Mastering LinkedIn Lookalike Audience: Alternatives, Seed Audience Best Practices & Segment Size Strategy

In the fast – paced world of digital advertising, LinkedIn lookalike audiences were a game – changer, as noted by a SEMrush 2023 Study, with over 70% of advertisers using them. But with their discontinuation in February 2024, it’s urgent to explore alternatives like Predictive Audiences and Audience Expansion. Premium options, such as Predictive Audiences, offer higher conversion rates compared to counterfeit – like broad strategies. Leading US authority sources like SEMrush and HubSpot back these tactics. Get a Best Price Guarantee and Free Installation Included (metaphorically) by choosing the right strategy today for your local and global campaigns.

Definition and Discontinuation

Did you know that over 70% of LinkedIn advertisers have utilized lookalike audiences to expand their reach, according to a SEMrush 2023 Study? Understanding LinkedIn lookalike audiences is crucial in the ever – evolving world of digital advertising.

Definition of LinkedIn lookalike audience

Lookalike audiences on LinkedIn are a powerful tool widely used by advertisers. As per [1], they are designed to help expand an existing user base and increase the number of ad viewers. Advertisers start with a “seed audience,” which is a group of their existing customers or target customers. The platform then uses sophisticated algorithms, as mentioned in [2], to analyze data points associated with the seed audience. These data points include demographics, job titles, industry affiliations, and interests (as described in [3]). Based on this analysis, LinkedIn identifies potential buyers who resemble the seed audience in terms of these characteristics and are more likely to engage and convert.
Practical Example: A software company has a seed audience of 500 existing customers who are mainly mid – level managers in the technology industry. Using LinkedIn lookalike audiences, the platform finds similar mid – level managers in related technology sub – industries who might be interested in the software.
Pro Tip: When creating your seed audience, include metrics like lifetime value (LTV), frequency of transactions, and engagement scores as suggested in [4]. This will help you identify the best candidates for your lookalike audience creation.

Discontinuation of LinkedIn lookalike audiences (February 29, 2024)

The digital advertising landscape is constantly changing, and as of February 29, 2024, LinkedIn is discontinuing lookalike audiences. This move from Lookalike to Predictive audiences reflects a broader trend in digital marketing: AI – powered, data – driven personalization [5]. Instead of relying on the traditional lookalike models, LinkedIn suggests exploring Predictive Audiences or Audience Expansion as seen in [6].
Predictive Audiences, starting from this week, can now include company lists, which will further expand targeting capacity [7]. It uses advanced algorithms to not only find similar audiences but also pinpoint potential buyers who are more likely to engage and convert [2].
As recommended by industry tools like Google Analytics, marketers should start transitioning towards these new methods to stay competitive in the market.
Key Takeaways:

• Lookalike audiences on LinkedIn use seed audience data to find similar potential buyers.
• LinkedIn will discontinue lookalike audiences on February 29, 2024.
• Marketers should consider Predictive Audiences or Audience Expansion as alternatives.
  Try our LinkedIn audience planner to help you transition smoothly to these new audience – targeting options.

Alternatives for Similar Audience Expansion

According to recent SEMrush 2023 Study, in the dynamic realm of digital advertising, 70% of marketers are constantly on the lookout for effective audience – expansion strategies. As LinkedIn removes Lookalike Audiences as an ad – targeting option, it’s crucial to explore alternative ways to reach similar audiences.

Predictive Audiences

How it works

Predictive Audiences on LinkedIn represent a significant advancement in digital advertising technology. Harnessing the power of machine learning, this tool uses sophisticated algorithms. It analyzes the data points associated with your seed audience, which can include demographics, job titles, industry affiliations, lifetime value (LTV), frequency of transactions, and engagement scores (info [3], [4]).
For instance, if you have a successful B2B software campaign with a seed audience of mid – level IT managers in the finance industry, Predictive Audiences will analyze these data points to pinpoint potential buyers who are more likely to engage and convert (info [2]).
Pro Tip: When building your seed audience, be as specific as possible. Include detailed metrics like LTV and engagement scores to get a more accurate predictive audience.

Benefits compared to Audience Expansion

Performance Insights have shown that despite smaller audience sizes, predictive audiences showed higher click – through and conversion rates compared to standard methods (info [8]). Predictive Audiences help advertisers go beyond predefined targeting criteria while still ensuring precision. In contrast, Audience Expansion broadens the target audience based on similar characteristics and behaviors, but in a less precise manner (info [5], [9]).
As recommended by leading industry tools, leveraging Predictive Audiences can give you a competitive edge in terms of campaign effectiveness.

Audience Expansion

LinkedIn’s definition

Audience Expansion on LinkedIn broadens your target audience based on similar characteristics and behaviors. Subject to members’ preferences, you can choose targeting options from locations, audience attributes such as company, job experience, education, and demographics (info [10], [9]).
Let’s say your current audience consists of marketing professionals in the tech startup space. Audience Expansion will find other LinkedIn members with similar professional profiles, but it won’t be as refined as Predictive Audiences.
Pro Tip: Use Audience Expansion in combination with other targeting methods to maximize your reach.
Key Takeaways:

• Predictive Audiences use machine learning to analyze seed – audience data and find high – potential buyers with better conversion rates.
• Audience Expansion broadens the target audience based on similar characteristics and behaviors but is less precise.
• Combine different targeting methods for optimal results.
  Try our Audience Effectiveness Calculator to see how these alternatives can impact your campaign.

Seed Audience Best Practices

Did you know that according to a SEMrush 2023 Study, campaigns using well – defined seed audiences can see a conversion rate increase of up to 30%? This statistic underscores the importance of getting your seed audience right in LinkedIn advertising.

Key Metrics for Selection

Performance Metrics

When selecting a seed audience, performance metrics are crucial. Metrics such as lifetime value (LTV), frequency of transactions, and engagement scores are essential to identify the best candidates for your seed audience. For example, a B2B software company might find that customers who have made multiple purchases in a year and have high engagement on their LinkedIn page are the best candidates for their seed audience. Pro Tip: Regularly track and update these performance metrics as customer behavior can change over time.

Audience Characteristics

The underlying technology for finding lookalike and predictive audiences analyzes data points like demographics, job titles, industry affiliations, and interests of the seed audience. For instance, if you’re a marketing agency targeting e – commerce businesses, your seed audience could consist of marketing managers from well – known e – commerce brands with a focus on digital marketing in their job descriptions. This will help in creating more accurate lookalike or predictive audiences. As recommended by HubSpot, understanding these characteristics in detail can significantly boost the effectiveness of your campaigns.

Campaign – Specific Metrics

It’s important to track key metrics like impressions, clicks, conversions, and cost – per – lead (CPL) for your campaigns. Analyzing this data helps in identifying areas for improvement. For example, if a campaign has high impressions but low conversions, it might be a sign that the targeting needs to be refined. Try our campaign performance calculator to better understand these metrics and make data – driven decisions.

Balancing Metrics

Balancing different metrics is a delicate but essential task. You can’t just focus on one metric, like engagement, and ignore others like conversion rates. A case study of a SaaS company showed that by finding the right balance between LTV, engagement scores, and CPL, they were able to increase their campaign ROI by 25%. Pro Tip: Use a weighted scoring system for different metrics based on your campaign goals. If your main goal is lead generation, give more weight to CPL and conversion metrics.

Impact of Seed Audience Size

The size of your seed audience can significantly impact your campaign results. A smaller seed audience might lead to more precise targeting but could limit the scale of your campaign. On the other hand, a very large seed audience might result in a broader but less accurate lookalike audience. For example, a startup with a small customer base might benefit from starting with a more focused seed audience to build targeted campaigns. As the business grows, they can expand the seed audience size. LinkedIn’s Campaign Manager’s Audience Penetration metric can be very helpful in determining the optimal seed audience size.

Factors in Digital Marketing Strategy Context

In the context of a broader digital marketing strategy, the seed audience should align with your overall goals. Whether you’re aiming for brand awareness, lead generation, or customer retention, the seed audience selection should support these objectives. For instance, if your goal is to enter a new market segment, your seed audience could be early adopters or influencers in that segment. Top – performing solutions include using AI – powered audience creation tools to better analyze and select the right seed audience based on your digital marketing strategy.
Key Takeaways:

• Select a seed audience based on performance metrics like LTV, frequency of transactions, and engagement scores.
• Analyze audience characteristics such as demographics, job titles, and interests.
• Track campaign – specific metrics to refine your targeting.
• Balance different metrics for optimal results.
• Consider the impact of seed audience size on your campaigns.
• Ensure the seed audience aligns with your overall digital marketing strategy.

Lookalike Segment Size Strategy

Did you know that digital advertising spending worldwide is projected to reach $876.0 billion in 2024, with a significant portion going towards targeted audience strategies like lookalike audiences (Statista 2024)? In the dynamic landscape of LinkedIn marketing, the lookalike segment size strategy is undergoing a notable shift, largely influenced by the rise of predictive audiences.

Shift due to Predictive Audiences

The emergence of predictive audiences on LinkedIn is causing marketers to reevaluate their lookalike segment size strategies. These new – age audiences use sophisticated algorithms to pinpoint potential buyers who are more likely to engage and convert (source [2]).

Higher click – through and conversion rates with smaller sizes

Research indicates that smaller lookalike segments often yield higher click – through and conversion rates. A SEMrush 2023 Study found that when companies reduced their lookalike segment sizes by 30%, they saw an average increase of 20% in click – through rates and 15% in conversion rates. For example, a B2B software company was struggling to get traction with large, broad lookalike segments. After reducing the segment size and focusing on more precise criteria, they noticed a significant improvement in the quality of leads and the number of conversions.
Pro Tip: Start with a small, well – defined lookalike segment. Analyze the performance metrics such as click – through rates, conversion rates, and engagement scores. Based on these results, gradually scale up your segment size.

Focus on quality over quantity

In the past, marketers might have been tempted to create large lookalike segments to reach as many potential customers as possible. However, with the advent of predictive audiences, the focus should be on quality rather than quantity. Predictive audiences use data – driven personalization to identify individuals who are not just similar to your seed audience but are also more likely to take the desired action.
As recommended by leading digital marketing tools, instead of casting a wide net, refine your seed audience by including metrics like lifetime value (LTV), frequency of transactions, and engagement scores (source [4]). This will help you create more targeted lookalike segments that are likely to convert.
Top – performing solutions include using advanced targeting options provided by LinkedIn, such as locations, audience attributes like company, job experience, education, and demographics (source [10]).
Key Takeaways:

• Smaller lookalike segments tend to have higher click – through and conversion rates.
• Focus on quality by refining your seed audience using metrics like LTV, transaction frequency, and engagement scores.
• Leverage LinkedIn’s advanced targeting options for more precise lookalike segment creation.
  Try our free LinkedIn audience performance calculator to see how different segment sizes can impact your campaign results.

FAQ

What is a LinkedIn lookalike audience?

According to the article, a LinkedIn lookalike audience is a powerful advertising tool. Advertisers start with a “seed audience” of existing or target customers. The platform then analyzes data points like demographics and job titles of this seed group. It identifies potential buyers with similar characteristics, likely to engage and convert. Detailed in our [Definition of LinkedIn lookalike audience] analysis, it helps expand the user base and increase ad views.

How to select the best seed audience for LinkedIn advertising?

As per industry best practices, select a seed audience based on multiple factors. First, consider performance metrics such as lifetime value (LTV) and engagement scores. Also, analyze audience characteristics like demographics and industry affiliations. Track campaign – specific metrics to refine targeting. Balancing these metrics is crucial. Detailed in our [Key Metrics for Selection] section, using these methods can enhance campaign effectiveness.

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

Unlike Audience Expansion, Predictive Audiences use machine learning to analyze seed – audience data. Predictive Audiences are more precise, finding high – potential buyers with better conversion rates. Audience Expansion broadens the target audience based on similar characteristics in a less refined way. As recommended by industry tools, Predictive Audiences offer a competitive edge in campaign effectiveness.

Steps for creating an effective lookalike segment size strategy?

Start with a small, well – defined lookalike segment. Analyze performance metrics like click – through and conversion rates. Based on the results, gradually scale up the segment size. Focus on quality over quantity by refining your seed audience with metrics such as LTV and engagement scores. Leverage LinkedIn’s advanced targeting options. Detailed in our [Shift due to Predictive Audiences] analysis, this approach can optimize campaign results.