Data Driven Strategy Via Ab Testing MRR Ebook

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Search Engine Optimization is a skill that is constantly changing and evolving. If you work in this profession, then resting on your laurels and sticking with what you know simply isn’t an option any more.

It was only a few years ago that we believed the best way to succeed at SEO was to stuff a page full of keywords and to pay for links from as many sites as possible. Of course, we know that this will get a site penalized and even de-indexed pretty quickly these days!

Today, Google is an AI-driven company. Google wants to combine its search engine with its smart assistant, so that you can simply ask Google who was in X film, or how to cook X meal, and it will be able to answer in natural language by pulling from the web.

Future implications of this aside, what it means for webmasters right now, is that they need to start being smarter about their use of keywords and the type of content they produce. They need to think about using markup language, employing latent semantic indexing, and getting links from sites that Google trusts, with plenty of authority. They need to do all this while STILL producing content that is engaging and entertaining for real, human readers.

This is such a nuanced and complex topic, that you’ll find you can no longer just ‘guess’ what will work. And you can no longer make assumptions.

The ONLY way to succeed online, is to take a data-driven approach. That means watching your stats and metrics extremely closely, but it also means running split tests, which can help you to identify the precise techniques and strategies that are guaranteed to bring your website success.

In this report, you’ll learn why this is no longer optional for SEOs, and why it’s crucial for the entire industry that more agencies start using this topic. You’ll also see precisely what an AB test is, and how you can employ it to amazing effect.

So, just what is an AB Test?

AB Tests, also known as split tests, are tests used in marketing and business in order to ensure that a strategy works before going ‘all in’. They do this by testing that strategy in a real-world scenario, using controlled conditions.

Essentially, this works just like experimental design in research. That is to say, that you will split your test subjects into two groups: an experimental group and a control group. You’ll then attempt to keep as many variables (factors) the same as possible in the two groups, change just one thing, and then compare the outcome to see which worked better.

So, an example of how this might work in business, would be to think about a fast food chain that currently uses a bold, sans-serif font for its name on the front of the buildings. The owner of the business conducts some market research however, and learns that customers are not too keen on that logo, and would rather a more ornate font to help welcome them into the building.

What does the owner do? One option would be to change the text across all stores and to hope that the market research proves to be accurate.

The business owner did something right here, in that they at least conducted market research first, which helped to motivate a smart change. The worst case scenario is that the business owner would simply decide that they like a more ornate font and change it across all their stores without thinking about the potential implications. They could end up losing a lot of money and never knowing where the ‘leak’ was.

But the problem is that even with market research, you still can’t be certain that you’ve made the right decision. Market research can be wrong, and it can miss other factors (the visitors may prefer the more ornate font, but they might not see it as easily as the clear, bold font!).

A split test then would involve changing the font on half the buildings. It would then compare the profits of those two groups, in order to see which one performed better and whether or not the change should be employed across the entire chain. If the stores with the new font earned more money, then the same technique could be used globally. If not, it could simply be forgotten. And another new change could be tested.

This way, split testing allows you to be certain that something is the right move before you do it. And the same thing works just like that in SEO. Here, you might test changing keyword densities, or you might test using more headers. Maybe you test using more images, or perhaps you try using an image at the top of the page.

All these things might end up impacting on the performance of your pages in the Search Engine Results Pages (SERPs), and thus help inform your practices in future. You might also go back through all older pages on the website and make the changes across the board.

How do you run a split test for SEO? One option is to take lots of similar web pages that are all performing equally well, and then to make changes to half of them. Head into your Google Analytics account and make a projection for how would normally expect them to perform, and then compare that projection to how the pages actually perform.
If all the pages with the changes start performing better than projected while the other pages remain the same, then you can take the changes and adopt them permanently on all versions of your site. If they start to fall in the rankings, then you can drop the change and move onto your next strategy.

Another option is to use a redirect – creating two versions of the same web page and sending half of your visitors to each. This will allow you to conduct a more scientific study, but it will also mean that you can’t measure your position in the SERPs (seeing as it’s just one page and Google will only rank it once). This can nevertheless be used to see how changes affect things like bounce rates, CTR, conversions etc., which all are likely to have a knock-on effect on SEO AND on your profits.

Not sure how to do this? Then you should check out the eBook: Split Testing in SEO for Data Driven Success, which will explain everything in more detail. This will also show you how to avoid letting split testing hurt your ranking, and how to be as scientific as possible about your results.

I know what you might be thinking at this point: do you really need to go to all the trouble of creating two different versions of the same pages? Or split your pages into groups that way?

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