Search by Algolia
Feature Spotlight: Query Rules
product

Feature Spotlight: Query Rules

You’re running an ecommerce site for an electronics retailer, and you’re seeing in your analytics that users keep ...

Jaden Baptista

Technical Writer

An introduction to transformer models in neural networks and machine learning
ai

An introduction to transformer models in neural networks and machine learning

What do OpenAI and DeepMind have in common? Give up? These innovative organizations both utilize technology known as transformer models ...

Vincent Caruana

Sr. SEO Web Digital Marketing Manager

What’s the secret of online merchandise management? Giving store merchandisers the right tools
e-commerce

What’s the secret of online merchandise management? Giving store merchandisers the right tools

As a successful in-store boutique manager in 1994, you might have had your merchandisers adorn your street-facing storefront ...

Catherine Dee

Search and Discovery writer

New features and capabilities in Algolia InstantSearch
engineering

New features and capabilities in Algolia InstantSearch

At Algolia, our business is more than search and discovery, it’s the continuous improvement of site search. If you ...

Haroen Viaene

JavaScript Library Developer

Feature Spotlight: Analytics
product

Feature Spotlight: Analytics

Analytics brings math and data into the otherwise very subjective world of ecommerce. It helps companies quantify how well their ...

Jaden Baptista

Technical Writer

What is clustering?
ai

What is clustering?

Amid all the momentous developments in the generative AI data space, are you a data scientist struggling to make sense ...

Vincent Caruana

Sr. SEO Web Digital Marketing Manager

What is a vector database?
product

What is a vector database?

Fashion ideas for guest aunt informal summer wedding Funny movie to get my bored high-schoolers off their addictive gaming ...

Vincent Caruana

Sr. SEO Web Digital Marketing Manager

Unlock the power of image-based recommendation with Algolia’s LookingSimilar
engineering

Unlock the power of image-based recommendation with Algolia’s LookingSimilar

Imagine you're visiting an online art gallery and a specific painting catches your eye. You'd like to find ...

Raed Chammam

Senior Software Engineer

Empowering Change: Algolia's Global Giving Days Impact Report
algolia

Empowering Change: Algolia's Global Giving Days Impact Report

At Algolia, our commitment to making a positive impact extends far beyond the digital landscape. We believe in the power ...

Amy Ciba

Senior Manager, People Success

Retail personalization: Give your ecommerce customers the tailored shopping experiences they expect and deserve
e-commerce

Retail personalization: Give your ecommerce customers the tailored shopping experiences they expect and deserve

In today’s post-pandemic-yet-still-super-competitive retail landscape, gaining, keeping, and converting ecommerce customers is no easy ...

Vincent Caruana

Sr. SEO Web Digital Marketing Manager

Algolia x eTail | A busy few days in Boston
algolia

Algolia x eTail | A busy few days in Boston

There are few atmospheres as unique as that of a conference exhibit hall: the air always filled with an indescribable ...

Marissa Wharton

Marketing Content Manager

What are vectors and how do they apply to machine learning?
ai

What are vectors and how do they apply to machine learning?

To consider the question of what vectors are, it helps to be a mathematician, or at least someone who’s ...

Catherine Dee

Search and Discovery writer

Why imports are important in JS
engineering

Why imports are important in JS

My first foray into programming was writing Python on a Raspberry Pi to flicker some LED lights — it wasn’t ...

Jaden Baptista

Technical Writer

What is ecommerce? The complete guide
e-commerce

What is ecommerce? The complete guide

How well do you know the world of modern ecommerce?  With retail ecommerce sales having exceeded $5.7 trillion worldwide ...

Vincent Caruana

Sr. SEO Web Digital Marketing Manager

Data is king: The role of data capture and integrity in embracing AI
ai

Data is king: The role of data capture and integrity in embracing AI

In a world of artificial intelligence (AI), data serves as the foundation for machine learning (ML) models to identify trends ...

Alexandra Anghel

Director of AI Engineering

What are data privacy and data security? Why are they  critical for an organization?
product

What are data privacy and data security? Why are they critical for an organization?

Imagine you’re a leading healthcare provider that performs extensive data collection as part of your patient management. You’re ...

Catherine Dee

Search and Discovery writer

Achieving digital excellence: Algolia's insights from the GDS Retail Digital Summit
e-commerce

Achieving digital excellence: Algolia's insights from the GDS Retail Digital Summit

In an era where customer experience reigns supreme, achieving digital excellence is a worthy goal for retail leaders. But what ...

Marissa Wharton

Marketing Content Manager

AI at scale: Managing ML models over time & across use cases
ai

AI at scale: Managing ML models over time & across use cases

Just a few years ago it would have required considerable resources to build a new AI service from scratch. Of ...

Benoit Perrot

VP, Engineering

Looking for something?

facebookfacebooklinkedinlinkedintwittertwittermailmail

You liked that article you read on Medium.com written by a teen about what teens think of the various social media–site options. Hey, would you also like this one by a 60-something about what Baby Boomers think of Facebook?

Similar-content recommendations that appear as you’re browsing online keep you intrigued and learning. They make you feel like online content providers such as video and TV show sites, newspaper publishers and writing sites, social media, job boards, and other-content-type hubs are attuned to just what you want. They make you wonder if even you may not be the expert on what you want to read, watch, or interact with, after all, sometimes they suggest related content you don’t think to look up. At any rate, if you consider yourself an information sponge or a budding expert on a topic, you probably go out of your way to look for related-content recommendations.

You’re a VIP

People like you are great news for companies that provide online content. If you’re following links around their site, you’re driving page views. The longer you’re doing that, the more likely you are to convert, such as by signing up as a member in order to read (or watch or listen to) more of that juicy content. Helping you find the content pages you need or want, and extending the number of minutes or hours you spend captivated, is their key to driving conversion. 

For content site owners, that’s where related content recommendations come in. When they can hit the nail on the head in terms of additional-content-recommendations functionality, it constitutes a compelling reason for you to stick around on their site, as well as to keep coming back and perhaps become a loyal member or subscriber.

What are related content recommendations?

Related content recommendations are links to similar relevant content based on the user’s search activity or other indicators. Think of a time you went online to find a new movie, and how the interface didn’t forget what you’d been searching for the week earlier; it recommended items that made you want to learn more. Or when you read that news article on the New York Times site, which then suggested an additional interesting article, which you devoured from top to bottom. 

How does related content generation work?

On the technical level, a recommendation engine analyzes the interactions of users alongside different items to draw links between those items. From there, it uses qualitative data to display related content recommendations.

But that’s just the beginning. The more inputs and actions (e.g., completed searches) a user logs, the more accurate their recommendations can become. In time, the search software builds a reliably  accurate personalized profile. So reliable that some people feel like it’s akin to an old friend who just “knows them.” And, well, that high-quality awareness easily leads to a lower bounce rate and solid long-term “friendship.”

The benefits of doing related content right

So far, so good. But many websites don’t come close to (or even attempt to shoot for) the online personalization levels that a megasite like Netflix does. That’s unfortunate, because more and more, consumers expect to be duly showered with related content suggestions.

Remember, your mission — should you choose to accept it — is to make people prefer to stay on your site and see what else you’ve got going on. The existence of related recommendations facilitates this worthy endeavor, which can then wildly elevate your site’s desirability.

As you can imagine from the gist of this post so far, there are many benefits, many of which have ripple effects, of setting up related content recommendations. Here are arguably the top three:

Delighted, grateful users 

Being offered the next investigative story in a series or the next related topic on a blog-post site, or the newest movie in the genre they love, draws people in. They warm to it and may remember how much they enjoyed the content. They bookmark your site and visit you often. You gain their undying loyalty.

Improved user engagement 

Phenomenal user engagement levels and a top-notch user experience go hand in hand. When related information recommendations are presented in the right way, site visitors can’t help but be enticed to trawl around your site, explore similar topics, and enrich their understanding.

Skyrocketing conversion

Recommending related content (whether in the form of regarding products, blog posts, news items, or something else) is a nice idea; it’s also one proven to drive conversion and revenue. As online retailer Gymshark discovered, with Algolia Recommend, they could increase their order rate 5.5% for customers who clicked on a recommended product. Plus, their order rate for mobile increased by an eye-popping 150%.

How to rock related content

OK, so you’re sold on the importance of doing this related content recommendation thing. But how do you get your site to cooperate? Can your users see a path to your related content from the content they just read or interacted with?

To get the best results from rolling out related content suggestions, keep in mind that:

Right is wrong

There’s a tendency for people online to perceive certain web page elements on the right side of the page as ads, and therefore ignore them (whether or not they’re ads). Yep, people have trained themselves to avoid being diverted to advertisers’ landing pages. Which means the right side is not the best spot for introducing related content.

The bottom is out

A web page template that relegates related content links to the bottom of the page is a losing proposition. Your users simply won’t see them  waaaay down there.

We’re ruling out options here. So where, then, is left to stick these things?

Merchandising experts advise websites to put them directly below the content (as opposed to at the very bottom of the page). This is the sweet spot where viewers are likely to cast their eyes; the jumping-off point for further content exploration.

Relevance is a requisite

If someone’s looking for news articles on climate change, they don’t want to see one about the Kardashians. If they’re looking at a cute rom-com flick, they probably don’t want you to suggest some depressing documentary.

Providing a broadly curated batch of links might seem sensible, but if the items are not related enough, they’re not going to get noticed. So even if you’re dying to promote some particular content, think twice if it’s not relevant. Folks have landed on your site for a specific content-driven reason, and now’s not the time to go off on a tangent. Give them your best related content menu.

Expert help is available

To make related content recommendations work, it helps to have technology capable of meeting your goal of building engagement and increasing conversion. Something easy to implement, adapt, and streamline to meet your users’ content needs. That way, whether people go straight to a content detail page or randomly click homepage headings, you’re confident that you’re offering the right suggestions. 

Our recommendation for you? Learn more

We’re glad you’ve taken a minute to check out this content that we hope will help you transform your site performance. Thanks for your interest!

And now for a few related content recommendations (and in the right location to boot):

You might also like

Benefits of providing great content recommendations

Why Algolia Recommend?

How to contact us

About the author
Catherine Dee

Search and Discovery writer

linkedin

Recommended Articles

Powered byAlgolia Algolia Recommend

What is content discovery, and how can you make it easier for your users to find what they want?
ux

Catherine Dee

Search and Discovery writer

How can related product recommendations boost engagement and ROI?
ux

Catherine Dee

Search and Discovery writer

The anatomy of high-performance recommender systems – Part V
ai

Paul-Louis Nech

Senior ML Engineer