LinkedIn is Removing Lookalike Audiences: What Marketers Need to Know

Starting February 29, 2024, you will no longer be able to create new lookalike audiences or refresh and edit current lookalike audiences. Lookalike audiences were designed to help expand audience reach by targeting individuals with similar characteristics to the base audience. Active lookalike audiences will continue to deliver as they appear until the end of February. After 30 days, if a lookalike audience is not active in a campaign, it will be archived.  

LinkedIn has launched predictive audiences, a new tool designed to enhance your campaign’s effectiveness by offering:

  • The ability to reach perfect-fit prospects by matching them with your existing customer base’s characteristics
  • AI-powered precision to identify high-intent buyers most likely to convert.
  • An effortless setup by simply combining your data with LinkedIn’s algorithm to automatically generate a custom audience tailored to your needs.
  • Lead generation gold: campaigns see a significant 21% reduction in cost-per-lead.

So what is the difference between the two? Lookalike audiences rely on historical data to mirror past behaviors of customers, assuming these behaviors will persist. In contrast, predictive audiences use AI to forecast future actions based on recent interactions, like website activity and email engagement, allowing for more tailored and anticipatory campaign personalization. This forward-looking approach enhances the experience by accurately predicting customer interests and potential actions. 

Practical Use

Predictive audiences can be created within the audience tab, found in the same location as lookalike audiences. After you name your audience you’ll be able to choose the source. All predictive audience sources require a minimum number of 300 members. Lastly, you’ll choose the location and size of the audience.

Options for expanding LinkedIn audiences in the future:

  • Predictive Audiences – expand your campaign’s reach by creating an audience that mirrors the traits of your existing data source who are more likely to convert.
    • Create a more targeted audience with minimal data sources, focusing exclusively on LinkedIn-specific inputs such as lead gen forms, contact lists, or conversions through the Insight Tag.
  • Audience Expansion: Target groups that share key characteristics with your primary audience, broadening your reach while maintaining relevance.
    • Attributes specifically excluded from your target audience will not be included in audience expansion.
    • When creating the campaign’s targeting, the audience count will not include members from audience expansion.
    • Audience expansion is not available when predictive audiences are selected.
  • LinkedIn Audience Network – deliver ads beyond the LinkedIn feed to members on third-party apps and sites.
    • The same targeting parameters, bid type, and budget created for your campaign applies.
    • This is only available for the following ad formats: single image, carousel, document, and video ads.

Say No to Lazy Data – How Everyone Can Be Part of the Solution

What is Lazy Data?

Picture this: a chaotic jumble of inconsistent formats, messy categories, and a general disregard for order. Lazy data isn’t just data that prefers lounging on the couch to hitting the gym; it’s the unruly teenager of your business – wild, rebellious, and refuses to conform to a standard.

This laid-back attitude is the root of the problem – a lack of discipline that prevents your data from realizing its full potential. Lazy data isn’t a solitary problem; it triggers a domino effect. One inconsistent entry leads to confusion in reporting, which, in turn, affects decision-making.

Why Did Data Get Lazy?

In the early days of digital marketing, the ease of connecting systems with just a click led to a somewhat chaotic scenario. Imagine the digital landscape as the Wild West, with data flowing freely and connecting without much oversight. While convenient, this Wild West approach allowed lazy data to thrive, as there were minimal checks and balances. The ability to effortlessly connect systems created a false sense of accuracy, like linking two puzzle pieces together without ensuring they fit. 

Inconsistent data entry, neglecting updates, and failing to recognize the importance of standardized schemas have allowed lazy data to infiltrate our systems. The result? Confusion, inefficiency, and missed opportunities.

As privacy regulations tightened, especially in the wake of concerns surrounding user data, businesses realized they could no longer afford a laissez-faire attitude. The emergence of data clean rooms and the imperative for strict naming convention compliance, essential for enabling tools like marketing mix modeling, forced a reckoning. Lazy data, accustomed to a more carefree existence, suddenly found itself in an environment that demanded structure and order.

While the concept of standardized schemas might initially seem bureaucratic, they are, in fact, the essential foundation for ensuring data usability. Consider it as akin to a musical performance without a conductor; in such a scenario, each instrument plays its own tune, leading to dissonance.

How to Solve  

Data should not be viewed as isolated islands or individual pieces. Instead, envision your organization as a harmonious orchestra led by a master conductor. This fresh perspective brings forth a unified approach, ensuring that every fragment of data performs its role seamlessly.

View Your Business as a System: Don’t think of your business data in silos or individual platforms. Instead, adopt a holistic approach, viewing your organization as an interconnected system – an orchestra led by a master conductor. This perspective helps in creating a seamless flow of information and makes sure that every piece of data plays its part.

Embrace the Standard: Establish a standard data schema across your business. Think of it as giving your data a set of rules to live by – no more rebels without a cause – every piece of data should know its role and play it well.

Audit to Insure: Regular audits are the insurance policy for your data’s health. Ensure that the established standards are being followed and identify any areas that might need a little extra TLC. An audit is like a health checkup for your data – catch potential issues before they become major problems.

How to Uncover Insights in Marketing Research

The tools we use to conduct marketing research and understand our target audiences and industries are constantly evolving. Traditionally, syndicated research tools have been the go-to resources to understand media consumption and behaviors.

But brand challenges require much more than knowing how many hours a day consumers watch TV to put together a successful marketing strategy. 

How to Find Meaningful Marketing Research Insights

Use both qualitative research and quantitative research to unveil unique marketing trends and audience learnings for brands. From social listening tools to focus groups to macro-level industry reports, you need multiple sources to achieve a 360 degree view with your marketing research. Instead of always turning to the same default tools and platforms, take on a journalistic mentality and get creative to discover unique insights that will differentiate your strategy from competitors. 

Lean into your creative side. Use out of the box tactics to search for answers to questions such as: 

  • What’s the press coverage on this topic? 
  • What changes are happening in the vertical? 
  • What’s happening in adjacent industries? 

From this type of information sourcing, you can then better contextualize the second or third party data embedded in syndicated research and build custom insights for your brand.

It’s also important to look at your own historical first party data, when available. Evaluate what’s been successful and not in order to provide a starting point to build baseline learnings.   

Balancing the Art and Science of Market Research

Marketing research is both an art and a science. You need some specific numbers to justify assumptions and hypotheses. But there’s also an element of simply trusting your intuition. A lot of times it’s right and a lot cheaper than running complex, time consuming studies. Your team’s instinct and experience is going to become increasingly valuable in finding insights and closing the gaps

Sometimes, simply putting yourself in your audience’s shoes and mimicking their behaviors reveals more than any survey could tell you. As an example, if your audience are heavy Twitter users and the data indicates they use certain hashtags – actually read through that content. Go to the subreddits they might frequent. Watch the Hulu shows they’re watching. Use this time of exploration to see if you can unveil something new about how your audience is living day to day.  

Avoiding Research Pitfalls

With so much data available, you can use research to essentially prove any point you want. This makes it easy for bias to creep into statistics, intentional or not. If you think the audience is Millennial Moms, there will undoubtedly be evidence somewhere pointing to confirm this assumption.

To avoid this, be transparent when your data does not back up your hypothesis. This is one of the more powerful things you can do to form trusting relationships with your colleagues and clients. It’s okay to admit if the research is refuting your initial assumption. Use this as an opportunity to build a bridge with this learning and adjust your strategy to continue making your marketing smarter.  

Additionally, when using third-party studies, it’s important to remember that people answering surveys aren’t always going to be completely truthful about their media consumption or lifestyle. Take a step back before blindly trusting what you’re reading and hearing.

Watch this video for more tips on avoiding common research mistakes:

Finding the Big Idea

Strategists are always digging for the ‘big idea’. The groundbreaking tactic, message, or plan the world has never seen before and will make you millions. If you have a predestined big idea in your head, don’t let that blind you from finding something even better. You need to ground yourself by exploring a variety of research sources without forcing anything. Allow the data to weave together a story rather than reverse engineering your predetermined story to create a successful path forward for your brand. 

Key Takeaways

In the impending privacy-first marketing landscape, there will be more emphasis on planning and finding the right research. Decision making is coming back to the hands of marketers, rather than left to platform algorithms.

Take a balanced, creative approach to the market research process and unlock the most meaningful insights to improve your bottom line and build customer loyalty. 

To hear more about Coegi’s approach to marketing research, contact us for a discovery call today.

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