Over my career, I have lost count of the number of migrations I have worked on, and one problem frequently comes up, the dreaded problem of attribution. Even worse, the temptation to compare the analytics from different projects and implementations. However, it is vital to remember that there is nearly always a huge difference between migrations, meaning they can never easily be compared, nor create like for like data.

Here, I will explain just how you can use analytics, and how to avoid common traps when looking at your migration data.

The attribution issue

So often, and for multiple reasons, source attribution fails. Because of this, it is always important to make sure you are attributing to the correct source, or you will come up against issues with Google - such as redirects stripping off UTM parameters, the GCLID tracking parameter or the referral information from the source. To avoid this, just test the redirects and make sure the correct information carries through. It’s an easy process, and can save a whole lot of trouble should anything be wrong.

Testing for attribution issues

To test your redirects effectively and quickly, append the following to the url you want to test:


If the new (redirected) URL doesn’t have these additional parameters, potential traffic won’t either. It’s always worth testing this in a test environment, but always test it in the live environment as well to ensure everything is working when live.

Repeat this process with the append ‘gclid=123’ to test for the automated parameter. I’d also recommend testing this on a page that you know has a parameter already, to make it evident if anything is wrong. When testing on a page with an existing parameter, you’ll need to change the URL since a URL should only have one question mark in it, use ‘&utm_source=’ and it should all work perfectly.

When testing to see if the redirect strips the referrer, I’ll use some basic JavaScript in the URL bar:


This will tell you what page initially referred you, or at least what is being tracked in JavaScript. This is what analytics packages can read before adding additional tracking parameters.

One other common issue is that, often, clients choose a new or different analytics property when migrating. By doing this, it makes it more difficult to compare side by side after the move of the site, especially if there are subtle differences in the configuration.

Payment gateways and social logins

Another reason why attribution issues can occur is because of payment gateways and social logins. These are often missed in testing, but if you find that returning Google organic has a very high conversion rate when compared with paid, or that Facebook is suddenly converting far higher than ever before - this could be a social login and if banks and PayPal are suddenly converting highly payment gateways are often the issue.

To resolve this, check in your referrals for PayPal, banks and credit cards, look at Facebook and Google landing pages - problems with payment gateways can be easily fixed by adding to your referral exclusion list, however excluding Google and PayPal can create problems. If you have a journey which crosses subdomains, this isn’t usually an issue - but it’s still worth watching out for.

Implementation of analytics

There are plenty of ways to implement your Google Analytics - Code on the page, the version of the code, and if using GTM where this is placed can all have an impact on the percentage of users that are tracked accurately. Some analytics folk have noticed that between the results of GA in your code and GA injected with GTM, there can be up to a 10% difference.

The speed your analytics loads and how many users are tracked (especially slower mobile users) can have quite an impact . The Analytics and CRO Manager at Rise at Seven, Stacey Harper, said it better than anyone:

“It is inevitable you will see changes in data following a migration; it may highlight inaccuracies you were not aware of in your previous set up. Use it as an opportunity to ensure your data collection is as accurate as possible moving forward.”

Site changes

Another key issue is that, inevitably, your site will change after a migration. This is normally the whole point of a migration and any issues will hopefully be improved once it’s complete. If interactions are changed, particularly the ‘added to basket’ stage of a journey (from a seperate page to an event) this can significantly impact your site metrics, such as bounce rate and tracking of pages per session.

Amp is one key change, either the removal or addition of it, there are so many ways this can impact your data, Dan Smullen has incredible experience of this doing this as the Head of SEO for mediahuis.be

"Really important to audit before migrating to or from AMP. As if the AMP linker is not used, it will appear there are now two new users recorded for every actual user. And of course, if the session is not connected via the AMP linker this is going to artificially inflate your bounce rate." @dansmull

So what’s the point of analytics?

It’s important to be looking at your data before, during and after a migration in your analytics. I’d be lying if I said it wasn’t. However, it’s also key to remember that migrations will affect how your data is collected and analysed. I want to stress that you aren’t always comparing apples with apples here - instead, you are comparing your old website with, hopefully, a new and improved version, where even small changes can impact how users interact with your site. By understanding this, you will not panic when your bounce rate increases, or celebrate too quickly if the conversion rate goes up.

Useful data sources for validating your findings

Other data sources are also important to look at when working on a migration. For those in SEO, Webmaster Tools (Bing and Google Search Console) can be very helpful, but unfortunately this data can often be a couple of days behind.

Your paid channels also have their own reporting areas (such as Adwords), and these should be checked just as much as Google Analytics. The two can be used to validate each other - but don’t expect clicks, sessions and conversions to match as they are fundamentally different metrics with different attribution methods.

I’d also pay close attention to services such as Sistrix, SEMrush and a rank checking tool such as Rank Ranger, as these can spot where your visibility has dropped, and in what.

Double check and audit your analytics as much as possible, using tools such as ContentKing or Screaming Frog, to ensure all your pages have analytics. If you want to go a little further (good on you), check out Observe Point to really validate your findings.

When it comes to advice on validating your data after a migration, there’s no better person to take it from than our Senior International SEO Lead, Lidia Infante:

“A good way to streamline your data validation efforts after a migration is to establish a clear benchmark of your current performance. Identify your conversion funnel and it’s key metrics, select a handful of money pages that you are going to track and focus on a few KPIs. This will help you identify any issues really early on and point at where the problem might be.”

What should you take from this?

If I leave you with anything after reading this, it’s to always treat analytics with a pinch of salt. Everything from user count to conversions can be impacted by so many outside changes, none of which you can control. Changes might even be completely unrelated to your site migration or analytics, since external changes in how browsers handle cookies can impact your data significantly. Check your data often, in small doses, and remember: no amount of testing will be as good as testing how it works in the real world.

Find as many data sources as possible, and use them all, but always bear it in mind that each one has its own unique set of limitations and potential flaws.

For me, DataStudio is an extremely useful resource, as it allows me to monitor half a dozen sources at once. Whatever software you use, I strongly recommend you ensure it has automation and intelligence, so that you can see as many key metrics as possible.

I’ll leave you with a list of my favourite data sources, to hopefully help your next migration go as smoothly as possible:

  • Sistrix
  • DataStudio
  • Google Analytics
  • SEMrush

Graham Grieve, from A1SEO.com says "Incorrect data attribution still poses a major risk to businesses globally and see's it time and time again with migrations".

Want to know more about how to get the most of your analytics? Drop an email to Gerry.White@riseatseven.com.