This guest post is by Adam Connell of Bloggingwizard.com.
There’s a testing technique out there that’s not being used to its full potential—or even used at all by most website owners.
Today I want to show you how you can use it to create the ultimate high-converting opt-in form.
Many site owners avoid multivariate testing as it seems overly complex, and most of the services on the market that provide multivariate testing are paid services, which leaves bloggers unsure of the potential ROI.
In this post you will learn how you can use Google Analytics content experiments to conduct multivariate testing on your own opt-in forms in an easy and controlled way that will allow you to maximise your conversions.
Why multivariate testing?
In early 2012 Econsultancy.com and Redeye conducted a survey http://econsultancy.com/uk/reports/conversion-rate-optimization-report that yielded some interesting results.
Multivariate testing came out as the most valuable testing method for improving conversions, despite only 17% of companies stating that they used it.
According to the same report, taking the leap from A/B split testing to multivariate testing can help you improve conversions by an extra 15%.
This shows a huge opportunity for those site owners and businesses that come on board and start using this testing method.
So let’s see how it’s done.
Step 1. Break down your opt-in form
In order to conduct any worthwhile experiment you need a plan and identify all of the different variables; but in order to come up with a complete list of variables you need to break your opt-in form into its various elements.
Here is a combination of the typical elements you may find in an opt-in form:
- additional text
- name capture field
- email capture field
Step 2. Define your variables
Now that we have all of the elements of your opt-in form mapped out, we need to break each element down further and plan out how we might want to vary each one.
Please note, the list below is not exhaustive, nor do you have to vary all of these when you come to experiment. The point is to show you all of the possibilities.
You may think some of these are minor changes, and they are. But the impact of some of these changes can be enormous.
For example, some marketers have tested opt-ins with name capture and email fields against forms with just an email capture field, and have managed to increase conversions by 20%. So it all makes a difference!
- Headline: font, text size, text colour, capitalisation, alignment
- Sub-headline: font, text size, text colour, capitalisation, alignment
- Additional text: yes/no, font, text size, text colour, capitalisation, alignment, bullet points
- Image/video: yes/no, image size, image content, video size, video content, video audio, video type
- Name capture: yes/no, text in field, icon to the left
- Email capture: icon to the left, text in field
- Button: size, shape, text colour, text font, text size, background colour, rounded edges
- Background: border, image, drop shadow, border.
Step 3. Plan the test
This is where it starts to get a little bit more complex: you need to come up with the original control version of the form for your test, and as large a number of variations as possible.
The downside to Google Analytics content experiments is that you’re limited to nine variations plus the original (or control) version.
You also need to be able to keep track of the variations and changes that you’re making; you can’t just throw something in and hope for the best.
To make this easy for you, we’ve put together a Google docs spreadsheet that will allow you to keep track of all your elements and variations.
Please note: you must make a copy of this spreadsheet before altering it, otherwise everyone who visits will be able to see your testing plan!
Due to the number of variations that may be needed in the future we’ve broken the document down into controlled groups.
Now just add the variations, which may look something like this:
At this stage it’s important that you only fill in the variations for group A as you need to use the results of each group’s test to inform the variations you select for the next group.
Step 4. Gear up to test group A
Now that you have planned out your variations for group A, you’re ready to get the test underway.
The setup process here is fairly straightforward:
- Set up a new page for each variation.
- Add the pages to Google analytics content experiments. Log in to your account, then navigate to standard reporting > content > experiments.
- Set your goals. Note: the easiest way to do this is to ensure your opt-in form directs users to a thank you page, then find the URL and add this as the goal URL.
- Add the content experiments code to your pages.
- Let the experiment run.
It’s important to let your experiments run for as long as possible, so you can get data from the largest possible amount of traffic.
The more traffic you run this experiment on, the better, but if your blog doesn’t have as much traffic, then you will need to run it for even longer.
You are just looking for conversion rate here so, strictly speaking, you can run each test on different numbers of traffic. You need a statistically significant result for each test; you don’t need every test to involve the same amount of traffic.
Step 5. Review results and prepare to test group B
By now you will have had the results from group A, which means you can start thinking about the group B tests.
The first thing to do is to take the best performing variation from group A and add it as the original for group B (don’t forget to update your main page on your website at this point).
Now it’s just a case of rinsing and repeating the process above, tweaking and coming up with new variations to test each time.
A potential 15% conversion boost
Using this guide you will be able to create additional experiments for other parts of your sites, not just opt-in forms. You can easily tweak this method to use on sales pages, product reviews, squeeze pages, ad layouts or anything else you can think of.
The important thing is laying out your variations and keeping track of them. Then, just rinse and repeat.
Are you using any form of testing at the moment? We would love to hear about which methods you’re using and how much you’ve managed to increase your conversions in the comments.