The Effectiveness of A/B Testing as a Marketing Tool for Small Businesses

It is comparatively easier to make a decision when the choices are limited. You can compare the options, evaluate the pros and cons, and finally choose the option that serves your needs better. A/B testing has allowed marketers to do that over the past few decades. Whenever they have encountered untapped opportunities, A/B testing has made a difference in their decision making process, often drawing the line between success and failure.

There’s no denying that A/B testing has served digital marketers rather proficiently. However, it no longer remains the only viable option for marketers, especially after the introduction of some proficient marketing tools in recent times.

Just think for a moment – would it be convenient for you to gather the statistics of a large scale sample and compare the efficacy of only two strategies when the competitors are using multichannel approaches to storytelling? The answer is a big no. But, does it mean the A/B testing is no longer applicable for small businesses?

The problem with A/B testing in today’s marketing scene

Well, the relevance of A/B testing cannot be sufficed with a simple “Yes” or “No”. It’s more complicated than you think. Yes, the A/B testing does come with a few issues, like –

1. The testing is done on your own assumptions, which means there is going to be a bias in results which is likely to distort the test more often than not.
2. The tests usually require a large scale sample. So, gathering the accurate statistics from the large sample size becomes a strenuous process.
3. Also, it takes a decent amount of time to get the results. You can use that time and energy and invest it somewhere else.

Most professionals report that 8 out of 10 A/B tests do not offer significant results, as highlighted by a survey from eMarketer. Since the A/B testing is a process of trial and error, the results (predictions) were likely to be inaccurate from the beginning. So, why did the yesteryear marketers use this technique on their job?

For a significant period, A/B testing was considered a quintessential practice in the marketing landscape. Proper use of A/B testing could help marketers –

1. Reduce bounce rates
2. Boost the conversion rates
3. Improve the sales, and
4. Increase the conversion value

Even though it offered a number of benefits, A/B testing was still a slow process. In fact, marketers could only test one variable at a time while tracking the results. The results, however, were quite straightforward when it was about testing the social media elements. The problem surfaced when marketers tried to test a number of different variables at the same time.

It is wrong to say that A/B testing has stopped delivering those benefits lately or there was no other alternative available to marketers in the past. It is just that the marketing approach has evolved rapidly in these past few years, and A/B testing not only seems outdated but is also inconvenient to the marketing practitioners.

In today’s dynamic environment, where every brand is trying its best to improve the conversion, A/B testing often falls short in delivering timely support. As a marketer, you may realize that you need to optimize, improve and fine-tune your marketing strategy quite frequently to keep up with the changing requirements of the digital platforms.

Should you give up on A/B testing?

A lot of people may suggest you give up on A/B testing today, and for the most part, they are actually right. There are a lot of other areas to focus on than A/B testing, which does not guarantee significant results. However, you may still need this yesteryear technique to refine your campaign strategy over time.

Whether you realize or not, there is actually a lot of room for improvement in the technique of A/B testing. And now that there are enough opportunities to make technological enhancements (automation and artificial intelligence) on the technique, it will further help the practitioners to make better content marketing decisions.

For years, marketers have relied on the A/B testing marketing campaigns for positive results. And in a significant number of cases, they have received what they desired. But now you cannot just test one variable and trust the results to be accurate. The content marketers of today are more inclined towards adopting multi-layered approaches to brand storytelling, where a number of factors come into play, contributing to the success of the content marketing efforts.

The marketing technology developers have started to understand the significance of A/B testing in today’s market. And they have begun to work on the tools that can eliminate the limitations that manual A/B testing had. Basically, they are working towards an automated solution. In fact, they have made some progress in that context.

Google responsive search ads are a new ad product which uses contextual information to automatically choose the best headline and description for a given situation. Of course, it requires you to upload a bunch of different headlines (up to 15) and ad body text descriptions (preferably four) beforehand.

Do you realize what marketers can do with such a tool? Well, for starters, they can schedule social media posts and emails to be sent automatically at an optimal time, and optimize case-specific headlines and preview texts without any additional effort. The applications of such automation are nearly limitless.

What does the future hold for the testing practice?

One of the major challenges that marketers had with A/B testing was that it could not evaluate multiple variables at the same time. With the advancement in technology and AI-powered solutions, marketers may be able to test a number of different variables during a single A/B test. The ability to test multiple variables at once may enable marketers to get faster results as well as accuracy with improved data support.

The data derived from the AI-powered A/B testing can also help marketers to identify the effectiveness of a certain marketing effort and decide whether it needs any further modification. Even though the initial efforts may revolve around the use of search ad campaigns, it won’t remain the primary application of the AI-powered A/B testing.

It is believed that the creators may be able to use AI to brainstorm storytelling ideas and other significant strategies to develop engaging stories that resonate with the audience. This may lead to complete automation in the creative segment of the brand storytelling part, but it will also allow marketers to explore other angles to present a branded story.

Now, it may seem like the A/B testing is a waste of time and money. However, in the near future, when the automation and AI will be integrated with the process, A/B testing will allow marketers to receive smarter, better and faster insights while reducing the workload.

So yes, A/B testing will still be an effective tool for marketers in 2018 and beyond. However, a significant advancement needs to be made in the process to revive its efficacy.