Audience Curation: Are You Weeding Out Faulty Audiences?

Advertising Audience Curation

Published on December 27, 2023

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When you buy a plant, you don’t plant it in the ground and then leave it be. Plants require a fair amount of upkeep to stay healthy, living, and growing. Like plants, the audience segments used in digital advertising campaigns also require tending to. Weeding out poor, out of date, or overall underperforming audience segments plays a huge part in a campaign’s success.

With deterministic attribution data, marketers can curate their audiences to optimize media efficiency. However, evaluating these audience segments on data management platforms (DMPs) is no simple task. Advertisers must weed through thousands of faulty, underperforming audiences via trial and error before curating their perfect audience configurations. There are many sneaky audience weeds that marketers may be unaware of and we’re here to pull out these weeds.

Isn’t Programmatic Advertising Enough? No.

With programmatic advertising gaining popularity, many marketers think converting to this targeting strategy will automatically increase their campaign’s performance. While programmatic advertising is substantially more productive than old-fashioned endemic techniques, it still requires weeding and watering.

Programmatic advertising allows marketers to hone in on interested car buyers, shrinking the market to include exclusively pre-market and in-market auto-intending individuals. Targeting advertising specialists can access massive quantities of audience segments offered on data management platforms, then buy and use these segments to shrink their advertising universe. This carves out the uninterested audiences to stop guessing where the desired individuals are.

Although this method is far more effective than endemic or untargeted advertising, many audience segments on DMPs are inaccurate, out of date, or completely incorrect. Many advertisers are missing out on the full potential of streaming advertising by running their campaigns with targeted, but unfiltered and underperforming audience segments. Programmatic advertising requires audience curation to function optimally, and the only way to weed out poor audience segments is to test run them in advertising campaigns and optimize from measured attribution data.

The Hard Truth about Audience Data

With thousands of automotive audience segments available, there’s competition among audience providers for business. Marketers are typically drawn to large audience pools because they believe that makes it easier to deliver their budget in full. This incentivizes audience providers to produce attractive-looking, large audience segments. Therefore, this means audience providers have no incentive to remove expired users from their data pool because they want to keep their audience large enough to deliver against.

For automotive, this looks like an audience provider keeping an in-market car buyer, who was 30 days from buying a car at the time of entry, in their audience segment for 2 years. These expired users were once in-market for a car, but no longer are; serving ads to them is meaningless. A large audience does not automatically mean it is a high-quality audience. The quality of the segments depends on the accuracy of their users, which is often hard to detect initially. Finding and curating these quality audience segments is a complex process.

Mindful of these dirty data pools, EMG audits their selected audience segments to ensure all users are on the correct time horizon of the customer journey. This means they are within the accurate number of days from buying a car and have proven to be actively moving through the market cohorts to remain in EMG’s audience groups. Constantly monitoring the age of the consumers in these segments is necessary to prevent serving ads to expired users. Ensuring that the right people see your ads is massively important — these are the people generating sales and walk-ins! By cleansing and curating audience pools, campaigns can confidently reach the right, interested viewers.

Setting the Stage with Baseline Metrics

In order to understand the impact a curated audience has on campaign lift, looking at the base performance rates is important. The par response rate for car-buyers is 2.75%. This means that 2.75% of any given population will be in-market for a car in any given month. If an automotive ad were shared to ten thousand people, and 275 people who saw that ad bought a car that month, that campaign had no genuine lift— those 275 people (2.75%) would have purchased a car with or without seeing an automotive ad that month. To see genuine lift, the media efficiency must be above the 2.75% of people who are buying a car nonetheless. In an honest campaign evaluation, 2.75% efficiency is really 0%, or the starting point.

6 Years Later: EMG’s Audience Curation Solution

Through 6+ years of audience auditing, EMG has evaluated and eliminated 99.8% (10,000!) of the audience segments offered on data management platforms. Only the top performing audience segments are currently used in our targeting, and many of those chosen segments are still internally filtered to some degree. As a result, EMG Audiences contain the most hyper-targeted, highly predictive auto intending audience segments available that consistently generate the highest conversion rates and media efficiency for their time cohorts.

How are These Audiences Curated?

Simply put, EMG looks for deviations from the par response rate (2.75%).

  • EMG analyzes each audience segment and eliminates audiences with conversion rates aligning with the par response rate. EMG only keeps segments that generate substantially more conversions than the 2.75% already buying a car.
  • Additionally, EMG keeps the audience groups at an optimal size for budget delivery and continuously adjusts the segments’ filters to fit the cohort’s time horizon. These filters eliminate expired users who have not been removed by audience providers.

EMG’s average media efficiency, or conversion rate, is 35%, meaning EMG is at least 8.5x more efficient at serving media to the right people than an untargeted or poorly targeted campaign would generate (a flat 2.75%).

EMG’s Market Groups: Considering the Customer Journey

EMG’s audience cohorts include pre-market, in-market, and conquest. These audience groups reflect the consumer journey, finding users at each stage of the car-buying process, whether they know they are about to buy a car or not. EMG finds indicators of pre-market individuals based on life changes and car-buying history, follows them through their in-market stage, and finally as they are about to buy a car in the conquest stage. EMG regularly evaluates and filters our audience segments to provide the most accurate reflection of the customer journey. We find these audiences exactly when they are of value, predictive of their exact timeline to vehicle purchase.

Last Thoughts:

Just because someone is advertising programmatically does not mean their campaigns will automatically jump in efficiency. Many of these audience segments are flawed and include expired users. Proper time and auditing are necessary to define the optimal audience configuration through campaign attribution optimization. EMG specializes in media efficiency, with our streaming campaigns averaging 35% media efficiency, against the national average of 2.75% efficiency. EMG creates at least 8.5x the average campaign lift by ensuring our audiences only contain active and interested auto intenders.

Want your streaming campaigns to deliver to highly curated automotive audiences? We know how. Get started today.

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