Connect with us

MARKETING

How the LinkedIn Algorithm Works in 2023 [Updated]

Published

on

How the LinkedIn Algorithm Works in 2023 [Updated]

LinkedIn bills itself as “the world’s largest professional network” — and they have the numbers to prove it. With over 875 million members in more than 200 countries and regions, LinkedIn is immensely popular and well-used. On top of the sheer size of the platform, nearly 25% of users are senior-level influencers; about 10 million are categorized as C-level executives, and LinkedIn classifies 63 million as “decision makers.”

If you’re a B2B marketer or brand, you probably already know this social media platform offers you an excellent opportunity to reach your target demographic. However, seizing that opportunity is easier said than done since LinkedIn uses a unique algorithm to serve content to users.

In this article, we will walk through how the LinkedIn algorithm works in 2023, best practices for beating the algorithm with organic content, and how brands can elevate their presence on the platform.
 

What is the LinkedIn Algorithm?

 
The LinkedIn algorithm is a formula that determines which content gets seen by certain users on the platform. It’s designed to make each user’s newsfeed as relevant and interesting to them as possible to increase engagement and time spent on the platform. In this way, the LinkedIn algorithm is similar to the Facebook or TikTok algorithm, though LinkedIn’s is slightly more transparent (which is good news!). 

In fact, LinkedIn itself is a good source for demystifying the algorithm and understanding what content is prioritized for members. But the general function of the LinkedIn algorithm is to review and assess billions of posts every day and position those that are most authentic, substantive and relevant to each user at the top of their feeds.  

How the algorithm achieves that function is a little more complex.
 

How the LinkedIn Algorithm Works in 2023

 
 
LinkedIn users’ feeds don’t show posts in chronological order. Instead, the LinkedIn algorithm determines which posts show up at the top of users’ feeds, meaning that sometimes users see older or more popular posts before they see more recent ones.

Several factors influence the LinkedIn algorithm, and the factors change relatively often. Let’s take a closer look.
 

1. Assess and Filter Content by Quality

 
When someone posts on LinkedIn, the algorithm determines whether it’s spam, low-quality, or high-quality content. High-quality content is cleared, low-quality content undergoes additional screening, and spam content is eliminated. 

 

  • Spam – Content flagged as spam can have poor grammar, contain multiple links within the post, tag more than five people, use more than ten hashtags (or use expressly prescriptive hashtags like #follow, #like, and #comment) or be one of multiple postings from the same user within three hours. 
  • Low-quality – Content categorized as low quality isn’t spam but is judged as not particularly relevant to the audience. These posts can be hard to read, tag people who are unlikely to respond or interact, or deal with topics too broad to be interesting to users.  
  • High-quality – “Clear” content is easy to read, encourages engagement, incorporates strong keywords, uses three or fewer hashtags, and reserves outbound links to the comments. In other words, it’s something your audience will want to read or see and react to in a substantive way.

 

2. Test Post Engagement with a Small Follower Group

 
Once a post has made it through the spam filter, the algorithm distributes it to a small subset of your followers for a short time (about an hour) to test its ability to generate engagement. If this group of followers likes, comments or shares the post within this “golden hour,” the LinkedIn algorithm will push it to more people. 

If, on the other hand, the post is ignored, or your followers choose to hide it from their feeds (or, worst of all, mark it as spam), the algorithm will not share it further.  
 

3. Expand the Audience Based on Ranking Signals

 
If the algorithm decides your post is worthy of being sent to a broader audience, it will use a series of three ranking signals to determine exactly who sees it: personal connection, interest relevance and engagement probability. 

These signals boil down to the level of connection between you and the user who potentially sees the post, that user’s interest in the content’s topic and the likelihood of that user interacting with the content. We’ll break down exactly what these ranking signals are further in the post.
 

4. Additional Spam Checks and Continued Engagement Monitoring

 
Even after a post is pushed to a broader audience, the LinkedIn algorithm continues monitoring how users perceive it in terms of quality. If your content is marked as spam or entirely ignored by the new audience group, LinkedIn will stop showing it to those audiences. On the other hand, if your post resonates with new audiences, LinkedIn will keep the post in rotation. So long as the post gets a steady stream of engagement, posts can stay in circulation for months.
 

8 Best Practices to Make the LinkedIn Algorithm Work for You

 
 Understanding how the LinkedIn algorithm works is the first step to reaching more people on LinkedIn and ensuring your content is well-received and engaging. The next step is optimizing your content based on the factors the algorithm prioritizes to maximize its effect. This is where mastering the ranking signals comes into play.

Here are eight tips for crafting high-performing LinkedIn content:
 

1. Know What’s Relevant to Your Audience

 
Relevance is what the algorithm prizes above all other content qualities. For LinkedIn, relevance translates to engagement, which leads to more time spent on the platform, which results in more ad revenue and continued growth. Following this tip will win you points in the “interest relevance” and “engagement probability” ranking categories. 

The entire LinkedIn ecosystem is set up to prioritize highly relevant content. To ensure your posts are relevant, create content focused on your niche and your audience’s specific needs and interests. As LinkedIn’s then-Director of Product Management Linda Leung explained in 2022, “we are continuously investing in the teams, tools, and technology to ensure that the content that you see on your feed adds value to your professional journey.” 

Use customer research and analytics from other social media platforms to learn more about what your audience wants to know. Focus on creating high-quality, valuable content that helps professionals succeed in formats they prefer (for example, videos, which get three times the average engagement of text-only posts). But above all, posting content that is personal and has industry relevance is vital. 
 

2. Post at the Right Time

 
As with most things, timing is crucial for successful LinkedIn posts. It’s even more critical when considering the “golden hour” testing process integral to the algorithm’s rankings. Remember, how much interaction a post gets within the first hour after it’s published determines whether it gets pushed to a broader audience. That means posting at the optimal time when your followers are online and primed to respond is a central factor to success.

You are the best judge of when your top LinkedIn followers and people in your network are most likely to be on the platform and engaging with content. But for the general public, data suggests the best time to post is at 9:00 a.m. EST on Tuesdays and Wednesdays. Cross-reference these times with your own analytics and knowledge about your audience — like a common time zone, for example — to find the best time for your posts.
 

3. Encourage Engagement

 
Your post format can play a significant role in user engagement. The LinkedIn algorithm doesn’t explicitly prioritize videos over photo and text posts, but LinkedIn’s internal research has found video ads are five times more likely to start conversations compared to other types of promoted content. 

Asking a question is another great way to encourage interaction with your post. If you’re sharing industry insights, open the conversation to commenters by asking them to share their opinions or experiences on the topic. 

Additionally, tagging someone in your LinkedIn post can expand its reach, but only tag relevant users and people likely to engage with the post. You don’t automatically get in front of a celebrity’s entire following just because you tagged them. In fact, the algorithm’s spam filter can penalize your post for that. But when you tag someone relevant, the tagged person’s connections and followers will also see your post in their feeds. 
 

4. … But don’t beg users to engage

 
The LinkedIn algorithm penalizes posts and hashtags that expressly ask for an engagement action like a follow or a comment. In an official blog post from May 2022, LinkedIn said that it “won’t be promoting” posts that “ask or encourage the community to engage with content via likes or reactions posted with the exclusive intent of boosting reach on the platform.” Essentially, content that begs for engagement is now considered low-quality and should be avoided.
 

5. Promote new posts on non-LinkedIn channels

 
LinkedIn doesn’t exist in a vacuum, and neither do its users. Content that gains traction in other channels can help boost LinkedIn posts and vice versa. Sharing posts on your website, other social media platforms, or with coworkers can spark the initial engagement required for a viral LinkedIn post. Promoting content on other channels can also encourage inactive LinkedIn users to re-engage with the platform, and that interaction will be interpreted as net new engagement for your post.
 

6. Keep Your Posts Professional

 
As the “professional social networking site,” LinkedIn has a well-honed identity that extends to the type of content it favors. Specifically, business-related content that users will find relevant and helpful to their careers or within their industry. 

This might seem common sense, but it can be tempting to think that content that earns lots of clicks or likes on other social media platforms will perform similarly when cross-posted on LinkedIn. Unfortunately (or fortunately), hilarious memes, TikTok dance clips and personal videos don’t resonate with the LinkedIn algorithm. 
 

7. Avoid Outbound Links
 
 

The urge to include an outbound link in a LinkedIn post is real, especially for B2B marketers using LinkedIn to generate leads and traffic to their websites. But this is universally regarded as a tactic to avoid. LinkedIn wants to keep users on the platform and engaging; link-outs defeat that purpose. Therefore, the algorithm tends to downgrade content that includes an outbound link. 

Posts without outbound links enjoyed six times more reach than posts containing links. Does that mean there’s no room for a link to your brand’s website or blog with additional resources? No. But the best practice is creating content that encourages a conversation and letting the audience request an outbound link. If you feel compelled to link to something off-platform, include that link in the comments. 
 

8. Keep an Eye on SSI

 
LinkedIn has a proprietary metric called the Social Selling Index, which measures “how effective you are at establishing your professional brand, finding the right people, engaging with insights, and building relationships.” Per LinkedIn, social selling leaders create 45% more opportunities than those users with lower SSI scores.

A higher SSI boosts users’ posts closer to the top of their audience’s feeds. While this impacts post visibility for individual posters rather than brands and companies, it remains a significant influence on LinkedIn’s algorithm and is worth noting. 

Source: Business 2 Community
 

An Overview of Ranking Signals on LinkedIn’s Algorithm

 
 
As mentioned earlier, there are three ranking signals the LinkedIn algorithm uses to rank posts in a user’s feed:
 

  1. Personal connections
  2. Interest relevance
  3. Engagement probability

 
And here’s how each signal impacts a post’s ranking:
 

Personal Connections

 
In 2019, LinkedIn began deprioritizing content from mega influencers (think Oprah and Richard Brandon) and instead began highlighting content from users’ personal connections. To determine a user’s connections, LinkedIn considers these two things:
 

  1. Who a user works with or has previously worked with
  2. Who a user has interacted with before on the platform

 
At the top of the feed, users now see posts by people they engage with often and by anyone who posts consistently. Users also see more posts from connections with whom they share interests and skills (according to their LinkedIn profiles). 

That said, as of 2022, LinkedIn is also “creating more ways to follow people throughout the feed experience,” including thought leaders, industry experts, and creators that may be outside of a user’s network. So it’s important to remember that personal connection is just one factor influencing post ranking.
 

Interest relevance

 
Relevance is another of the three ranking signals – and in many ways, the most important one. LinkedIn explains on its engineering blog: “We already have a strong set of explicit and implicit signals that provide context on what content a member may find interesting based on their social connections and the Knowledge Graph (e.g., a company that they follow, or news widely shared within their company).”

LinkedIn also uses what they call an “interest graph” that represents the relationships between users and a variety of topics. This lets the LinkedIn algorithm measure the following:
 

  • How interested users are in certain topics
  • How related are different topics to one another
  • Which connections share a user’s interests

 
The algorithm also considers the companies, people, hashtags, and topics mentioned in a post to predict interest. To maximize the interest relevance ranking, you have to understand your target audience and craft content that they’ll find relevant.
 

Engagement Probability

 
Interaction plays a significant role in a post’s ranking on LinkedIn. The platform uses machine learning to rank interaction in two ways:
 

  1. How likely a user is to comment on, share, or react to a post based on the content and people they have interacted with
  2. How quickly a post starts receiving engagement after it’s published. The faster users interact with a post, the more likely it will appear at the top of others’ feeds

 
Users who regularly interact with others’ posts in their LinkedIn feed are more likely to see interactions on their content, which in turn means that they’ll be more likely to show up on other people’s feeds.
 

Elevate Your Brand’s LinkedIn Presence

 
The LinkedIn algorithm can seem intimidating, but it really isn’t. It relies on a series of rules and ranking measures that can be understood and mastered to present users with content they find helpful in their professional lives.

Knowing that the algorithm prioritizes engagement, relevance and connection will help get your posts in front of more LinkedIn users and improve your overall performance on the platform. And by following the eight best practices outlined in this article, you’ll be able to keep your audience’s interest and create plenty of opportunities for them to engage with your content. 

Tinuiti helps brands strengthen relationships with new and current customers through expert social media strategy and brilliant creative. Reach out to our Paid Social services team to learn how to start advancing your LinkedIn strategy today.

Editor’s Note: This post was originally published in September 2021 and has been regularly updated for freshness, accuracy, and comprehensiveness.

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address

MARKETING

Salesforce, Google partner on local commerce

Published

on

Salesforce, Google partner on local commerce

Salesforce has announced an integration between Salesforce Commerce Cloud and Google Merchant Center to help merchants highlight the availability of products in stores. The move builds on Salesforce data that suggests both the widespread use of online search in advance of brick and mortar store visits, and an increased likelihood of shopping trips when consumers can see that a store has an item in stock.

Using this new integration, merchants using Commerce Cloud will be able to turn local inventory data into local product listings on Google Search and Google Maps and in the Shopping tab.

Why we care. The distinction between digital and real-world commerce continues to collapse. Those online shopping behaviors that exploded during the pandemic will be with us for the foreseeable future, but it doesn’t mean store visits are a thing of the past.

Rather, consumers are looking for seamless connections between an online product discovery experience and in-person purchases. This integration seeks to support that aim at a granular local level.

The Salesforce data that supports the move can be found here.

Embedding commerce in discovery. The integration also braids together online discovery and the commerce experience. Just as many merchants now seek to provide a frictionless transition from finding a product online to making a digital purchase, this sees the opportunity to link discovery with in-person shopping.

This move pairs with the recent announcement of Salesforce’s Einstein GPT for Commerce that combines proprietary and generative AI models with real-time data such as customer demographic data and shopping history, to automate and tailor shopper recommendations in Commerce Cloud.

Dig deeper: A roundup of the latest AI-powered marketing technology releases


Get MarTech! Daily. Free. In your inbox.



About the author

Kim Davis

Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space.

He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020.

Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

What Is AIO? The New Model Revolutionizing Content & Predictions About AI

Published

on

What Is AIO? The New Model Revolutionizing Content & Predictions About AI

In 1936, the creator of Turing Machines predicted that a machine would one day be able to think like a human, if not even outperform the human. 

It’s 2023, and we’re officially here.

82% of marketers believe that AI will be the future of marketing—in fact, many of them already believe AI writes better than a human (Capterra study).

Well, with ChatGPT flying past 100 million users in just two months…we’re living in the future.

AI is revolutionizing the way we work, think, and create. 

I joined Content at Scale as the VP of Marketing this January in a bold move of ‘adapting or die’ for my career in content—one month in, what I’m seeing, learning, and facilitating for marketers and teams is blowing my mind. Let’s talk about it.

Reduce Content Overhead Costs and Frustrations by 5x-25x With the AIO Model

It’s now the Stone Age to sit at your computer and drum up 2,500 words for an SEO post from a blank slate.

Seriously.

1679645854 863 What Is AIO The New Model Revolutionizing Content Predictions

When you can generate long-form SEO content (2,500 words or more) that’s fully original and well-written inside of five minutes or less, you’ll never want to go back. 

On average, I’m seeing a 5-25x reduction in associated content creation costs (which is mind-boggling!), and a time savings of 5-10x. (My full-time writer at Content Hacker went from 7 hours per post to one hour per post after we adapted this model.)

Here’s the AIO model I’ve built out reflecting the difference of what you can do in your business and marketing by replacing the human blank-slate writing with AI blank-slate writing, based on hundreds upon hundreds of use cases from Content at Scale clients:

1679645854 917 What Is AIO The New Model Revolutionizing Content Predictions

“AIO”, Artificial Intelligence Optimization, is the term I’ve created to properly define the new way we’re seeing hundreds of marketers and teams create content:

  • Artificial Intelligence as the baseline writer (replacing the human writer and blank slate)
  • The human writer as an optimizer of the AI baseline content

And—it’s working.

With the time and money savings, it’s an absolute no-brainer to switch to AI as the baseline.

The Human Process Involved In AIO

While we see AI perfectly capable of writing an entire 2,500 word blog from scratch, with a single keyword and one-sentence prompt:

What Is AIO The New Model Revolutionizing Content Predictions

We also see the need for the human optimization process pre-publish more necessary than ever.

Without your unique story (or client case studies/testimonials) woven in, the human touch of adding statistics, double-checking facts and cutting the fluff; AI-written content simply won’t stand out. It won’t set you apart in the content sea; it won’t drive customers and loyal fans in droves to your email list. So, the human touch is necessary.

My C.R.A.F.T. framework within AIO defines the steps writers should take to make the AI content more human and personalized once you take it from AI and get it ready to publish (from AI to O):

1.     Cut the fluff

2.     Review, edit, optimize

3.     Add images, visuals, media

4.     Fact-check

5.     Trust-build with personal story, tone, links

Content Marketing Certification

Want to get certified in Content Marketing?

Leverage the tools and channels to predictably and profitably drive awareness, leads, sales, and referrals—EVERYTHING you need to know to become a true master of digital marketing.​ Click Here

Humans are needed for the optimization side, and for that human touch that must be applied to the content AI generates. Content itself will never be a fully automated, 100% AI process; but AI can remove hours and hours of painstaking work from the content creation pipeline, which will save countless amounts of energy and dollars in the coming months and years when marketers adapt in full force.

 Predictions About the Future of Content & AI

This year, Capterra surveyed almost 200 marketers using AI in their marketing. 82% of them said that the content written by AI was just as good if not better than human-generated content.

One of the first Generative AI experts in the world, Nina Schick (founder of Tamang Ventures, and creator of Substack project ‘The Era of Generative AI’), has told Yahoo Finance Live that she believes ChatGPT will completely revamp how digital content is created, and by 2025, software built with ChatGPT will enable us to reach 90% of all online content now being generated by AI. She said: “ChatGPT has really captured the public imagination in an extremely compelling way, but I think in a few months’ time, ChatGPT is just going to be seen as another tool powered by this new form of AI, known as generative AI,” she said.

Google Trends shows a HUGE jump in interest and traffic around the term “ChatGPT:”

What Is AIO The New Model Revolutionizing Content Predictions.webp

Search traffic shows that the interest in AI is the highest it has ever been. The previous peak was in January 2012:

1679645855 976 What Is AIO The New Model Revolutionizing Content Predictions.webp

375 million jobs obsolete in the next ten years. In the next three years, it’s predicted that 120 million workers around the globe will need to be retrained and re-skilled for this new world.

Newer and better-paying jobs in AI will come on the scene, but they won’t replace the amount of jobs lost; so without retraining and reskilling, and learning how to adapt, average people will have difficulty finding new work.  

Are You Ready to Join the Future? 

I’m excited to see just how much AI will revolutionize human efficiency and optimization. 

We’re in new times.

Are you ready to join the future of marketing and learn about all things AI?

I know I am. 

See you on the other side!


1675814445 466 The Rise of Web3 in Web Design 8 Ways Website

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

The New Digital World: Top 3 Key Takeaways from Opticon

Published

on

The New Digital World: Top 3 Key Takeaways from Opticon



Each year, I look forward to Opticon, where our global community of customers, partners, industry experts, academia, media, and digital leaders come together to explore the latest in digital.

 

This year, we brought everyone together in San Diego, in person for the first time since 2019. Over  three dynamic days, we enjoyed countless conversations envisioning a future of digital where experiences are created and optimized at the same time. 

 

Plenty of valuable learnings were shared, but I’ve highlighted my top three takeaways below.

 

  1. Change has become uncertain; we must be adaptive.

The world is moving faster than ever, and change is constant and chaotic. Today’s digital leaders must navigate uncertainty on nearly every level: economic upheaval, rapid cultural change, ever-escalating customer expectations, and a tight talent market. Digital leaders face challenges that make it difficult for consumers and brands to react and connect. 

 

But another element of change has profoundly changed over the past three years: change has become unpredictable, dramatically increasing the difficulty of creating the end-user experience. To not only stay the course but to grow in this unpredictable environment, you must put your organization on “adaptive footing” to account for quick changes. 

 

That’s why Optimizely is increasing digital team agility through automation and AI and building simpler, reliable systems of records. Think customizable AI workflow for content creation and approval processes, automation to sync updates across all destinations, and approved templates that can be integrated seamlessly for marketers to speed up production while maintaining governance. 

 

Keeping pace with the digital elite requires frictionless collaboration across teams, and there is no time to waste on clunky, inefficient workflows.

 

  1. A great customer experience requires a great practitioner experience. ​

Simplifying “work about work” helps teams not only ride the wave of change but prioritize their well-being. 

 

So many marketers feel overwhelmed by complexity, which is a real problem for creativity. You wouldn’t want your sports team playing exhausted or demoralized before the big game; the same goes for your team at work. 

 

When we surveyed global marketers, the top creative roadblocks included employee burnout and high turnover. Our research also revealed that 92% of global marketers believe dispersed teams caused by remote or hybrid work impacted their ability to develop ideas and execute campaigns, and 93% say their creative ideas were better before the pandemic. 

 

If the practitioner experience is suffering, your can bet that the customer experience is also suffering. We must ensure our teams are up for the challenge of keeping pace. 

 

Teams need a platform where they can effectively collaborate and communicate across internal silos inclusively, and where workflows are purpose-built to the needs across the content lifecycle. With this reality in mind, we built Optimizely’s Ddigital Eexperience Pplatform (DXP) — because inclusive, well-orchestrated collaboration leads to better outcomes for all.

 

  1. Marketers, developers, and product leaders have become part of the same digital team. 

Today’s customers are digitally adept and confident, and their brand expectations — and the stakes of meeting those expectations — are rising faster than ever before. 

 

According to recent research on customer expectations, 80% of customers now consider the experience a company provides to be as important as its products and services, and 71% say they’ve made a purchase decision based on experience quality.

 

Being customer-centric is at the heart of any great digital experience. That’s why the digital team — comprised of marketers, developers, and product teams in our modern digital landscape — must work together to meet customer expectations and deliver optimized experiences. 

 

Consider marketers. With access to a slew of customer touchpoints and experimentation data, the marketing team is a critical resource for understanding customers’ wants and needs. Developers, product teams, and beyond should absolutely utilize this data to remove the guesswork and inform strategies, priorities, roadmaps, and decisions. 

 

By working together to inject data across silos, teams can have the insight needed to make the right decisions and create with confidence. 

 

Thank you to all who kindly shared their wisdom during this year’s Opticon. Stay tuned for information about next’s year Opticon, taking place October 10-12, 2023 back in San Diego!


Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

Trending

en_USEnglish