Michael Epps Utley 
Is your A/B testing program all that it can be?
It might not be if you aren’t leveraging artificial intelligence (AI) to power it.
This article explains how AI can improve your A/B testing and overall marketing program.
What Is A/B Testing?
A/B testing is a research method for evaluating and improving landing pages, user interfaces, social media campaigns, and other types of marketing.
With A/B testing, you divide your audience into two (or more) groups. One experiences the control marketing effort (referred to as A, the original version) while the others interact with a variant or variants (B, and possibly more letters, the modified versions). Small business owners and marketers can then monitor interactions, analyze results, and then use this information to refine their marketing.
AI in A/B Testing: The Basics
A/B testing requires careful planning before implementation. Fortunately, AI tools are now able to do much of the initial legwork. When you use artificial intelligence in A/B testing, you automate the most tedious parts of it. You come away with clear, actionable insights because AI simplifies and improves the following components:
Coming up with testing ideas. AI systems, especially ones using machine learning (ChatGPT is an example), can quickly sort through massive amounts of data. They leverage insights from the data to generate novel A/B testing concepts and refine them based on new insights.
Modeling and analyzing data. Quality data is the bedrock of sound A/B testing. AI improves data by eliminating errors, duplicates, and inconsistencies that could negatively impact test results.
Customizing A/B testing. Artificial intelligence's sophistication allows you to bring high complexity to testing. For instance, it can more finely define the audiences participating in it and personalize their testing experiences.
Automating the testing process. AI systems can automatically set up experiments, track user interactions in real time, analyze metrics, and provide improvement recommendations. Automation reduces tedious manual activities and speeds up testing.
Generating testing variants. Instead of manually setting up each test version, artificial intelligence can create new variants based on your inputs.
Speeding data processing and analysis. Humans can take days or weeks to gather and analyze A/B testing data. AI can do it in seconds or minutes.
Creating content. AI can help you quickly and easily develop content variations for testing.
Mitigating cognitive bias. Humans are just that — human. And people come with biases, recognized or not. Leveraging artificial intelligence in testing can help reduce biases that could skew results. Note, however, that AI tools may also carry their own biases based on their methods for gathering and processing information.
Optimizing campaigns. AI can optimize marketing campaigns based on real-time A/B testing results, helping improve campaigns faster.
Adding predictive capabilities. AI doesn’t merely analyze past data; it also predicts future trends, allowing you to make proactive — not just reactive — campaign adjustments.
Simply put, artificial intelligence helps avoid the common mistakes that occur with human-handled A/B testing and delivers better results faster.
Limitations of AI in A/B Testing
Of course, nothing is perfect, especially when it comes to artificial intelligence. Here are some of the limits of AI when used in A/B testing.
It’s Complex
AI A/B testing sometimes requires advanced algorithms, specialized software, and skilled technicians. The complexity makes using it difficult for smaller organizations or people with limited technical experience. Still, tools like Userpilot and Hubspot make AI-fueled variant testing easy for everyone.
Privacy and Safety
Many business owners and marketers are concerned about privacy and data safety issues related to artificial intelligence. Attacks on AI-backed systems are possible, resulting in significant harm. Hackers could manipulate test results to damage your marketing strategies or, worse, steal personal and business information.
If you’re concerned about introducing AI into your A/B testing, carefully research the solutions you are considering to ensure they take security seriously.
Misinformation and Ethical Issues
Unlike humans, artificial intelligence lacks empathy and intuitive understanding. It can reveal what is happening but typically cannot explain why. It also doesn’t have a moral core, so automated actions based strictly on data could possibly cause harm.
What’s critical is to use AI responsibly. Leverage it to process data more quickly and efficiently, automate tedious and repetitive tasks, and generate initial content drafts. As a good rule of thumb, use AI for the doing aspects of your work but not the thinking or acting parts of it.
How to Use AI in A/B Testing
Here are proven ways to use artificial intelligence in your A/B testing effectively.
Real-time data processing to influence decision-making. AI can process a vast amount of data quickly. It identifies trends, patterns, and other information, providing the insights required to make sound marketing choices.
Leverage predictive analytics to increase accuracy. AI-based predictions help prevent you from coming up with incorrect hypotheses and testing ineffective or meaningless variants. Predictive analytics can identify bad data and other testing issues before they become big problems.
Develop personalized testing to create unique customer experiences. AI makes it easy to segment your consumers based on behavior, demographics, and preferences. You can use AI-backed testing to ensure the optimal buyer experience for each segment.
Simplify and expand multi-variant testing to improve marketing performance. Artificial intelligence can easily scale A/B testing from A and B to a full A-to-Z spectrum of options, speeding the path to achieving optimal marketing performance.
Detect anomalies to improve data integrity. AI tools can monitor test data 24/7 and flag anything that seems wrong. They can also help you figure out what’s causing these issues.
AI in A/B Testing: The Bottom Line
Like it or not, AI is now part of all aspects of marketing, and it should be part of your A/B testing efforts. It can superpower them and make testing more accurate and effective. Get started today with the ideas in this guide.
