In the ever-evolving world of digital marketing, success hinges on understanding your audience. While the deprecation of third-party cookies presents significant challenges across the industry, advertisers have a powerful tool at their disposal: first-party signals.
They are an integral part of building effective audience strategies, and when leveraged correctly, first-party signals can propel your campaigns to new heights. However, it’s not just about aggregating these signals; it’s about using them intelligently to reach the right audience at the right time.
The power of lookalike audiences
Savvy advertisers understand that one of the key strategies they can use to elevate their first-party signals is to create lookalike audiences. Lookalike audiences enable advertisers to tap into new high-value segments while maintaining relevance and reach.
When lookalike audiences are seeded from first-party signals, they become a particularly powerful tool to combat signal loss, because they create larger audiences from a source that does not rely on third-party cookies. This also enhances the customer experience and creates brand trust by delivering relevant content to audiences.
When lookalike audiences are created with technology providers that have their own valuable signals—such as Amazon’s proprietary browsing, purchasing and streaming signals—they become a powerful technique to expand your reach to potential customers who are more likely to convert.
For instance, clean rooms such as Amazon Marketing Cloud (AMC) can be used to unify information and create audiences based on advanced first-party insights combined with Amazon Ads aggregated signals. Then, these audiences can be activated on your programmatic media buy using Amazon DSP.
Signal-based audiences
Amazon Ads recently announced a new lookalike modeling feature in AMC (currently in beta) that can create audiences that are seeded by advanced queries of first-party signals, and are generated from the entire Amazon audience pool containing billions of signals. The size of the lookalike audience can be tailored to be extremely similar to the seed or very broad, making this a beneficial tool for lower funnel as well as prospecting campaigns.
Choosing what seed to start with is crucial to creating effective lookalike audiences, and there are several use cases for different types of seed audiences. Advertisers should focus on seeds that are aligned most with their goals for a particular campaign to see the most success.
For instance, using offline buyers as a seed makes sense if your campaign has an offline call-to-action, whereas brand loyalists are a great fit for promoting new product lines. Some general-purpose seed audiences to consider for full-funnel campaigns include frequent customers, new-to-brand customers and high-value customers.
Recently, GroupM used AMC lookalike audiences to improve its return on ad spend on a campaign for Colgate-Palmolive. GroupM seeded a lookalike audience with first-party signals representing high-value customers in the top 10% of spend, which resulted in a lookalike audience with millions of prospects. Compared to the other in-market and lifestyle audiences used in the campaign, the lookalike audience delivered a 21% higher return on ad spend.
Compelling results from customers using lookalike audiences based on first-party signals indicate that this tactic can strengthen an already sound digital marketing strategy. Advertisers who harness the power of their own signals and collaborate with technology providers to create lookalike audiences gain a competitive edge in the crowded digital landscape.
The precision, efficiency and relevance that result from this collaboration not only benefit advertisers but also enhance the overall online experience for consumers. By embracing this strategy, advertisers can embark on a journey of insight-driven growth, build stronger customer relationships and deliver more impactful marketing campaigns.
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Michelle Winters leads global product marketing for Amazon Ads across commerce, sponsored ads, streaming TV, video, audio, ad tech and measurement. Prior to Amazon, Winters was the director of ads product marketing for Meta in core ads and innovation, including audiences.
