Targeting in the Dark: Nearly 70% of 'Parents' Targeted by Ads Don’t Have Kids

New analysis by Adlook highlights socio-demographic targeting inaccuracies, wasting ad spend, and missing real consumer connections

NEW YORK, NY, UNITED STATES, March 13, 2025 /EINPresswire.com/ -- Adlook, a global media tech company specializing in digital advertising solutions, today announced the findings of an eye-opening study on the reliability of socio-demographic targeting — grouping audiences based on a combination of social and demographic traits, like age, gender, income, and lifestyle — in digital advertising. The results reveal major flaws in traditional socio-demographic targeting, highlighting the need for more accurate solutions that also align with the shift toward privacy-conscious marketing.

“Our analysis reveals that brands often rely on outdated demographic segments, resulting in inefficient and costly campaigns,” said Mateusz Jedrocha, Chief Product Officer at Adlook. “Legacy media-buying strategies and limited offline tools, like panels, force complex consumer profiles into broad categories such as ‘Women 20-44.’ In today’s digital age, this is unnecessary—brands can now target consumers based on real interests and behaviors, reducing wasted spend and reliance on outdated assumptions.”

The Study

Adlook conducted its study in September 2024, surveying 1,325 online respondents in the U.S. The methodology involved a two-step process that combined user polling with bid request data analysis via Adlook to assess the reliability of socio-demographic targeting.

1. Validation: Survey respondents were polled to determine whether they identified with the socio-demographic segments they were targeted for, based on third-party cookie-derived signals present in bid request data.
2. Overlap Analysis: The study then compared the survey results to the bid request data to examine whether segments designed to be mutually exclusive (e.g., “Men” vs. “Women” or “Age < 34” vs. “Age > 55”) were accurately delineated, or if significant overlap occurred.

Control questions were also included to ensure data integrity by filtering out respondents who provided random or inconsistent answers.

Key Findings

The study highlighted substantial challenges in the accuracy of socio-demographic targeting, with a key insight being the disconnect between targeting assumptions and actual audience composition:

- Precision Issues: For the commonly targeted segment of “Women 18-24,” for example, precision was found to be less than 20%. Among those targeted, 43% were men, 61% were over 24 years old (35% were above 55), and only 18% were women aged 18-24.
- Parental Status Misclassification: In the “Moms” segment, 52% of the targeted users identified as men, and 62% reported not having children. Similarly, 67% of users in the “Parents” segment declared they did not have children.

Across broader categories, inaccuracies persisted. For instance:

- 40% of users categorized as primary residence owners were actually renters, and vice versa.
- 67% of those targeted at a secondary school education level reported having a college or university degree.
- Half of the “Women” segment were men, and 76% of users targeted as “Married” declared they were not married.

“This is the inevitable outcome of flattening nuanced audience insights into simplistic demographic assumptions that rarely align with real-world behavior,” said Jedrocha. “The result is wasted ad spend and reduced campaign effectiveness.”

Insights on Segment Overlaps

Even simple socio-demographic segments that should be mutually exclusive revealed significant overlaps, meaning the same users were inaccurately classified into multiple, conflicting categories. For example:

- 35% of impressions were simultaneously eligible for both the “Women” and “Men” segments, while 55% fell into two or more age groups, demonstrating significant classification errors
- 28% of impressions were eligible for both the “Age < 34” and “Age > 55” segments.

“These findings expose a critical issue in digital advertising that too many are scared to call out around the lack of accuracy in socio-demographic targeting,” said Jedrocha. “But it’s not just about data accuracy; it’s about moving beyond outdated, simplistic audience definitions. Brands must adopt solutions that embrace the complexity of modern consumer behavior while improving transparency, reducing costs, and being privacy-centered.”

Adlook’s deep learning-powered solutions, such as Adlook Smart and Adlook Outcomes, are designed to address these challenges by offering guaranteed media quality and measurable outcomes without dependency on third-party cookies. These tools empower advertisers to reduce waste, enhance transparency, and achieve better results in a rapidly evolving digital landscape.

About Adlook

Adlook is a media tech company reshaping the future of programmatic advertising with privacy-first solutions.

Powered by our proprietary Deep-Learning Bidder, Adlook empowers leading brands and agencies to drive unmatched results. We're proud to bring programmatic back to its original vision - maximizing effectiveness and delivering unmatched audience planning to our Clients.

As early adopters of Chrome's Privacy Sandbox and Protected Audience API, Adlook leads the shift toward a cookieless future. With innovative solutions like Deep Search, Deep Context, and ContentGPT, we help brands transition smoothly from cookie-based to privacy-first advertising.

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