A 2023 SEMrush study says LinkedIn Lookalike Audiences changed digital ads a lot. Over 70% of advertisers used these audiences for their work. It’s still a good idea to check out other similar options too. Two common alternatives are Predictive Audiences and Audience Expansion. Just like most wide-reaching ad plans, premium tools work better than fakes. Predictive Audiences are one of these higher-quality paid options. They get more people to act on your ads than knockoff versions do. These strategies are backed by top U.S. ad expert groups. Those groups are SEMrush, HubSpot, and HubSpot. Pick the best plan for your local or global ad campaigns right now. You can get free setup and a guaranteed lowest price, but that’s just a figure of speech.

Definition and Discontinuation

A 2023 study from SEMrush found an interesting ad trend. More than 70% of people who run LinkedIn ads use lookalike audiences. They use these groups to get their ads in front of more people. Digital advertising changes all the time these days. That’s why it’s really important to understand how LinkedIn audiences work.

Definition of LinkedIn lookalike audience

Advertisers find LinkedIn’s Lookalike Audiences really useful. [1] says the tool is built to grow existing user groups. This means more people will see the ads you run. First, advertisers start with a “seed audience.” That’s a small set of people who already buy from you. [2] says LinkedIn uses smart computer programs to study this seed group’s data. The data covers details noted in [3]. It includes age and location, job titles, industry, and personal interests. LinkedIn uses this info to find people similar to the seed group. These people are more likely to interact with ads and buy your product. Let’s use a software company as an example. It has 500 customers, mostly mid-level managers in tech. LinkedIn finds other mid-level managers in smaller tech sub-fields who might want the software. [4] says you should track specific numbers for your seed audience. Those numbers include long-term customer spend, how often they buy, and their engagement with your brand. This info helps you find the best possible lookalike audiences.

Discontinuation of LinkedIn lookalike audiences (February 29, 2024)

LinkedIn will stop using lookalike audiences on February 29, 2024. Digital advertising trends are always shifting over time. The shift to Predictive Audiences fits a larger digital marketing trend [5]. That trend uses AI and data to make content feel personal for each user. LinkedIn suggests you explore Predictive Audiences first. You can also try the audience expansion tool noted in [6]. Starting this week, Predictive Audiences can include lists of companies. This change will make targeting the right groups of people easier [7]. Advanced algorithms find audiences similar to your existing ones. They can also spot buyers who will interact more and become customers [2]. Marketers should start using these methods to stay competitive. Tools like Google Analytics also recommend using these strategies. These are the key takeaways.

• LinkedIn has a feature called Lookalike Audiences. You can use this feature to find new buyers. These buyers are very similar to the ones you already have.
• LinkedIn is getting rid of its lookalike audiences feature. This change officially starts on February 29, 2024.
• Marketers have two great alternative targeting methods to consider. These are Predictive Audiences and Audience Expansion. Use our LinkedIn Audience Planner to make switching to these new targeting options much easier.

Alternatives for Similar Audience Expansion

The world of online advertising changes all the time. 70% of people who run ads are always looking for new ways to reach more people. LinkedIn recently got rid of its Lookalike Audiences ad targeting option. Now it’s important to find other ways to reach those same kinds of people.

Predictive Audiences

How it works

LinkedIn’s Predictive Audiences tool is a big step up for digital ads. It uses machine learning and smart, complex math to work. It first looks at data from your chosen starting group of users. That data includes age ranges, job titles, and what industry people work in. It also checks how much people spend over time, how often they buy things, how much they interact with content, and more. For example, say you run a successful ad campaign aimed at other businesses. Your starting target group is mid-level IT managers who work in finance. Predictive Audiences will use all these data points to find possible new customers most likely to follow through on your ad’s ask. You need to be as exact as possible when you build that starting group. If you want the most accurate possible audience, add in detailed numbers like total lifetime spending value and interaction scores.

Benefits compared to Audience Expansion

Performance Insights says predictive audiences work better than standard ad methods (info [8]). They get more ad clicks and more people to do what the ad asks for. Advertisers can use predictive audiences to skip pre-set targeting rules while staying accurate. The other common method is called Audience Expansion. It grows your target audience by finding people with similar habits and traits (info [5],[9]). It works in a much broader, less specific way though. Top ad industry tools recommend using predictive audiences. Using them can give you an advantage over competitors with better ad campaign results.

Audience Expansion

LinkedIn’s definition

LinkedIn has a tool called Audience Expansion. It helps you reach more people on the platform. It finds users with similar habits and traits to your target group. You can pick who to target based on user preferences. Your options include workplace, past jobs, education, and basic personal details. Say you want to reach marketing workers at tech startups. The tool will search for other LinkedIn users with similar profiles. But it is not as precise as the Predictive audiences feature. To get the widest possible reach, use it alongside other targeting methods. Those are the main key points to remember.

• Predictive audiences use machine learning to sort through data. This data comes from groups called seed audiences. They pick out people who are very likely to buy things. These potential buyers end up purchasing at higher rates than most people.
• The audience expansion method isn’t super precise. But it grows the group of people you’re targeting. It uses traits and behaviors similar to your current audience to do this.
• Mix different targeting methods to get the best possible results. Use our audience effectiveness calculator to see how these other options affect your campaign.

Seed Audience Best Practices

A 2023 study from SEMrush found a clear ad trend. Campaigns using well-defined seed audiences get better results. Their conversion rate is 30% higher than other campaigns. This stat shows how important smart LinkedIn ad targeting is. You should always aim your LinkedIn ads at the right group of people.

Key Metrics for Selection

Performance Metrics

You need key numbers to pick your best starting group of customers. These numbers include how much customers spend long term. They also cover how often people buy, and how much they interact with you. For example, a company that sells to other businesses might notice a pattern. Their best customers buy multiple times every calendar year. Those customers also interact with their LinkedIn page often. You should keep track of these key numbers consistently. Update them on a regular basis, too. Customer habits can change over time, so you can’t set these numbers once and forget them.

Audience Characteristics

Some tech helps find lookalike or predicted new audiences for you. It sifts through data from your core starting group of people. That data includes basic info like age, jobs, industries they work in, and their interests. Let’s say you run a marketing firm that targets online stores. Your core starting group could be marketing managers at well-known online shopping brands. These managers have a strong focus on digital ads in their job descriptions. This tech lets you build much more accurate lookalike or predicted audience groups. HubSpot says you should learn all about these traits deeply. That will help your marketing campaigns perform a lot better.

Campaign – Specific Metrics

When you run an ad campaign, you have to track key numbers. These include how many people see the ad, how many click it, and how much each new interested person costs. This data helps you spot areas that need improvement. If lots of people see your ad but very few act on it, you likely need to adjust your targeting. Use our campaign calculator to understand these numbers better. It will help you make smart choices based on real data.

Balancing Metrics

It’s important to balance different performance numbers for your campaigns. You can’t only focus on how much people interact with your content. You can’t ignore other key numbers, like how many people take the action you want. One software company tested this approach. They balanced three key numbers: total customer lifetime spending, audience interaction, and cost per new lead. This balance boosted their campaign’s overall return by 25%. You can use a weighted scoring system that fits your campaign’s goals. If your main goal is to find new potential customers, prioritize lead costs and completed action numbers more.

Impact of Seed Audience Size

The size of your audience affects your campaign’s results a lot. Smaller starting audiences help you target people better. But they can also limit how big your campaign can grow. A very large audience is more accurate but also broader. Startups with only a few customers benefit from starting small. That lets them build campaigns that reach exactly the right people. You can expand that starting audience as your company grows. Audience Penetration metrics on LinkedIn Campaign Manager can help you out. They let you figure out the best starting audience size to use.

Factors in Digital Marketing Strategy Context

Your seed audience needs to fit the main goal of your online marketing campaign. Pick this group to help you hit all your targets. Those targets might be getting people to know your brand, finding possible new customers, or keeping current customers coming back. For example, say you want to break into a whole new slice of the market. Your seed audience could be popular creators or early trend followers in that group. The most successful plans use AI tools made to build audience groups. These tools look at your whole online strategy and help you pick the right seed audience. Those are the key points to remember.

• Pick the group of people you want to target. You’ll use three common performance stats to make this choice. First is LTV, the total a customer spends on your brand over time. Next is how often people buy things from you. Last is how much people interact with your brand overall.
• First, think about the group of people you’re talking to. Pay attention to their basic personal background details. Keep track of what kind of job they have, too. Don’t forget to note what things they are interested in.
• Each specific campaign has its own unique tracking numbers. Use those numbers to tweak who you’re targeting with it.
• Balance different metrics for optimal results.
• When you’re planning your campaign, think about how big your audience is.
• If you’re doing online marketing, you start with a base group of people to target. Make sure this group lines up with your whole digital marketing plan.

Lookalike Segment Size Strategy

Did you know worldwide digital ad spending will hit $876 billion in 2024? That number comes from 2020 data shared by Statista. A big chunk of that money goes to targeted ad strategies. One popular targeted strategy uses what are called lookalike audiences. LinkedIn’s marketing space is changing really fast right now. How brands split up and use lookalike audiences on the site has shifted a lot. Most of this big shift is driven by the growth of predictive audiences.

Shift due to Predictive Audiences

Marketers are rethinking how they sort their target customer groups. This shift is happening because of LinkedIn’s new predictive audiences tool. The tool uses smart, complex computer formulas to find possible buyers. These buyers are more likely to interact and become paying customers (source [2]).

Higher click – through and conversion rates with smaller sizes

Research says smaller groups of similar potential customers work better. They get more people to click links and make purchases. A 2023 study from SEMrush confirms this. Companies that shrank these similar groups by 30% saw great results. Their click rates and purchase rates both went up. One business that sells to other companies struggled at first. They used really large similar customer groups and got almost no good results. Then they made their groups smaller and used more specific rules for members. After that, they got way more, higher quality customer conversions. Here’s a simple pro tip to get this right. Start with a small, clearly defined group of similar potential customers. Track how well it performs, like purchase rates and interaction scores. Slowly make your groups bigger based on what those numbers tell you.

Focus on quality over quantity

Back in the day, marketers often wanted to make huge look-alike audience groups. Their goal was to reach as many possible customers as they could. Now we have predictive audiences, so focus should be on quality over quantity. We use data-based personalization to find specific people. These people are similar to your original seed audience. They’re also more likely to do the actions you want them to take. Top digital marketing tools share a useful tip for this. Don’t cast a super wide net to catch more people. Instead, make your seed audience more specific. You can add metrics like lifetime value, how often people buy, and engagement score. This guidance comes from source 4, by the way. This lets you make lookalike groups that are more likely to take your desired actions. LinkedIn has lots of advanced targeting tools too. You can target people by where they live, details about their company, their education, work experience, and basic demographic info. Here are the key takeaways.

• If you split your audience into smaller groups, two important rates usually get higher. The first is click-through rate, or how often people click links you share. The second is conversion rate, or how often people take the action you want.
• Focus on improving the quality of your audience first. You can tweak this audience group using regular measurements. These measurements include LTV, how often people buy, and engagement scores.
• Use LinkedIn’s advanced targeting options to make more accurate lookalike groups. You can also use our LinkedIn Audience Performance Calculator. It will show you how different group sizes affect your campaign.

FAQ

What is a LinkedIn lookalike audience?

This article says a LinkedIn-style audience is a great ad tool. Advertisers start with a “seed group” of target or current customers. The platform checks the seed group’s demographics, job titles, and other data. It finds other buyers who share those same key traits. These buyers are much more likely to act on the ad. All these details are laid out in the “Definition of LinkedIn Lookalike Audience” analysis. Using this method helps grow total user numbers and ad views.

How to select the best seed audience for LinkedIn advertising?

Common industry standards guide how you pick a target audience. You have to consider a bunch of different factors first. Check performance stats like how much value a user brings over time and engagement scores. Also look at audience traits like age, job, and group memberships. To make your targeting sharper, track numbers for each specific campaign. It’s important to keep all these stats balanced fairly. These methods are laid out in [Key Metrics For Selection]. Using them will make your campaigns work a lot better.

Predictive Audiences vs Audience Expansion: What’s the difference?

Predictive audiences are different from audience expansion tools. Unlike audience expansion, they use machine learning to study your starting base audience data. They are better at finding people who are very likely to buy things from you. They also have higher conversion rates, meaning more people do what you want them to. Audience expansion widens the group of customers you target for your campaign. It uses shared customer traits, and works in a more careful, fine-tuned way. Common industry tools show predictive audiences help your campaigns succeed more easily.

Steps for creating an effective lookalike segment size strategy?

Start with a small, clearly defined group of lookalike audiences. Look at key numbers like click-through and conversion rates. Use your results to decide if you should grow these groups. Tweak your core audience using metrics like LTV and engagement scores. This lets you focus on quality instead of just large group sizes. LinkedIn has built-in advanced targeting tools you can use. This method is fully explained in the [Shift Due to Predictive audiences] analysis. It can help you get the best possible results from your campaigns.