Why is A/B testing hard?
For A/B testing to be done correctly, it requires the decision to run an experiment for a period of time.
A/B testing can help you improve your SaaS landing page performance.
Through an experiment, you can see what works for your landing page and what doesn’t.
In this guide, I’ll show you two ways you can perform A/B testing by using Google Analytics and Google Looker Studio.
What is A/B Testing?
Imagine having two pages being identical, the only difference being on one of them using a Calendly form and on the other one, you use a normal form.
Now, you want to see which one converts better.
The other component that you need is the test needs to be run at the same time.
You don’t want to run one test in January during the low season and run the other in September during the high season.
You want to be running these both in the same month or as close to the same time as possible to ensure that the numbers aren’t affected by other factors.
When you look at the results, there needs to be a significant difference in performance.
If you don’t have enough data for the test to be statistically significant, then any conclusion that you draw isn’t based on a strong foundation.
All of this requires a dedicated A/B testing tool that allows you to swap your test A and test B very quickly.
There are tools like Google Optimize and there are even tools that have this built-in natively like ThriveCart or Landingi.
However, what do you do if you’re not working for a large client or your client doesn’t have an A/B testing culture or workflow set up?
Well, you can monitor performance in Google Analytics or by using this quick and dirty method, using GA data, and putting that data into Looker Studio to observe.
How to Compare Landing Pages Performance in Google Analytics
If you have Google Analytics set up, we’ll go over the way to look into the numbers and see what pages are working well for you in Google Ads.
There are pros and cons to this approach.
It’s easy, you can quickly log in and see the table of reports and see the numbers.
The disadvantage is that you can’t customize it.
Let’s log into Google Analytics, go to Behavior → Site Content → Landing Pages
Here you can see a report of all your landing pages and metrics for each page.
Quite an interesting report if you’re doing blog content, for example, to see which blog led to conversions, but also really important information when you’re testing out different destination URLs in PPC or Google Ads.
There’s a lot of information here, but this report gets really valuable when you start segmenting and looking into the numbers.
The report that we showed is segmented for all site visitors.
But what we want to do is limit our segment and just focus on people who came from paid advertising or Google Ads.
So, we’ll switch our segment from All Users to Google Ads.
You can see both the absolute amounts and the percentage of the total.
In our case, we have around 50% of traffic going to our first page.
Let’s see the data for the goal sign-ups and also we’ll increase the date range to a few months.
We’re getting a lot of sign-ups from this signup page, but we have only around 2% of total users going to this page.
We have site links going to pages number 1 and 3. In this case, we might want to look to optimize the text with the ad copy on those pages.
The problem with Google Analytics is that you can only look at one goal at a time.
It’s very inflexible because you can’t add more metrics.
When you want to do a deeper analysis, you can use GA or Google Ads data and import it into a reporting tool.
That’s where Looker Studio comes into play.
How to Compare Landing Page Performance in Looker Studio
Looker Studio lets you pipe in data from GA, Google Ads, or some other source (Facebook ads, TikTok ads, etc.).
✏️Learn how to have full control over where you spend your PPC budget in your ad account by using our PPC budget allocation tracker template.
You can make the same chart with the landing pages on the left here and add all key metrics here.
This becomes valuable when you’re testing out pages against each other.
Let’s take a look at this page.
This page got five trial signups and its cost per trial is around $270.
When compared to the rest of the pages we start to see that this page isn’t ideal for this client.
You need to take into account which campaigns are we using this landing page in.
There are a lot of factors to consider and it’s not just cost per trial.
You want to look at the cost per purchase, volume of purchases as well, and how many users actually activated.
Let’s now take a closer look at the features page.
So you can see that this page was capturing a lot of trials, but for some reason, none of those trials actually converted into purchases.
Which is worth digging into and seeing why that was.
Could it be that our features page is unclear about what we’re promising inside our software or that we promising too much?
All of these things are worth taking into account before making your final decision on your analysis.
All of this data is imported from Google Ads.
We use Final URLs for our dimension.
Then on the metric front, we have cost, impressions, clicks, click-through rate, trials, cost per trial, purchases, and cost per purchase.
You can add anything else that you want.
Let’s add the trial activation rate metric to our table.
Click on Add metric, give it a name, then divide the SUM of Purchase with the SUM of Free trials, use Percent for the type, and select Apply.
✏️ The reason that we use SUM is that you’re not doing each purchase divided by each trial.
Now that we’ve added our new metric, let’s check out our table.
So 5% of people who landed on the top page activated after they started the trial, while on the second page, 10% activated.
Even though we’re getting fewer trial signups from the second page, for some reason the trial activation is higher.
Now let’s create a trial conversion rate metric that will measure the performance of the page.
For this one, we’ll use SUM of trials divided by SUM of clicks.
We want to put our landing page conversion rate after the metrics that we’re looking at.
Now you can see the performance of the actual page and the landing page conversion rate.
It differs a lot depending on the traffic, the page, etc.
It’s always worth bearing in mind that these landing pages are often used for specific reasons.
Some of them are competitor landing pages, so there’s different intent there.
The landing page’s high conversion rate may not be a hundred percent due to the page being better because it’s not an apples-for-apples comparison.
However, it gives you an interesting insight into the conversion rate of each page, how the campaigns are doing, and how the pages are doing.
You can actually very easily A/B test different pages to each other.
It’s not ideal, but in cases that you want to change the offer on a page or the pricing, and you want to send traffic to that other page, you can look at the landing page conversion rate and find out which page is actually converting better.
The trial activation rate is nice to have, but it depends on the SaaS or the software that you have on whether you want to track this.
We can see that the second page is leading to paid customers way more than the fourth page, which is also a competitor landing page.
Both of these pages are converting trials at the same rate, the cost per trial for the second is a bit higher, but overall we’re getting more users from it.
You can see how we need a full picture of all the landing page performance metrics together to be able to see how they’re doing.
From this data, I can see that page two is our winner, whatever we’re doing on that page in terms of layout, copy, or sending traffic it’s working.
I can use a lot of that information, to build out new pages.
It doesn’t end here, you can do all kinds of cool stuff.
You can literally in Looker Studio make any metric that you want.
You can also filter this data for anything that you want.
Let’s say you want to exclude brand traffic or remarketing traffic, it can be done.
The way that you do that is on the table level.
You would select Add a Filter, then Create a Filter.
I usually use this naming convention Excl. brand, then select Exclude → Campaign → Contains, put your brand name and Save.
It’s really flexible compared to Google Analytics.
It’s not as good as an A/B testing tool, but because all data is there by default, you don’t need to actually set up A/B tests.
I prefer it over an A/B testing tool because with A/B testing tools you need to set up an experiment with a hypothesis with one test variable that you will change on one version of the page and you need to run it for a set period of time.
And for SaaS and software, it takes time to collect enough data to actually make a significant decision (which can be two or three months).
This is exactly why it can be a bit difficult to create a culture of A/B testing.
Someone needs to remember to check back in on the test, stop the test after that set period of time, analyze the data, and then make a decision based on it and collect the learnings in a document.
However, with Looker Studio, you’re collecting data all the time and you can run new tests and the tests are automatically collecting data.
All you just need to do is just check back in here.
If I activated a new landing page and I put it in the ads, it would appear here automatically, because it’s a dynamic report.
I wouldn’t have to manually set up a test.
It would automatically start testing in the background.
That’s why I really like this approach.
So I would definitely recommend every SaaS to have a table like this with all their landing page data for Google Ads, paid acquisition, and even SEO as well.
Summary
We’ve covered how the reports in Google Analytics and Looker Studio work and how you can compare your pages within these tools.
By using our table in Looker Studio, not only will you have a way of comparing pages, but also a nice table that you can show to your clients. 😀
Once you start monitoring the performance of your landing pages, it’s time to check out the performance of your SaaS marketing funnels.
