User Experience and AI: Website Personalization at Scale

In this article, we explore the power of AI to enhance end user experience by personalizing each individual's website visit. Key goal for user experience and AI being: how do we use AI to increase average session time and engage users more effectively — how do we only serve them the best, most relevant, and least duplicative content from a site's vast library?

Apparently AI thinks that "website personalization" comes down to invoking more color pink — AI (of course) wouldn't be the first! 

Defining "User Experience" For High-Traffic Websites

To state bluntly, user experience (aka "UI/UX" = user interface/user experience) determines ultimate success for website(s) with millions of monthly pageviews, and those websites' owners.

To be clear, we're not taking away from the importance of quality and E-E-A-T of content —in the business of millions of monthly pageviews, content is king, period. However, the whole experience of consuming content has to be considered — the best article ever written will never be seen if published to a slow-loading site.

Thus, the importance of "user experience:" how website visitors perceive and interact with a website's content, according to a smorgasbord of data / characteristics such as: (aforementioned content quality), site speed, design, navigation, usability, likability, and configuration of revenue-generating elements for ads, affiliate, lead gen, and subscriptions. 

Remember:

• A positive user experience registers in website analytics platforms in the form of increased engagement, higher conversion rates, longer average session times, and higher revenue per visit.
  
  
• On the other hand, a poor user experience registers as high bounce rates, low user retention (e.g. declining direct traffic), and declining referrals from search, syndication, etc.

Poor user experiences abound, but suffice it to say that a high-traffic website needs to avoid the "chumbox" reputation that comes with traffic-killing tactics such as "no viewable editorial content" (i.e. only ads or revenue-generating elements, no authentic, human-written content). Not only does the poor content quality churn users, but it also churns syndication and search platforms who don't refer their audience to sites with longer loading times and glitchy rendering.

Thus, when thinking about how to optimize individual user experiences for an audience utilizing AI, website owners need to most importantly understand their target audience and its preferences through a data lens — both qualitative and quantitative. Thinking about audience in this way accommodates a vision for past/present/future, aka the audience you have vs. the audience you want.

(Friendly reminder, your editorial's team perspective has to be invoked in any/all of these discussions about using AI for audience outcomes. Reason being: the editorial team has the expertise the audience—not to mention Google and other referral source of traffic—ultimately wants.)

Net/net, ultimate success using AI to power website personalization will come from inside these qualitiatve and quantitive data analyses; success in AI = success in first-party data. The prize in this case is rich: leveraging AI algorithms and machine learning, websites can potentially tailor the delivery of their content at the individual level. Same goes for the design, and functionality for every single visit, allowing site owners to maximize conversion rates every step of the funnel way. 

Let's Unpack: Website Personalization = Apex of User Experience and AI

From looking at industry trends, AI will eventually play a crucial role in website personalization; this is a question of when. 

Reason being: AI can analyze vast amounts of data and identify patterns and trends that humans would otherwise miss. Behind the scenes, traditional personalization methods too often rely on manual segmentation / rule-based approaches, which are time-consuming and limited in their effectiveness — not every company has the same resources as a Forbes-level enterprise (related: the bulk of companies in website publishing are still OK). 

Keep in mind, we're still years away from the point where website owners can just  rely solely on AI to be an expert website designer or personalization engine. We're not close to that point. Instead, think of AI's role as that of a 1,000 interns who can pay attention to each individual website user—and what their individual website behavior tells you about what they want. To use an analogy:

In essence, AI-powered website personalization will use machine learning and algorithmic optimization to collect and analyze user data, taking into account browsing behavior, demographics, preferences in a way an individual human couldn't. This data will then be used to create personalized content experiences in real-time, i.e. delivering relevant content, recommendations, and offers at the individual user level.

(nb: AI should never be creating content for the brand on its own; this doesn't provide value)

From a tech perspective, this essentially means content prompts/suggestions that  come via pop-up, in-line content "round-ups," footer-content placements, sidebars, HelloBar-esque header drop-downs etc.

By partnering with AI to understand individual users' needs and interests, website owners will be able to increase engagement and encourage users to stay longer on their site (which is to say: "increase average session time").

User Experience and AI: Dynamic Content Recommendations

One of the key ways AI can increase average session time on a high-traffic website is through dynamic content recommendations. AI algorithms can analyze user behavior and preferences to predict what content a user is most likely to be interested in. This can include personalized content recommendations, related articles or products blog posts, and targeted advertisements.

Today's Stories: AI can serve specific, real-time content recommendations to individual visitors via targeted round-up modules including "Today's Top Stories," "Trending Articles," "Most Comments," etc.: 

By serving to the user relevant and personalized content recommendations, websites will keep users engaged, as well as encouraging them to explore more pages and spend more time on the site. The increased average session time will demonstrate the improvement in overall user experience, and can be used to measure project ROI via cross-channel Analytics.

Utilizing AI for Real-Time User Engagement

In addition to content recommendations, AI can also be used for real-time user engagement. AI-powered chatbots or virtual assistants can provide personalized assistance to users, answering their questions, guiding them through the website, and addressing their concerns. These AI-powered interactions can simulate human-like conversations and provide a seamless and personalized user experience.

By utilizing AI for real-time user engagement, websites can create a more interactive and engaging experience for users. This can help increase average session time, as users spend more time exploring the website and interacting with AI to find a site's most valuable and important content.

For example: one of the easiest things in the world is finding a website publisher who would like to improve the engagement of their "site search" module. AI makes a ton of sense for site search, as AI can be trained to be an expert on the content published/housed within a site, and how to serve it to a user on a personalized level (so that they ultimately spend more time during each session). Instead you're stuck forcing people to guess their way into content: 

Measuring the Success of User Experience and AI for Website Personalization

To measure the success of AI-powered website personalization, website owners can track various metrics but should ultimately focus on increasing average session time (while controlling for faster page load speed).

Other metrics include bounce rate, conversion rate, and user satisfaction — i.e. all the online publishing metrics used to gauge how much and many monetizable content blocks should exist in-line and otherwise with the editorial team's E-E-A-T laden output.

By A/B testing/comparing average session time of visitors to static websites vs. AI-powered personalized visits, website owners can assess the exact value of how AI grows audience and earnings. Because AI is helping an individual user find existing, valuable content, rather than generating content (or even authors), the ROI on AI will be much higher.  

It's of course important to regularly analyze and optimize AI-powered personalization strategies based on the collected data and feedback loop in place. By continuously focusing on the end user experience, websites can ensure that AI is effectively deployed to increase average session time and help publishers with millions of monthly visitors achieve and exceed their desired audience and earnings goals.