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Using Smart Recommendations and Related Content to Automate Reader Engagement

Eleanor Hecks

Users arrive on a page with a specific goal in mind. After reading the opening content, they pause to consider whether to keep reading or to leave. Sites that offer strategically placed recommendation sections or related content enhance the flow, allowing readers to avoid the decision of what to do next.

Turning a dead-end page into a jumping-off point can help small and midsize businesses by increasing the time visitors spend on the website. If the user has visited your page before or comes via a specific link, you can create highly relevant content to help them navigate your sales funnel without a hard sales pitch.

Why Readers Need Direction

Readers often start their research on sites like Google or ChatGPT. Google advises that well-structured content improves the page experience for readers and may help boost your site’s discoverability.

If you’ve spent any time shopping online, you have probably seen smart recommendations in action. As you click on different products or input terms into the site’s search bar, the company stores information about your preferences. When you purchase something or add it to your cart, you’ll continue to see recommendations for similar products every time you visit the site.

In the right place, automated elements can help with consumer decision-making. People may land on your page out of curiosity or because they seek a solution. Their entry points and the type of content they seek offer clues about where they are in the buyer’s journey and the content they are most likely to respond to. Current research shows companies now increasingly automate daily tasks, including customer experience, by leveraging analytics to create stronger engagement.

Even if your site isn’t e-commerce, you can use the same method to deliver content that engages users by giving them exactly what they need to solve a pain point. Without directions, the customer may bounce away and never return.

Smart recommendations are informed via behavioral data and contextual signals, indicating which content a reader is most likely to find helpful. These indicators can include time on page, clicks and topics of interest. The system adapts to readers’ preferences over time.

The approach also benefits small and midsize businesses, as the tool drives engagement without requiring manual updates after the initial implementation. It’s like an invisible assistant that can remember what the audience was interested in and provide the next steps.

How Related Content Complements the Journey

Related content modules, found at the end of posts, on product pages or beside similar long-form content, display items based on topical relevance. The modules are typically not personalized but serve as a stopping point for readers, keeping them engaged. The next piece of information is there when they need it, which can lead to longer viewing sessions.

Smart recommendations and related content improve site performance by maximizing the reader experience. By confidently leading the user through the funnel, the company establishes authority and positions itself as a resource. Automated surfacing also raises the profile of low-engagement posts or evergreen content, making them more visible and accessible. Visitors who stay longer on a website are more likely to encounter more conversion points, such as calls to action, newsletter boxes and product pages, because they experience a smoother flow.

You may not always have in-depth knowledge about the person visiting your page. It could be their first time there, or they may have blockers that prevent tracking. However, you have an idea of the behaviors of your typical buyer. You can create a persona and tailor recommendations to your average user. Put their experience first. If you were in their shoes and you read a piece of content, what would your next natural question be?

You can use AI to identify who your average user is and what their content preferences are, and then ask what their next question might be. Verify accuracy by reviewing search results and the “People Also Ask” sections on Google, as well as considering the touchpoints on your website.

How Automated Engagement Works Behind the Scenes

Automated engagement tools use data models, metadata and site structure to deliver a personalized or semi-personalized experience. Business owners don’t necessarily need to know how every tool at their disposal works, but they should be familiar with a few related terms. You can tap into the power of popular recommendation tools like HubSpot, Storyblok and Algolia.

Metadata

With metadata, such as categories and tags, the system can make faster decisions, resulting in more relevant and accurate recommendations. If you sell household goods and a site visitor searches for cookware, the next natural recommendation might be for kitchen tools, not throw pillows.

User Behavior

If readers regularly read two articles together, the system will learn to recommend one with the other because that is a pathway readers frequently take. Ideally, you will recommend based on each reader’s specific path, but some tools look at the big picture of when readers convert into customers. The system can then recommend content most likely to result in a sale.

You can also encourage users to read specific content by using a typographical hierarchy to signal to the reader when you’re sharing important information. Readers tend to read in an F-pattern and focus on the upper left of the screen before scrolling across.

Fresh Content

The newest posts are prioritized, with recommendation algorithms giving extra weight to posts with recently posted content and displaying them sooner. This encourages users to explore newer content.

Practical Tips for Adding Recommendations to a Website

Knowing where to place recommendations without making them disruptive is a skill you’ll develop through practice and by gauging user reactions. Every audience is unique, so you must use data to determine what works best for yours.

Start by placing recommendations after a long-form or tutorial post, so readers can easily find them while browsing. Recommendations should match the site’s design to feel like a natural part of the user experience.

Any smart content tool can meet your needs, but you must enter the correct parameters — consistent tagging leads to better recommendations. Tags may drift in meaning or overlap over time, so they may periodically need a minor cleanup to work better. Monitoring, analyzing and testing should become a regular part of your routine. A basic A/B test can show whether readers prefer a grid of cards, a row of cards or a text list. The easier it is to interact with a module, the better.

Start Offering Smart Recommendations Today

Automated engagement creates natural touchpoints throughout your site, recommending content that supports the reader’s needs and interests. When you consider user behavior and site goals, you can achieve a smoother flow to your pages and guide visitors to the next helpful step. Smart recommendation tools enhance engagement and increase time spent on the page. Start with a few placements and add on as you develop more content. You’ll likely see impressive results.