A/B Testing explained and how you can use it
Imagine you’re preparing the launch of a new product. It’s well designed, you see your audience loving it, and you get positive reactions from peers. You believe it could be the next big product for your fledgling company.
But while you know who your target audience is, you lack the data to define what makes them tick, and what makes them see you and acknowledge your content. So come launch day, you’re pushing against the wind, and as a result, it underperforms despite your product’s undoubted quality.
The type of data that makes your product shine on the market, the data that demonstrates the behaviour of your core target for any channel of content, is actually very easy to obtain. It’s simply time and effort that result in detailed analysis of how your target audience acts to language, structure, imagery and anything that can be consumed.
This result comes from A/B tests, and if you’re not already conducting them in your company marketing, this post details why today is the day to start A/B Testing.
What is A/B Testing?
A/B testing is taking two or more items that are similar or relate to the same subject, but are presented differently. These are then shown to an audience with a similar characteristic or demographic, such as an age group or shared interest, with a split percentage to show how many were shown each item (such as 50% shown one, and 50% the other).
Then the results of the test show how the audience responded to each item, comparing the reaction and using the information gained to inform how best to proceed with the subject.
In marketing terms, this equates to showing multiple versions of content about the same product, service or topic to an audience segment and measuring the behaviour.
For example, if you’re a make-up artist sending email tips and tutorials to subscribers, an A/B test for a new tutorial would include one comprising exclusively of written copy, another with copy and images for guidance, and finally a version that embeds a video tutorial. Each one comes with two calls-to-action at the end for an exclusive discount on make-up sessions, and affiliate links to purchase the make-up products used in the tutorial that act as conversions.
With these sent to subscribers split equally, the data gathered highlights the open rate of each version, engagement levels including how long they were reading, unsubscribe clicks, and conversion rate for both the discount and the affiliate links.
Typically, this is achieved in your marketing suite. Platforms such as Mautic and MailChimp will present an option to take multiple emails and A/B test them in a campaign. At the campaign’s conclusion, the built-in analytics provides all of the information to you in clear reports.
That said, you can A/B test almost anything in marketing, from paid advertising and emails, to landing pages and video titles and thumbnails.
Why A/B testing is important
The example that I opened this article with highlights the consequences of failing to prepare your sales and marketing campaigns with evidence to back your decision-making.
While you may know who your target audience is, it’s not the same as actually knowing them. As the person driving a project, you need personas of who it is that will buy your product, but the only way to get an accurate profile is with data research obtained through extensive A/B tests.
If you’re looking to launch a new can of iced coffee designed for young coffee drinkers on the go, market research will suggest what coffee type is the most popular choice to produce. But due to the catalogue of variables at play with any new launch, it’s only through A/B testing that you can learn how to market your coffee to your specific target audience to turn your marketing into sales.
Data from your A/B tests drives the look, tone, language, imagery, colours, price and more of your product to give you the best chance of sales success to your target personas.
A/B testing is important because it provides information on your audience that can only be found through this type of testing. It takes away guesswork on your target audience’s behavior so you can rely on accurate, clear data.
So to lead the way for a data-driven, more informed future in your marketing, A/B test everything you can. It won’t take long for your efforts to bear fruit.
What A/B testing can’t help with
We’ve talked about why A/B testing is effective and how it provides insights on customer behaviour based on the communications and content you share with your audience. It’s fantastic at what it does, but it’s only part of the marketing toolbox you should be utilising.
The type of data gathering you can do with A/B testing works best when you have established what the product is and have a basic understanding of who you’re marketing to. More traditional forms of market research, such as test groups and surveys, provide insights that drive overall strategy rather than specific products and markets.
For example, an A/B test will establish how recipients react to marketing for your product and provide opportunities to optimise. What it can’t help with is identifying an arching trend if your audience’s wants and needs pivot.
So if your consumers start transitioning to preferring a competitor brand or a new product, those surveys and focus groups, as well as marketing and competitor research, provide that data more efficiently.
As such, a research and marketing project requires a variety of marketing strategies and tools to get the most effective results for a product launch from start to end.
But if you’re still unsure about where to start with A/B testing, enable have helped businesses across the UK with their marketing efforts through Mautic. Get in touch now to begin your new informed future.
