A shift is about to happen in the marketing industry; a disruption in how companies measure and attain marketing success. Artificial intelligence is emerging as a tool to help marketers boost website conversion rates incredibly quickly.
Let’s clarify one thing; conversion intelligence won’t replace human marketing instincts. It will augment human marketing expertise with data insights and machine learning.
Compared to human analysts, machine learning algorithms analyze more data more quickly to gain more insights. No matter how good you are at your job, AI will help you learn more about which versions of your web page deliver the most leads.
AI cannot replace human creativity and experience, but it can reveal which landing page and web page variations work. It can do this almost instantly, without forcing you to wait for AB testing tools.
This wave of AI is about more than data analysis; machine learning algorithms can now perform real-time adjustments to send individual customers to the web pages they’re more likely to take conversion actions on.
Let’s look at a real-world example. The landing page builder Unbounce has a new feature called Smart Traffic. This is a machine learning tool that moves customers to different variations of test landing pages. Smart Traffic finds the best landing page for each individual visitor based on that visitor's attributes.
These attributes include things like location, device type, OS, browser, etc. Once the AI understands which kind of customers perform conversion actions on each Unbounce page variation, it can send similar customers to the same variation of the page.
After analyzing the attributes of each user, Smart Traffic sends them to the landing page that has already worked on other users with similar attributes. If you’re running two or three variants of a landing page, Smart Traffic will send new leads to the variant that is likely to convince them to convert.
In general, the biggest benefit of AI is that it speeds up the A/B testing process by sending customers to the right page instead of comparing results afterwards. The clothing company Cosabella proved this. They used two different AI tools to improve conversion rates; Albert and Sentient Ascend.
In an effort to improve conversion rates, Cosabella wanted to test 15 different variables of headlines, buttons size, colors, CTAs and background images on their product pages. That’s 160 options, which is a whole lot more than the two options that can be tested with standard AB testing tools.
While an A/B test would only be able to test two variations at a time, the machine learning algorithm can send different users to 160 different versions, comparing conversion rates to identify the most effective versions of your website.
For websites, A/B testing is generally used to you out which version of a page converts more people. The problem is that you don’t can’t determine a winner and maximize conversions until after the A/B test is complete. Then you can switch to using the more successful landing page full-time. Machine learning algorithms can send customers to the most effective page in real-time.
This next point is key:
AI solves a problem you may not recognize. Most people who use A/B testing are hoping one version of their website variation clearly wins.
However, there isn’t always a clear-cut winner. It’s rare that one version of a page is always more effective at converting customers than another; in many cases, different variations are effective for different customer demographics; you have to show the right variation to the right customer.
The other issue is speed. When you run an A/B test, you have to wait for the test to gather enough results to determine a winner. Machine learning speeds things up. You don’t have to wait until the test is over to identify which marketing material converts best.
By analyzing the attributes of each website visitor and then showing them the best marketing materials for their demographics, machine learning algorithms can immediately start seeing more call, form and chat conversions.
Your business has many different types of customers, and they all convert for different reasons. However, it's not feasible to run A/B tests with hundreds of variables to account for every variable that might convince a customer to convert.
It’s helpful to think of conversion algorithms as “smart routing tools.” If you’re testing landing page layouts, the algorithm “routes” a new visitor to the landing page that has already successfully converted users with similar attributes. These users are measured by attributes like OS, Device Type, Marketing Source, Location, etc.
The more you send the right customers to the right landing pages, the faster you’ll improve conversion rates. That’s the essence of machine learning's impact in this space.
Every time a visitor comes to your website, they either take a conversion action or they don’t.
Machine learning algorithms can analyze the user’s background data, determine whether they’ve taken the desired conversion action or not, and learn which types of users take action on which types of landing pages. Of course, you have to have the ability to track every type of conversion action including phone calls, form-fills, web chats and eCommerce transactions.
Every visitor has data attached to them. The algorithm can learn which pages work for visitors with certain attributes, then show those pages with similar customers.
The algorithm updates with every visitor, meaning you can improve conversion rates more quickly than you would with AB testing tools that take weeks to complete.
A/B testing isn’t obsolete, but it does lack the speed and accuracy of machine learning algorithms that can use conversion intelligence to rapidly improve conversion rates. Keep an eye out for machine learning algorithms in the marketing software you use, and look for more information on conversion intelligence to improve your conversion rates in 2021.
Mac Mischke is a Writer and Content Marketer at WhatConverts. Connect with him via email at firstname.lastname@example.org.
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