As you scale your experimentation program, segmenting users and drawing insights from data will take more time and resources.
For many CX programs that start with simple A/B tests, the ability to efficiently process data is the bottleneck that prevents them from moving on to complex tests and personalized experiences.
AI can make scaling your experimentation program more efficient, which is why many A/B testing solutions now have AI systems. For example, Kameleoon users can use the Kameleoon Conversion Score to target website visitors based on their interests and probability of converting.
In the future, will analyzing user data with AI algorithms become a CRO best practice? Will it make user experience personalization possible for more organizations?
Here’s what marketing and CRO experts say.
1 You will process large quantities of data
AI can process enormous quantities of data, freeing up time for CROs to focus on other tasks.
Peep Laja, CEO of Wynter, agrees.
“Before using AI in optimization, one needs to understand what AI is really good at: crunching through a lot of data fast”.
Gabriel Souza, Senior Business Reporting Specialist at Nordea, also said AI can increase efficiency for CRO teams.
In today’s competitive market, swift access to data collection and analysis will make CRO teams more agile in narrowing their focus and implementation on what improves the overall customer experience.
2 Brands will create personalized experience for customers
It is nearly impossible to create personalized experiences for millions of website visitors without the use of AI. Manually doing this is time-consuming and often leads to results that would underperform regular A/B tests.
Jake Sapirstein, Founder and Head of Strategy of LiftCentro, a CRO agency, said that AI-powered machine learning has a profound impact on CRO in a couple of different scenarios.
"When applied to the delivery of highly personalized experiences, AI-powered machine learning can elevate conversion rates by zeroing in on what works best for each individual visitor," he said.
Because customer interests and needs are always evolving, AI can quickly adapt to these changes by predicting what content customers want and offering product recommendations with algorithm-driven suggestions.
By adopting AI technology for your website personalization, you can serve customers with highly customized recommendations for content based on their predicted preferences, which helps increase conversions by giving them more of what they want.
Julien Descombes, Digital Communication Manager at Toyota, has firsthand experience in using AI to personalize experiences for customers.
3 Optimization will include real-time flexibility
Flexibility—the ability to make real-time adjustments—is important in marketing and optimization as it’s the only way to meet customers’ ever-evolving needs. With AI, you can segment users more effectively based on their behavior.
Amrdeep Athwal, Founder of Conversion Matters Ltd, a CRO Agency, said AI is already making the jobs of CROs easier by offering greater flexibility in tests that optimizers can run.
4 Routine tasks will be automated
To provide great CX, companies need to understand how visitors consume content and search for products.
Analyzing the data generated by customer behavior is time-intensive. And often leaves you unable to make quick decisions that impact conversions. AI can help optimizers automate routine tasks like data analysis to they can make business decisions.
Andra Baragan, Founder of Ontrack Digital, a CRO agency, agrees that AI can help CROs automate data analysis, but the final decision lies with the CRO.
“I would say that there have always been two sides to the job of a CRO specialist—one is knowing the numbers and one is understanding the behavior," Andra says. "I think you could compare it to the work of a doctor or a mechanic—you need to diagnose by looking back through hundreds of other cases or similar situations and you need to come up with a treatment based on that. That’s where I think AI comes in to assist in CRO.”
Using AI to automate analysis of previous experiments, cases and websites can shorten the time needed to run comprehensive tests that generate lifts.
5 Organizations will create better user experiences
Knowing how each customer navigates your website is crucial to creating a world-class user experience.
The insights from navigational and behavioral data on your site can help you create a user experience that wows visitors. And AI can be instrumental in that.
Jake Sapirstein believes AI use in complex experimentation can lead to getting insights faster.
And you can implement changes that work. Or roll back those that don’t work.
“AI and machine learning have the unique ability to optimize against deeper and more granular micro-segments - something that humans are not wired to do, quickly and easily”.
This gives you more access to go deeper into what your customers want and need. Thus, providing them with a seamless user experience.
Athwal agrees that AI is already helping optimizers improve user experience on their websites by finding problem areas quicker.
“New machine learning insights in analytics tools like GA that are making it quicker and easier to find problem areas of a site,” he said.
The faster you find conversion leaks in your website, the faster you can fix them.
6 AI should be paired with respect for users’ privacy
A respect for users’ privacy needs to be paired with using AI in marketing activities.
This is vital in industries, like finance and healthcare, where providing better services and experience to customers may rely on using personally identifiable information (PII).
Kathy Baxter, Principal Architect, Ethical AI Practice at Salesforce, believes companies need to be more ethical in using AI.
While AI is a useful tool in providing better experiences for customers, its use needs to be balanced by respecting customers’ right to privacy and asking for consent where necessary.
7 How to move forward with AI
CRO specialists can already leverage AI when using A/B testing tools. In the future, AI capabilities will likely become more ubiquitous among experimentation and personalization softwares, with the strength of AI algorithms becoming a key value proposition.