LinkedIn Shares 7 Insights For Powerful Online Engagement via @sejournal, @martinibuster

LinkedIn shared insights with Search Engine Journal about how to effectively plan and roll out new features based on their experience planning and rolling out new AI features. The insights are useful whether you’re planning a content strategy or adding new features to your business.

I spoke with Prashanthi Padmanabhan, Head of Engineering for LinkedIn Premium. LinkedIn recently rolled out a massive change for their premium subscribers that analyzes comments, articles, videos, and posts and suggest how the information is useful for the member, as well as a new job seeker experience.

What happened behind the scenes and the takeaways from it offer useful insights that are useful to anyone who publishes or sells online.

Prashanthi Padmanabhan, Head of Engineering for LinkedIn Premium

Image/LinkedIn

Creating A Foundation For Success

I asked Prashanthi about her takeaways on planning and creating these features and her answer consisted of three points

  1. Anchor your strategy to your mission
  2. Think through how your plans add value to your audience or customers
  3. Get member feedback from day one

Here is what she shared:

“There are three main takeaways for me from this experience so far. The first is to anchor your strategy to your mission. A robust product strategy and roadmap should always be anchored in the company’s overarching mission. By aligning every decision on our roadmap with this purpose, we ensure our efforts directly contribute to member success.

The next is about thinking through how to leverage technical innovations. As part of the engineering team, we embrace cutting-edge technologies like Generative AI. These innovations allow us to craft elegant and practical solutions that cater to our members’ needs. Our commitment lies in delivering features that truly add value to our members’ experiences.

Last, but not least, is to incorporate member feedback early and often. We strongly believe that our members’ feedback and sentiments are invaluable. From the moment our product faces our customers, it’s Day 1. We build and roll out features through iterative development, relying on a blend of internal reviews and in-product feedback to gauge quality.

For instance, our initial foray into AI-powered writing suggestions for LinkedIn profiles and messages provided valuable insights from our members’ point of view. By listening to our members and adapting based on their actions, we will continue to refine features to meet—and ideally exceed—their expectations.”

Map Your Plans To User’s Needs, Not Trends

There are always many ideas of things that a business can do for their users. But what’s the right way to assess if something is worth doing?

Prashanthi answered that she and team started with understanding member’s needs as an ongoing iterative process. This is a great insight for anyone who works online and wants to go beyond what competitors are doing.

Another insight that everyone should pay attention to is that LinkedIn didn’t look at what others are doing, they focused on what their users might find useful. A lot of SEO and online content projects begin with competitor research and that’s something that in my opinion leads to unoriginal content that is the opposite of the unique experiences that Google wants to show in the search engine results pages (SERPs).

She answered:

“The process of identifying the right features to add begins with a deep understanding of our members’ and customers’ needs. We do this by validating our hypotheses through research and feedback. However, it’s not a one-time task; it’s an ongoing, iterative process. At LinkedIn, we rely on a combination of data, success metrics, and member feedback to gauge how well we’re meeting those needs. As we evolve our products, alignment to our mission, data insights, and feedback help guide our overall development journey.

For example, when we recognized that Generative AI could revolutionize technology, we didn’t simply follow trends. Instead, we asked ourselves: Could this technology truly benefit our members? If so, how could we integrate it into our Premium platform? For instance, we explored using it to simplify tasks like helping to write when starting a blank page or extracting key insights from LinkedIn feed posts.

It’s important to note that LinkedIn Premium is intentionally designed to enhance member productivity and experience based on their individual goals. So the features we add to Premium should map to their specific needs – for job seekers that could be helping them stand out to find the right job, getting the right insights for creators to help them build their audiences, and giving businesses a platform to build and grow their brand.”

The Importance Of The Why, What, & When

Every business faces the question, what do we do next and how do we do it? Prashanthi offered her insights on what to focus on in order to maximize for a successful outcome.

Prashanthi shared:

“Our product engineering principles at LinkedIn are rooted in three fundamental elements: starting with the “why,” aligning on the “what,” and optimizing for the “when.” We found these principles are a solid guide for navigating through the complex process of creating impactful products that resonate with our members.

The why is determined by delving into the site’s purpose and identifying the target audience—those who will benefit most from the site’s offerings. This clarity on the “why” sets the foundation for subsequent decisions.

With the “why” firmly in mind, now align on the “what.” This step involves defining the set of features and capabilities the site needs. We ask ourselves, what functionalities are essential to address the identified needs and then go from there. Carefully curating this feature set can help get a better feel for how they align with members’ requirements.

The final step is optimizing for the “when.” Engineering teams often grapple with the delicate balance between craftsmanship and time-to-market. Rather than waiting indefinitely for perfection, embrace early testing, such as releasing a minimum viable product (MVP) to gather feedback promptly. Metrics such as site visitor volume, engagement duration, and return frequency guide the assessment of the site’s value. It’s a dynamic dance between precision and speed, all aimed at delivering an exceptional experience.”

What Is A Good User Experience?

The concept of user experience can be subjective, we all have an idea of what it might be. I wanted to find out from Prashanthi, as head of engineering, how does one even translate the concept of a good user experience to an actual user experience online?

Her answer emphasized the importance of keeping things as simple and intuitive as possible, plus consistency.

She shared:

“For me, a good user experience means a product is simple, intuitive, and trustworthy. As an engineering team, translating the concept of a good user experience into reality requires meticulous attention to detail throughout the process. At LinkedIn this starts at the very beginning when we are transforming product and design specifications into a technical design. It’s essential to focus on simplicity and the consistency of the user experience across the entire product, so it’s intuitive to use with less cognitive load.

I’m also a big fan of clear and concise messaging (copy) for our customers as they help to build trust; in fact, when users run into issues, the clarity and usefulness of error messages and support resources make a huge difference.

I’ve found that customers are forgiving when your product works well and fast most of the time, and during times when there are issues, clear guidance on how they can best navigate that situation is critical. When it comes to reliability and performance, it’s simple – the product should work reliably every single time. A high-performance product gives users instant gratification as people care a lot about productivity and saving time, so they should be able to trust that the product will always work, and work fast.”

Importance Of Commitment To Improvement

A majority of LinkedIn’s users indicated that the new features are useful. I asked Prashanthi is the takeaway for online businesses that would in their own way increase the helpfulness of their business, whether that’s an ecommerce site, recipe blog, product review or comparison site?

Her answer suggests that creating content or features that resonate with users is a key to increasing the helpfulness of a website, something that’s super important for any online business today.

She offered the following insights:

“We’re extremely excited that early tests show that 90% of subscribers with access to our popular AI-powered job experience find it useful! This positive feedback underscores our commitment to creating features that genuinely resonate with our members. Rather than focusing on technology for technology’s sake, prioritizing how this tech can genuinely benefit our members seems to be resonating.

As professionals we know that job hunting can be an isolating and overwhelming experience, so we’ve introduced AI-assistant features designed to support and guide members throughout their job search journey, leveraging the knowledge from our Economic Graph. Our goal is to provide a virtual handhold, enabling job seekers to efficiently and confidently identify roles that align with their skills and aspirations. The overwhelmingly positive response reinforces that we’re moving in the right direction.

Our product development journey is guided by a combination of essential factors:

  • Product intuition
  • Technical innovation
  • Data insights
  • Customer feedback.

These elements apply universally to any product we create. It’s essential to recognize that achieving success doesn’t happen overnight. Instead, it requires a culture of rapid experimentation and continuous learning. We understand that perfection isn’t attainable on the first try, but our commitment to improvement drives us forward.”

How To Decide What’s Helpful For Users?

Being unique and helpful is important for ranking in today’s search engine. But how does one go about reimagining the user’s experience? It can be difficult to someone inside the business to understand what users may need.

I asked, what advice would you give an online business, whether that’s an ecommerce or a product review site that is contemplating what they can do better to serve their users?

She suggested the following steps:

“When we create new products, it’s essential to consider what other people need. So, right at the start, finding ways to bring more of the outside into development is critical. In the initial phases of developing our product strategy and roadmap for Premium, our user experience research and marketing teams conducted a combination of qualitative (numbers) and quantitative (stories) research to develop a deeper understanding of specific needs and related sentiments. This kind of research helps refine the personas we are building products for and clearly articulates the specific jobs and goals people are trying to accomplish with our products. For any business, this process can really humanize the product development process by helping to build a clear picture of the people that the product is designed for. It’s like getting to know them as real individuals.

But don’t just stop there. Once a basic version of the product (MVP) is ready, test it with a small group and pay attention to how well it works and what is said by the users. At LinkedIn, we involve our engineers in this process so they can learn about member’s needs and hear feedback first hand. As an engineering leader, I really enjoy sitting in these research sessions!—it makes the problems the team and I are solving feel more real. It’s better than just reading a list of product requirements.”

Cultivate Empathy For Online Success

A lot of times I read posts on social media where someone describes how they did their keyword research, hired experts for content and did many things to demonstrate expertise, experience, authoritativeness, and trustworthiness but nothing about empathizing with the site visitors, something that Prashanthi suggested was key to creating quality user experiences.

Reading some of LinkedIn’s descriptions of what they do, I saw a reference to a “user-focused lens” and I was curious about what that means to LinkedIn and what the end goal of that is.

She answered:

“Looking through a user-focused lens is about really connecting with our members and understanding their needs and experiences, with the goal being that what we create is functional as well as a joy to use.

As product builders, our most important job is to build ones that solve our member’s needs and create value for them at every touch point. For me, the only way to internalize what this means is to put ourselves in our members’ shoes and empathize with their needs. And this is where all product development functions, especially engineering, staying close to the member experience, sentiments, feedback, etc. will go a long way in developing a member-centric product development culture.

For example, when discussing features like AI-powered writing assistants, some members have reflected on how they consider themselves novice writers and how useful they find our thought-starters and suggested message drafts. When I hear these sentiments, it gives me confidence that the products we are building are helping make their lives easier, taking them a step closer to their goals and, in turn, making our jobs and purpose more meaningful.”

User Focused Online Experiences

Prashanthi’s answers show the value of a user-centric approach to everything we do online. Anchoring your content strategy to your mission, cultivating the quality of empathy, and listening to your site visitors is important.

The information she shared is adaptable to any scenario in online marketing whether that business is sales, content, recipes or reviews.

LinkedIn’s Most In-Demand Skills: Why You Need Them Your Profile via @sejournal, @MattGSouthern

A new report from LinkedIn identifies the critical skills professionals must develop to remain competitive in today’s workforce.

Communication, customer service, leadership, and adaptability top the list, reflecting a growing emphasis on uniquely human capabilities that AI can’t replicate.

“People skills are going to come more to the center of individual career growth,” predicts LinkedIn VP Aneesh Raman. “And people-to-people collaboration is going to come into the center more for company growth.”

The annual ranking is based on data from LinkedIn’s 1 billion users across 200 countries and regions.

The Top 10 Most In-Demand Skills For 2024

A graphic showcasing the Screenshot from: LinkedIn, April 2024.
  1. Communication
  2. Customer Service
  3. Leadership
  4. Project Management
  5. Management
  6. Analytics
  7. Teamwork
  8. Sales
  9. Problem-Solving
  10. Research

In addition to the top 10 list, LinkedIn identified adaptability as the “skill of the moment” due to its remarkable year-over-year growth in demand.

“Since AI has changed work so profoundly over the last year, we’re highlighting adaptability as the top ‘skill of the moment’ with the biggest surge in demand,” said LinkedIn Global Head of Content Strategy Dan Brodnitz. “It’s indispensable for teams to keep steady and drive impact as the pace of change accelerates.”

By 2030, an estimated 65% of job skills are expected to change, up from just 25% in 2015. Currently, over half of LinkedIn users have roles at risk of disruption by AI.

To help people build critical soft skills, LinkedIn is offering free access to relevant learning courses until May 31st, 2024. Find links to each course in LinkedIn’s report.

The Importance Of Showcasing Skills On LinkedIn

According to a new LinkedIn blog post, as skills-based hiring becomes the norm, clearly listing your capabilities on your LinkedIn profile has never been more important.

“Increasingly, skills — as much as schooling, previous companies, job titles, and work experience — are what get you a new job,” writes LinkedIn’s Bruce M. Anderson.

Nearly half of hirers explicitly use members’ listed skills to fill open roles.

LinkedIn data shows that people with at least one listed skill receive up to double the number of profile views, connection requests, and messages compared to those without skills listed.

LinkedIn recommends listing up to 50 skills spanning hard technical and soft human skills.

Job seekers are advised to focus on skills frequently mentioned in job postings for their desired roles and sectors.

“God is in the details,” advises Anderson. “Where appropriate, list specific skills rather than generic skills or umbrella terms.”

For instance, instead of just “communication,” list public speaking, executive communications, copywriting, and other specialized communication skills.

However, more than simply listing skills is needed. LinkedIn recommends asking colleagues and managers for endorsements of listed skills.

Additionally, users can create a “Projects” section detailing how they applied particular skills and supporting claims with media like case studies, blog posts, and presentations.

“Regularly adding new skills is also advisable,” says Anderson, pointing to data showing members updated their skills 11% more frequently when hired or promoted.

In Summary

As AI automates more technical roles, clearly articulating one’s complete skills portfolio on LinkedIn has become a vital career currency. Those most adept at constantly updating their skills – and skillfully marketing them – will remain most employable in 2024 and beyond.


FAQ

How can adaptability enhance an SEO expert’s value in the face of AI advancements?

LinkedIn considers adaptability to be the most essential skill because the workplace is changing quickly due to advances in artificial intelligence (AI). For SEO professionals, adaptability means smoothly transitioning to using new technologies and dealing with search engine algorithm updates.

It involves flexibly shifting strategies when needed and staying competitive in the SEO industry.

As AI continues to transform job roles, SEO specialists who can rapidly learn and implement new techniques will continue to provide value to their clients and remain prominent and successful in the market.

In the context of SEO, what is the significance of continuously updating one’s skill set on professional platforms like LinkedIn?

Showing a broad and expanding set of abilities helps SEO experts better appeal to potential clients or employers, putting more emphasis on hiring people based on their specific skills.

Highlighting specialized SEO skills like technical website optimization and building high-quality backlinks, along with endorsements and examples of past projects, builds credibility. It proves you are dedicated to keeping up with the latest best practices in the ever-evolving SEO field.

Why should SEO experts focus on soft skills like leadership and teamwork, as LinkedIn indicates?

LinkedIn’s report shows a growing emphasis on soft skills, such as leadership and teamwork, which are difficult for AI to replicate.

For SEO experts, honing these skills is vital to successful project management, cross-functional collaborations, and leading SEO teams or initiatives.

Soft skills complement technical abilities, enabling SEO professionals to navigate client relationships and foster an environment of continuous improvement.

How LinkedIn Unlocked A Genius SEO Strategy With AI via @sejournal, @martinibuster

LinkedIn’s Collaborative Articles features reached the milestone of 10 million pages of expert content in one year. The Collaborative Articles project has experienced a significant rise in weekly readership, rising by over 270% since September 2023.  How they reached these milestones and are planning to achieve even more results offer valuable lessons for creating an SEO strategy that uses AI together with human expertise.

Why Collaborative Articles Works

The intuition underlying the Collaborative Articles project is that people turn to the Internet to understand subject matter topics but what’s on the Internet is not always the best information from actual subject matter experts.

A person typically searches on Google and maybe lands on a site like Reddit and reads what’s posted but there’s no assurance that the information is by a subject matter expert or just the person with the biggest social media mouth. How does someone who is not a subject matter expert know that a post by a stranger is trustworthy and expert?

The solution to the problem was to leverage LinkedIn’s experts to create articles on topics they are expert in. The pages rank in Google and this turns into a benefit for the subject matter expert, which in turn motivates the subject matter expert to write more content.

How LinkedIn Engineered 10 Million Pages Of Expert Content

LinkedIn identifies subject matter experts and contacts them to write an essay on the topic. The essay topics are generated by an AI “conversation starter” tool developed by a LinkedIn editorial team. Those conversation topics are then matched to subject matter experts identified by LinkedIn’s Skills Graph.

The LinkedIn Skills Graph maps LinkedIn members to subject matter expertise through a framework called Structured Skills which uses machine learning models and natural language processing to identify related skills beyond what the members themselves identify.

The mapping uses skills found in members’ profiles, job descriptions, and other text data on the platform as a starting point from which they use AI, machine learning and natural language processing to expand on additional subject matter expertise the members may have.

The Skills Graph documentation explains:

“If a member knows about Artificial Neural Networks, the member knows something about Deep Learning, which means the member knows something about Machine Learning.

…our machine learning and artificial intelligence combs through massive amounts of data and suggests new skills and relations between them.

…Combined with natural language processing, we extract skills from many different types of text – with a high degree of confidence – to make sure we have high coverage and high precision when we map skills to our members…”

Experience, Expertise, Authoritativeness and Trustworthiness

The underlying strategy of LinkedIn’s Collaborative Articles project is genius because it results in millions of pages of high quality content by subject matter experts on millions of topics. That may be why LinkedIn’s pages have become more and more visible in Google search.

LinkedIn is now improving their Collaborative Articles project with features that are meant to improve the quality of the pages even more.

  • Evolved how questions are asked:
    LinkedIn is now presenting scenarios to subject matter experts that they can respond to with essays that address real-world topics and questions.
  • New unhelpful button:
    There is now a button that readers can use to offer feedback to LinkedIn that a particular essay is not helpful. It’s super interesting from an SEO viewpoint that LinkedIn is framing the thumbs down button through the paradigm of helpfulness.
  • Improved Topic Matching Algorithms
    LinkedIn has improved how they match users to topics with what they refer to as “Embedding Based Retrieval For Improved Matching” which was created to address feedback from members about the quality of the topic to member matching.

LinkedIn explains:

“Based on feedback from our members through our evaluation mechanisms, we focused our efforts on our matching capabilities between articles and member experts. One of the new methods we use is embedding-based retrieval (EBR). This method generates embeddings for both members and articles in the same semantic space and uses an approximate nearest neighbor search in that space to generate the best article matches for contributors.”

Top Takeaways For SEO

LinkedIn’s Collaborative Articles project is one of the best strategized content creation projects to come along in a long while. What makes it not just genius but revolutionary is that it uses AI and machine learning technology together with human expertise to create expert and helpful content that readers enjoy and can trust.

LinkedIn is now using user interaction signals to improve the quality of the subject matter experts that are invited to create articles as well as to identify articles that do not meet the needs of users.

The benefits of creating articles is that the high quality subject matter experts are promoted every time their article ranks in Google, which offers anyone who is promoting a service, a product or looking for clients or the next job an opportunity to demonstrate their skills, expertise and authoritativeness.

Read LinkedIn’s announcement of the one-year anniversary of the project:

Unlocking nearly 10 billion years worth of knowledge to help you tackle everyday work problems

Featured Image by Shutterstock/I AM NIKOM

LinkedIn Reports Most In-Demand Jobs Across All Industries via @sejournal, @MattGSouthern

LinkedIn’s analysis of global talent trends shows healthcare roles dominating the list of fastest-growing jobs while customer-facing and in-person positions remain highly in demand.

According to LinkedIn’s data, healthcare jobs represent 6 out of the top 10 roles, with the most significant increase in paid job posts on the platform.

Outside of healthcare, customer-facing and in-person jobs dominate the top most in-demand roles by the total volume of job posts.

Here are the highlights from LinkedIn’s report.

Healthcare Industry Seeing Highest Growth

“The global staffing shortage in healthcare is a chronic issue that’s grown into a full-blown crisis,” states LinkedIn in its latest in-demand jobs report.

Demand is being driven higher for healthcare roles globally due to an aging population.

Health worker shortages are especially dire in poorer countries, where qualified professionals often migrate abroad for better opportunities.

Jobs With The Fastest-Growing Demand

LinkedIn’s report shows the greatest increase in hiring for the following roles:

  1. Care Specialist.
  2. Surgical Technician.
  3. Tax Preparer.
  4. Medical Surgical Nurse.
  5. Secretary.
  6. Sonographer.
  7. Progressive Care Nurse.
  8. Home Health Licensed Practical Nurse.
  9. Customer Associate.
  10. Business Administrator.

The demand for specific healthcare jobs reflects their continued importance despite predictions that AI could make the roles unnecessary.

Administrative positions also continue to play a vital role, even with advances in AI. Rather than becoming obsolete, many of these jobs are as essential as ever.

Most In-Demand Jobs Overall

Despite the focus on healthcare, customer-facing roles remain highly sought after, with positions like retail salesperson, store manager, and cashier seeing significant demand.

Additionally, after a dip, tech roles such as software and full-stack engineers are again rising, indicating a swing in demand for these remote-capable positions.

These are the roles with the most significant number of paid LinkedIn job posts in Q4 2023, along with their change in ranking compared to the previous quarter:

  1. Salesperson (no change in rank vs. previous quarter).
  2. Retail Salesperson (+1).
  3. Registered Nurse (+1).
  4. Software Engineer (+1).
  5. Project Manager (+1).
  6. Customer Service Representative (-4).
  7. Store Manager (+3).
  8. Full Stack Engineer (+6).
  9. Cashier (+6).
  10. Driver (-2).

Key Takeaways For Businesses & Employers

The growth in healthcare roles presents an opportunity for employers in other industries to attract healthcare talent by highlighting transferable skills. With so much demand in healthcare, casting a wider talent net could help fill open roles.

The return of demand for tech roles like software engineers shows employers need to ensure their tech staffing budgets reflect the current competitive market. With tech talent in high demand, compensation and retention efforts may need revisiting.

Administrative and operations roles remain essential for business operations despite predictions. Employers should ensure these roles are valued for their ongoing contributions, even as AI automates specific tasks.

Methodology

The findings are based on global LinkedIn data from premium job posts between July and December 2023.

The analysis excludes roles with fewer than 1,000 posts or dominated by single-company listings.

FAQ

What are the most in-demand jobs according to LinkedIn’s recent report?

  • The report from LinkedIn shows significant demand for healthcare roles.
  • Administrative positions also remain vital.
  • Customer-facing roles like retail salesperson, store manager, and cashier are highly sought after.

According to LinkedIn’s data, how has the demand for tech roles such as software and full-stack engineers changed?

  • LinkedIn’s recent data indicates a resurgence in demand for tech roles such as software and full-stack engineers after a previous dip in demand.
  • These positions, which are often remote-capable, have seen a rise in their rank concerning the number of paid job posts on LinkedIn for Q4 2023.
  • Full stack engineer roles jumped by six positions in the ranking compared to the previous quarter.

More resources:


Featured Image: Irina Strelnikova/Shutterstock

LinkedIn Algorithm Change Could Promote Your Best Posts For Months via @sejournal, @MattGSouthern

LinkedIn is readying new features and algorithm changes to help users connect with more targeted audiences months or even years after posting their best content, according to a recent interview with company leaders.

This information is revealed in a recent talk published on Entrepreneur.com; LinkedIn executives Tim Jurka and Dan Roth addressed topics relevant to boosting engagement on the platform.

Here are the highlights from the discussion.

Suggested Posts – A Major Algorithm Shift

LinkedIn is developing a new “suggested post” feature to promote relevant content to specific audiences long after it was initially shared.

“Right now, content lives and dies on the newsfeed very quickly,” said Jurka. “We’re trying to collect the sum total of professional knowledge on our platform and make sure it surfaces whenever you need it.”

The suggested posts feature marks one of LinkedIn’s biggest algorithm changes in years. It represents a shift in how social platforms distribute content by keeping old posts alive if they remain relevant.

LinkedIn confirmed the feature is currently being tested on a small percentage of users. However, the executives didn’t specify when it may roll out more widely.

How LinkedIn Will Choose Posts To Suggest

Here’s how suggested posts will work:

  • LinkedIn’s algorithm may identify content as uniquely valuable if you share an insightful post on a niche topic.
  • Then, for months or years after you posted it, your content could appear in the feeds of users who show interest in that subject – even if they don’t already follow you.

The goal is to actively match users with relevant content based on their needs at the moment rather than simply displaying the most recent posts.

Addressing Claims Of Declining Organic Reach

Some content creators say it has become harder to gain reach on LinkedIn since algorithm changes began last year.

LinkedIn says the company’s priority is targeted value over mass reach.

The executives explained that organic reach has always fluctuated on the platform. They maintain that meaningful connections are more important than vanity metrics like views or followers.

Cautions Against Algorithm “Hacks”

LinkedIn cautions users not to trust reports claiming to crack LinkedIn’s algorithm, arguing the signals change constantly.

Instead, Roth says sharing genuinely helpful knowledge is the best strategy.

Takeaways For Marketers

Here are some ways digital marketers can adapt their LinkedIn strategy based on these algorithm changes.

Focus On Quality Over Quantity

With LinkedIn prioritizing “knowledge and advice” content that remains useful over time, marketers should shift focus away from producing a high volume of posts. Instead, concentrate on publishing genuinely unique, high-quality insights that provide value.

Prioritize Niche Communities

Mass reach is less important on today’s LinkedIn. Marketers should engage with niche professional groups and build strong connections with key subsets rather than spraying content across the platform.

Embrace Long-Form Content

Lengthy, in-depth posts are prime targets for LinkedIn’s suggested post and newsletter features. Marketers should experiment with long-form content and series.

Monitor Analytics Closely

Keep a close eye on audience analytics to see what content resonates. Let data guide your strategy rather than following hypothetical “hacks” or best practices.

Test a Mix of Content Formats

LinkedIn now offers more options like newsletters, audio, and live video. Marketers should test and analyze results across multiple formats to see what best engages their audience.

The key is providing genuine value and insight to niche professional communities versus broad, spammy posts. Quality over quantity is now more critical than ever.

Additional Features and Offerings

In addition to the features mentioned, LinkedIn is exploring more ways to integrate newsletters and audio features as they build their content offerings.

The changes illustrate how LinkedIn aims to transition from a social network into a knowledge-sharing platform for professionals. The long-term viability of old content through suggested posts is a big part of that strategy.


FAQ

How will LinkedIn’s suggested post feature enhance content visibility?

The upcoming suggested post feature on LinkedIn is designed to significantly extend the life and reach of valuable content on the platform. By promoting posts based on relevancy rather than recency, useful insights, and knowledge can remain in circulation for extended periods, potentially allowing them to reach interested users months or even years after they were initially shared. Key advantages include:

  • Better content longevity, as impactful posts may appear in user feeds long after publication.
  • Increased visibility for content creators focusing on niche topics by matching their posts with users demonstrating interest in those areas.
  • A shift from ephemeral content to a repository of enduring professional knowledge, as LinkedIn aims to facilitate lasting connections between content and users’ needs.

What content formats should marketers experiment with on LinkedIn to maximize audience engagement?

As LinkedIn enhances its platform capabilities, marketers have various content formats to explore to maximize audience engagement. These formats include:

  • Long-form, insightful articles and posts that cater to niche professional groups and can take advantage of the suggested post feature.
  • Newsletters that can help maintain ongoing communication with interested followers.
  • Audio and video content, including live broadcasts, to capture the attention of users who prefer more interactive or personal formats.

An experimental approach with these formats and close monitoring of engagement analytics can help marketers find the optimal mix that resonates with their communities.


Featured Image: tovovan/Shutterstock

LinkedIn Rolls Out New AI Features To Make Networking Easier via @sejournal, @MattGSouthern

LinkedIn has introduced new AI-powered features to improve the networking experience on its platform.

These updates come at a time when many professionals are re-evaluating their careers and looking to expand their networks.

The new features use AI to streamline processes like making connections, searching for jobs, and sharing content.

A Competitive Edge in the Job Market

LinkedIn cites a recent survey that found 85% of professionals are considering changing jobs in 2024.

LinkedIn acknowledges that building and maintaining a professional network requires a substantial time commitment, with nearly a quarter of people surveyed reporting they spend 6-10 hours per week on networking activities.

AI to the Rescue

LinkedIn’s latest features use AI to make networking more efficient.

This includes a redesigned Network Tab with two sections, “Grow” and “Catch Up,” aimed at helping users expand their network and stay updated on existing connections.

The “Grow” Tab

The “Grow” tab utilizes AI algorithms to help users manage connections and find new relevant contacts. It provides personalized suggestions through the “People You May Know” feature.

The “Catch Up” Tab

The “Catch Up” tab prompts users to reconnect with their network based on updates like job changes, work anniversaries, new hires, or birthdays. This aims to encourage more meaningful interactions between users.

Crafting The Perfect First Message

LinkedIn has introduced a Premium feature that helps users compose introductory messages when initiating conversations to address the “blank page problem” many face when starting conversations on the platform.

The tool provides draft messages tailored to both parties by incorporating information from their profiles, which users can customize to reflect their voice and goals for the conversation.

The Power of Connection

With over 5 billion connections made on the platform in 2023, LinkedIn expects engagement and interactions to grow in 2024.

As professional relationships can heavily influence career advancement, LinkedIn’s newest AI-powered features aim to make navigating the job market easier and more efficient for users looking to get ahead in competitive industries.


Featured Image: nitpicker/Shutterstock

LinkedIn Retires Lookalike Audiences, Urges Shift To New Targeting via @sejournal, @MattGSouthern

LinkedIn has announced it will discontinue its lookalike audiences feature starting February 29, 2024.

According to a statement from LinkedIn, after February 2024, advertisers will no longer be able to create new lookalike audiences or edit existing ones. Any current lookalike audiences will become “static” and stop refreshing with new data.

LinkedIn stated that active ad campaigns using lookalike audiences will continue to run but will be delivered to the now static audience pool. After 30 days of inactivity, unused lookalike audiences will be automatically archived by LinkedIn.

Alternatives: Predictive Audiences & Audience Expansion

As an alternative to the soon-to-be-phased-out lookalike audiences, LinkedIn recommends advertisers use its newer “Predictive Audiences” and “Audience Expansion” feature instead.

Predictive audiences utilize LinkedIn’s AI to build custom audiences likely to convert based on advertisers’ conversion data, lead gen forms, or contact lists.

Audience expansion is suggested for marketers looking to broaden their target demographics. It expands target audiences using LinkedIn’s professional demographic data.

Both features aim to help advertisers identify and reach high-intent individuals similar to their existing customers.

Predictive Audiences Details

You need at least 300 people in the selected data source to create a predictive audience. The system allows a maximum of 30 predictive audiences per ad account, and they can’t be shared between accounts.

Note that campaigns using predictive audiences won’t be able to expand the audience.

Audience Expansion Details

Audience expansion relies on professional demographics and can be combined with Matched Audience segments.

LinkedIn has highlighted that performance metrics include data from those you initially aimed your ads at and the wider group. However, you won’t be able to widen your audience for adaptive ad formats or audiences chosen based on predicted behaviors.

Implications For Current Campaigns

Any current ad campaigns using lookalike audiences must switch to predictive audiences or turn on audience expansion to keep a dynamic targeting approach. LinkedIn said there will be a 30-day grace period where unused lookalike audiences can still be accessed before being archived.

In addition, LinkedIn’s API for creating lookalike audiences through third-party marketing platforms like HubSpot will go away. This means marketers who rely on those integrations to build audiences will need another option.

Looking Ahead

LinkedIn stated that existing lookalike audiences will function normally until February 2024.

Advertisers are advised to begin using Predictive Audiences and Audience Expansion for future dynamic targeting needs. More details are available in LinkedIn’s announcement and help documentation.


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New AI Framework Powers LinkedIn’s Content Moderation via @sejournal, @martinibuster

LinkedIn rolled out a new content moderation framework that’s a breakthrough in optimizing moderation queues, reducing the time to catch policy violations by 60%. This technology may be the future of content moderation once the technology becomes more available.

How LinkedIn Moderates Content Violations

LinkedIn has content moderation teams that work on manually reviewing possible policy-violating content.

They use a combination of AI models, LinkedIn member reports, and human reviews to catch harmful content and remove it.

But the scale of the problem is immense because there are hundreds of thousands of items needing review every single week.

What tended to happen in the past, using the first in, first out (FIFO) process, is that every item needing a review would wait in a queue, resulting in actual offensive content taking a long time to be reviewed and removed.

Thus, the consequence of using FIFO is that users were exposed to harmful content.

LinkedIn described the drawbacks of the previously used FIFO system:

“…this approach has two notable drawbacks.

First, not all content that is reviewed by humans violates our policies – a sizable portion is evaluated as non-violative (i.e., cleared).

This takes valuable reviewer bandwidth away from reviewing content that is actually violative.

Second, when items are reviewed on a FIFO basis, violative content can take longer to detect if it is ingested after non-violative content.”

LinkedIn devised an automated framework using a machine learning model to prioritize content that is likely to be violating content policies, moving those items to the front of the queue.

This new process helped to speed up the review process.

New Framework Uses XGBoost

The new framework uses an XGBoost machine learning model to predict which content item is likely to be a violation of policy.

XGBoost is shorthand for Extreme Gradient Boosting, an open source machine learning library that helps to classify and rank items in a dataset.

This kind of machine learning model, XGBoost, uses algorithms to train the model to find specific patterns on a labeled dataset (a dataset that is labeled as to which content item is in violation).

LinkedIn used that exact process to train their new framework:

“These models are trained on a representative sample of past human labeled data from the content review queue and tested on another out-of-time sample.”

Once trained the model can identify content that, in this application of the technology, is likely in violation and needs a human review.

XGBoost is a cutting edge technology that has been found in benchmarking tests to be highly successful for this kind of use, both in accuracy and the amount of processing time it takes, outperforming other kinds of algorithms..

LinkedIn described this new approach:

“With this framework, content entering review queues is scored by a set of AI models to calculate the probability that it likely violates our policies.

Content with a high probability of being non-violative is deprioritized, saving human reviewer bandwidth and content with a higher probability of being policy-violating is prioritized over others so it can be detected and removed quicker.”

Impact On Moderation

LinkedIn reported that the new framework is able to make an automatic decisions on about 10% of the content queued for review, with what LinkedIn calls an “extremely high” level of precision. It’s so accurate that the AI model exceeds the performance of a human reviewer.

Remarkably, the new framework reduces the average time for catching policy-violating content by about 60%.

Where New AI Is Being Used

The new content review prioritization system is currently used for feed posts and comments. LinkedIn announced that they are working to add this new process elsewhere in LinkedIn.

Moderating for harmful content is super important because it can help improve the user experience by reducing the amount of users who are exposed to harmful content.

It is also useful for the moderation team because it helps them scale up and handle the large volume.

This technology is proven to be successful and in time it may become more ubiquitous as it becomes more widely available.

Read the LinkedIn announcement:

Augmenting our content moderation efforts through machine learning and dynamic content prioritization

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LinkedIn Reaches 1 Billion Members, Unveils AI Job Search Tools via @sejournal, @MattGSouthern

LinkedIn unveils AI-powered Premium update to provide personalized career guidance for professionals navigating evolving work landscape.

LinkedIn celebrated reaching 1 billion members this week by announcing an update to its Premium offering.

The revamped Premium service will leverage artificial intelligence (AI) to offer tailored career advice, uncover hidden opportunities, and streamline the job search process.

Personalized Guidance For An Evolving Workplace

The new Premium experience responds to the increasing skills gap facing today’s professionals.

According to LinkedIn, 65% of the skills needed to perform jobs are expected to change by 2030 as workplaces continue to evolve.

LinkedIn’s AI assistant will analyze users’ activity and interactions to surface relevant insights and next steps. For example, it may suggest skills to build, articles to read, or connections to reach out to based on a user’s career context.

It will take on the hard work of parsing through long articles, videos, and posts and suggest ideas on how the information can be helpful to you.

AI-Powered Job Search

LinkedIn’s most significant new addition is an AI-powered chatbot that serves as a “job seeker coach.”

Powered by OpenAI’s GPT-4 language model, the chatbot can analyze your profile and experience to assess your qualifications for a given role.

Premium users can activate the chatbot directly from a job posting and ask questions such as “Am I qualified for this role?” and “How can I best showcase my background?”

The chatbot will scan your profile and provide an assessment, for example, noting that you have previous experience in marketing and event organizing that matches well with the opening. It also highlights any gaps in your background that could hurt your application.

According to Erran Berger, LinkedIn’s VP of Product Engineering, building the infrastructure to support the chatbot required significant investment.

“We had to build a lot of stuff on our end to work around that and to make this a snappy experience,” Berger tells CNBC in an iterview. “When you’re having these conversational experiences, sometimes it’s almost like search — you expect it to be instant. And so there’s real platform capabilities we had to develop to make that possible.”

Bigger Picture

These new features come as LinkedIn looks to reaccelerate revenue growth after recent slowdowns.

Two weeks ago, the company announced nearly 700 layoffs, mostly in engineering.

However, with 1 billion members globally, LinkedIn remains the world’s largest professional networking platform.

While these offerings aim to help more people find jobs, they highlight LinkedIn’s commitment to helping people accomplish more with AI.


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LinkedIn Announces New AI Tools To Enhance Hiring & Learning via @sejournal, @MattGSouthern

LinkedIn recently announced new AI-powered products aimed at transforming recruitment and employee training.

The professional networking platform is responding to the evolving skill requirements in the workforce and the role HR departments play in managing this change.

LinkedIn cited a survey showing that 90% of HR professionals believe their role has become more strategic in the past year.

LinkedIn is launching pilot versions of its AI-enhanced recruiting tool Recruiter 2024 to aid HR teams and a new AI coaching feature for LinkedIn Learning.

Recruiter 2024 Leverages AI To Streamline Hiring

LinkedIn’s new Recruiter 2024 tool uses AI and internal data on over 950 million professionals to generate qualified job candidates beyond the usual target companies quickly.

This allows recruiters to describe ideal candidates in natural language instead of spending hours on manual candidate searches.

The AI can then suggest expanding locations, skills, and remote work options to widen the talent pool.

Recruiter 2024 moves away from relying solely on brand-name companies. Instead, it utilizes insights job candidates provide, such as their openness to work and interest in companies based on their values.

Additionally, LinkedIn announced integrations called CRM Connect that connect Recruiter with existing candidate relationship management systems.

AI Coaching Coming To LinkedIn Learning

LinkedIn announced an enhancement to the LinkedIn Learning platform, which includes AI-powered coaching via a chatbot interface.

The AI-powered coaching tool provides tailored advice based on specific job titles, career goals, and skills.

This feature is being tested for leadership and management skills, with plans to expand to other areas.

Looking Ahead

Recruiter 2024 and AI-powered coaching on LinkedIn Learning are being piloted with a select number of customers, with plans to expand access to all Recruiter and Learning Hub customers throughout the year.

These updates mark the beginning of LinkedIn’s foray into leveraging AI to support HR and learning and development professionals.


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