal is the ‘next’ stage and is triggered when the visitor loads that page but before they fill in any data. The technique is based on reporting on the abandon rate from the ‘previous’ page to the goal page. Or the exits, if you prefer.

Taking the first two pages as an example (‘cart’ and ‘checkout start’ in the case of Magento One-page) the goal is the ‘checkout start page’ and the funnel is configured with one preliminary step: the ‘cart’ page. So the abandon rate is the drop off from the cart to the checkout start.

This goal could be described as ‘Cart to start abandonment’. In fact I tend to label these as something like “Cart to start abandonment [micro-funnel]” to make it very clear that these are special purpose goals and funnels.

On your second point: I agree that entrances to the goal page itself can be a problem. I’ve checked the original post and the point is discussed at some length there. I didn’t want to repeat that here, because I wanted to concentrate on how the introduction of Custom Dashboards makes this technique even more powerful. But you’re right: I should clarify it.

My personal approach to this issue is to always set the preliminary page as a ‘required step’ which should eliminate the entries to the goal stage from the abandon rate calculation.

I prefer trying to use the abandon rate rather than the count of exits for the dashboard because otherwise seasonal or promotional variations make it hard to spot the problems.

I’m glad that you’ve pointed out these potential problems. Working with funnels in Google Analytics is sometimes not a simple matter and so I think it’s useful to get discussion of the issues out into the open. The more we all talk about this, the better.

Jeanette January 6, 2012 at 10:06 am

Hi Tim, you are absolutely right that my questions concern more the post on lunametrics than your own one. All the more I thank you for your very thoughtful reply! Your answers are very much to the point and helped me a lot. Thanks! Jeanette

Tim Leighton-Boyce January 6, 2012 at 11:00 am

You’re welcome, Jeanette.

I think it’s interesting that even people very close to Google now seem prepared to refer to the GA Funnel Visualisation reports as ‘sub optimal’. I wish they would invest some time in improving them.

But I can also understand why it may make much more sense to put their efforts into new approaches which do not require configuration, such as the Flow reports and Intelligence.

Starting GA January 21, 2012 at 1:20 pm

Great article and helpful discussion. I tried to do exactly as oulined but still I have the same old problem.
The exit rates for the single funnels (consisting each of one step and one goal) are still considering the entrances to the goal page itself (as Tim expressed it) – although I set the preliminary page as a required step. Any idea?

Tim Leighton-Boyce January 23, 2012 at 10:41 am

That seems very strange. I’ve just looked at the Funnel Visualisation Report for a series of two-page micro-funnels of this type and I have not yet spotted any instances of any entrances being reported for the goal page.

Was the first stage configured as a ‘required step’ when the funnel was first set up? Are the goal-page entrances happening consistently every day? I often find it useful to look at very small date ranges, even just single days, when I am debugging things. It can help identify one-off glitches and problems with the data.

Starting GA January 24, 2012 at 11:34 am

Thanks Tim for your response.

No, at first the funnels were set up without “required step”. But I am only considering the time since I set “required step” (even giving some days).

Yes, there are frequently new goal and funnel page entrances and always there is exactly: Exit Rate
= exits / (entrances from preliminary page + entrances at goal page)

Would be great to get an idea where I should look next.

Tim Leighton-Boyce January 24, 2012 at 2:05 pm

This is very strange indeed.

Provided that the date range selected does not include any days on which the “required step” option was not enabled, I would not expect to see any entrances on the goal page itself.

Is this happening consistently, by which I mean for each of the last few days? I’m wondering if there has been some kind of unusual processing glitch at some point. Having said that, I would have thought we’d all have heard references within the GA community to such an issue.

Jeremy May 1, 2012 at 10:58 pm

Now that analytics dashboards can be shared, would someone care to share the dashboard created in this post?

Tim Leighton-Boyce May 2, 2012 at 9:36 am

Hi Jeremy,

Each of the widgets in the dashboard is specific to a funnel/goal combination and the choice of which to show will vary from site to site. The Titles for the widgets are also specific to the site itself.

So I don’t think there’s much point in sharing a link. But I will send you one privately so that you can see what I mean…


Kate June 28, 2012 at 9:49 pm

Hi Tim,

Can you share the dashboard? Thanks!

Tim Leighton-Boyce June 29, 2012 at 2:01 pm

Hi Kate,

Since these dashboards are based on goals and funnel abandon rates each one has to be configured on the basis of the relevant goals and funnels for the profile in question.

I doubt if you can save much time by using one of mine as a template. You could probably do it quicker by just starting over again.

But if you would like to see what I mean, here’s an example (it’s a random one, not the actual one I used in the original post):


Jorge Cunha November 2, 2012 at 3:32 pm

Hi Awsome content and very useful examples!

I am using and implementing customized dashboard for CXO and Marketing managers.

Contextual business data makes the difference!

Best Regards,

Jeanette December 14, 2012 at 8:57 am

Hi Tim, almost one year after my last question (on which you helped me a lot) here’s another one: which is the use of horizontal funnels since there are Goal Flow Reports? Well, using horizontal funnels you can show number of entrances and exits and the same in rates in GA reports – but the main reason why horizontal funnels were created at the first place – segmentation – can also be achieved with Goal Flows. Your ideas? Cheers Jeanette.

Tim Leighton-Boyce December 14, 2012 at 3:34 pm

Hi Jeanette,

These days I’m more excited by the use of this technique in order to produce dashboards, rather than for the segmentation abilities.

As Christmas approaches I have set up a scheduled email of that report for every day of the week. Each day it shows the last current week compared with the previous week and it’s very useful for keeping an eye on each stage of the checkout.

I’m also using the API more and more now. The metrics from these funnels are available there as well, which suits my way of working.

Although the various flow visualisation reports seem to have great potential, I’ve still not found a really good way of using them in everyday real life work. I spend even less time with Motion Charts, but at least in that case there’s a promising discussion taking place in the GA Google+ community:

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