Solve UX Challenges With Automated UX Recommendations from Evolv AI

How often do you go back and look at results from legacy AB tests? How many people in your organization know where to find legacy AB test results?

Knowledge management within an experimentation program is far from a solved problem, and knowledge sharing between teams or programs is even more of a pipe dream. Typically, individuals conducting experiments become the sole holders of insights, later translating them into personal sets of best practices or the colloquial “At <company X>, this had a big impact on <metric>”.

While individual growth is great, gaps in collective learning lead to missed opportunities for organizational growth. And if you ask an experimenter why translating findings is lackluster, you’ll usually hear “because it’s hard to orchestrate.” Mostly due to the platforms we’re using to run our experiments.

How Modern Experimentation Platforms Struggle

Experimentation platforms aren’t entirely flawed. They excel at compiling comprehensive databases of conducted experiments. However, they are flawed in their ability to utilize learnings from past tests effectively. And who has time to go back through all of the past experiments run by your entire company to make decisions about your upcoming release? Or to take the results of one experiment and ensure that every other place those learnings could be applied benefits from them?

Advancements in AI, however, are making it easier for businesses to tap into their accumulated knowledge and transform anecdotal evidence into actionable data, fostering a culture of continuous improvement across the entire organization.

Automated UX Recommendations to Bridge the Gap

Automated UX Recommendations, Evolv AI’s latest feature, is intended to solve for the gap between insights and action.

Automated UX Recommendations combines computer vision, behavioral analytics, segment affinity, UX research, and your experiment data to ensure every user in your digital experience achieves their goal. Whether they pick up your latest sneakers, sign up for a new phone plan, or apply for a mortgage, they should and can benefit from the best experience possible.

Automated UX Recommendations can:

• Create new ideas based on the latest UX and Cognitive Research
• Help prioritize ideas based on their potential uplift
• Recommend personalization opportunities based on your most important segments
• Recommend segments that might need something a little different from your average user
• Recommend other areas of your experience where new learnings can be applied

The DNA of Automated UX Recommendations

With experience, great UX, design, product, and marketing leaders can begin intuitively understanding the fundamentals of an observed change and how to successfully apply them in a new context to improve design, messaging, experience, and so on.

Evolv AI learns and functions in a similar way. With each change that is validated in production, Evolv AI extracts the fundamentals of the change or the “DNA” of the idea. That information is then generalized for future use. When faced with a new experience with or without user data, Evolv AI can generate ideas based on the “DNA” of past ideas across different digital experiences, different industries, and different goals. Evolv AI then uses these models to predict contextual opportunities, hypotheses, and novel recommendations to improve your business outcomes.

Unlocking the Full Power of Evolv AI

Auto-Recommendations is only one feature of Evolv AI’s fully automated DXO platform. When used in combination with Evolv AI’s full suite of tools, the platform emulates the entire design thinking process:

• Empathize: Analyze vast amounts of user interaction data, identifying patterns, behaviors, and pain points without requiring manual observation or interviews.
• Define: Pinpoint specific issues or opportunities for improvement in the digital experience with more precision and velocity than traditional methods.
• Ideate: Provide tailored solutions drawn from a vast database of customer behavioral data, past successes, current trends, and cross-industry insights, significantly increasing the breadth and innovation of foundation ideas.
• Prototype: Create testable versions of web pages, features, and user flows with generative AI, reducing the time and resources needed to develop assets.
• Optimize: Explore vast search spaces with billions of possible experiences, learning from each user what will help the next user convert.
• Personalize: Connect each user with the hyper-personalized experience that's perfect for them.

Together, we are setting a new standard for digital excellence powered by insights, shaped by experience, and optimized for impact. Want to learn more? Book a demo with an Evolv AI expert today.