A/B testing has always been a helpful tool for marketers, particularly those who want to prove their results. Instead of just sticking to the same campaigns, they can try different ideas and then show with numbers which one works best.
It’s a great way to understand what customers are really looking for, even if they can’t quite define it themselves.
However, there are downsides to A/B testing, particularly if you’re seeing campaigns where neither strategy produces convincing results. If you’re looking for a way to cut back on the inefficiencies of A/B testing, we’ll look at how the AI revolution is changing the process.
AI Testing
AI’s role is to both enhance and optimize A/B testing, which can help weed out poor ideas before investing too much time and energy in them. When you integrate AI, it’s no longer about gathering data from different sources and comparing like for like. This is a much deeper analysis that will give you insights into why customers are responding to certain stimuli but not others.
AI tools, such as VWO Testing & GPT-3.5 Turbo, ABTesting.ai, and Evolv AI, can deliver a vast trove of information when you need it most. These programs can pick up on the trends that marketers might miss and make stronger predictions based on the facts.
When you have that kind of information at your fingertips, you can start seeing how to refine your ideas.
For instance, let’s say that one landing page (A) focuses solely on your affordable pricing, whereas the second landing page (B) focuses on your reliable services or products. With AI tools, you can test across multiple variables, including time of day, location, and user behavior. This can be exceptionally important if you’re running a more nuanced test. Maybe you don’t need your second landing page to have as many conversions if you’re going after a high-end clientele. So, even if you have more conversions from A, you might choose to stick with B because you’ll have better long-term results with this strategy.
Stronger Data Analysis
It may take a little time to see dud ideas go by the wayside with AI, but the intense data analysis should make a difference if you stick with it. These analyses are done by algorithms, and you might be surprised at just how accurate they can be at understanding a person’s decision-making on the other side.
Ultimately, you're looking for underlying causes between what the customer sees and what they do as a result.
Whether that’s clicking off the offer or moving on to the next step, these programs can track their movements and offer real explanations as to what’s happening behind numbers. From there, it can forecast trends about what you should do next. In some cases, it’s as simple as timing. Maybe you simply need to run the campaign a month earlier in the year for better results. In other cases, it may mean a total overhaul of your current approach.
While it may be an investment to find, purchase, and implement the right AI tool, you'll save time and money in the long run. Just remember that different programs will work differently, so you'll need to some research before you choose one tool over the other.
Tips for AI in A/B Testing
There are plenty of companies using AI to improve their A/B testing, even though the most successful examples are companies with enough resources to invest in the best technology. The good news is that you don’t need to have unlimited funds to throw at the problem. You can still derive plenty of value from AI tools as long as you know where to start.
- Set priorities: Most marketers are going to want the same general things from their A/B test (e.g., conversions, retention, etc.), but it can pay to specify what you’re looking for. For instance, short-term boosts in sales, thanks to a promotion or discount, don’t always result in long-term customer engagement. Once you have the parameters for your test, AI can help you determine whether it was really a success.
- Research the tools: There are numerous solutions available today, and with AI being so hot right now, there are likely to be dozens more available tomorrow. Make sure you’re looking at how different AI tools work and whether they fit the objectives of your company before making the investment (even if that investment is just your time).
- Consider your tests: As a good rule of thumb, you should only have one or two variants of an A/B test if it’s relatively simple and no more than 10 for even the most complex of tests. Whether you change the CTA or the headline, these variants can deliver powerful insight so you can adapt your marketing strategy as needed.
- Analyze: This critical step is ultimately what will help you decide which ideas are really driving the business. No matter how you're appealing to customers, you can see whether your efforts are getting through or falling flat.
- Keep going: Because customer interest can change on a dime, so too should A/B testing. Once you've applied what you learned from A/B testing, be prepared to stay on your toes.
There's a lot to be said for using the latest technology to keep up with your marketing efforts. When you're in doubt, the right AI programs can prove to be a remarkable tool that you can use to feel more confident for every marketing dollar spent. This isn't about replacing human instinct with a machine, but about giving you enough context to make smarter decisions.
Just getting into AI and need some help? Laveh is your one-stop shop for all things digital marketing, and we can help you leverage AI for a better return on investment. Contact us today to find out how.
