I’ve been in the B2B online marketing industry for over a decade. Over this time I’ve seen the evolution from pure SEO/PPC to incorporating social media and content marketing.

As the digital landscape changes, so too must our approach to marketing. In today’s world, consumers have more power than ever before. They’ve grown accustomed to brands constantly trying to engage with them. Sometimes this may come in the form of a flashy ad. Other times it could be content that helps solve a problem.

Brands must now consider the power of the average consumer as much as they do that of a small market segment. The key to creating effective marketing is by thinking of multiple hypotheses, testing them, and learning from the results.

Create Multiple Hypothesis Testing

Testing multiple hypotheses isn’t a new concept. In fact, it’s something that scientists have been doing for centuries. If you want to get the most out of your marketing efforts, you need to consider running multiple tests and learning from the results.

Think of all the marketing approaches that you’ve tried over the years. Maybe you’ve focused on attracting organic traffic from search engines or used social media to grow your audience. You’ve tried adwords, PPC, and even sponsored listings. Each of those approaches has given you great results in terms of growing your business, but they’ve also each had their limits.

What if there was another way to drive traffic to your website? What if there was another approach that could possibly give you the results that you’re looking for?

The problem is that we often get stuck in a pattern. We try the same thing over and over again, but something isn’t adding up. We’ve been using the wrong metrics to measure the effectiveness of our campaigns. It’s time to expand our thinking and try something new.

Use A/B Testing To Your Advantage

A/B testing is a form of testing multiple hypotheses. The idea is simple—split your audience in two and run two separate campaigns on the same website. While the approach may seem obvious, it’s an area where a lot of businesses struggle. Most marketers start with the absolute minimum configuration of A/B testing and then add more configurations as they learn more.

Every time you make a configuration change, you’ll learn something new about your site. You can also measure the impact that the various changes have on your bottom line. For example, you could compare the results of a campaign with no tags to a campaign that uses all white hat SEO techniques and no keywords.

Consider using a tool like Google Tag Manager. With Tag Manager, you can separate the creation of various campaigns from the testing. This will make it much easier to add configurations as you go along.

How To Create Multiple Hypothesis Testing In Online Marketing – The Biggest Mistake

One of the biggest mistakes that you can make as a business owner or marketer is thinking that you can create multiple hypothesis testing by simply adding more tools to your digital toolbox.

If you want to create multiple hypothesis testing, it’s best to start with a basic test and then add more configurations as you learn more.

Make sure that you don’t just add tools without thinking. Consider what you’re trying to achieve and then look for the right tool to help you achieve your goal.

Create Multiple Hypothesis Testing In Your Online Marketing

To create multiple hypothesis testing in your online marketing, you need to start with a single test and then add more configurations as you go along.

For example, let’s say that you’re running a Google ad campaign for your business. You’ve decided that you want to learn more about the impact of different keyword combinations on your campaign performance. You could run a single test with basic Google keywords and then run another test with longer, more specific keywords. Or, you could simply add a third test with a mix of the two.

The possibilities for learning from different combinations are endless. You might find that articles with a mix of long and short keywords perform the best or that articles focused on a particular city perform better than those that aren’t geographically tied.

As you add more configurations to your testing, you’ll start to notice patterns emerge. It might be that your articles with the longest keywords tend to perform the best or that a certain city’s articles tend to outperform those from other areas. Whatever the case may be, you’ll know what works and what doesn’t based on actual data rather than your assumptions or guesses. Your efforts will then be directed towards maximizing your results rather than wasting time with approaches that won’t work. This is how you create a successful campaign that delivers the results that you’re looking for.