Baseline: US Meta Ads universe
The addressable audience in this dataset totals 252.2M, with 132.3M women and 119.9M men. Age concentration is strongest in 25–34 and 55+: on the female side, 25–34 (33.4M) and 55+ (36.5M) are the largest blocks; on the male side, 25–34 (32.0M) and 55+ (27.1M) stand out. This is the reference profile used to interpret how marketing and software interest clusters skew by age and gender.
US universe (All Population)
| Targeting | Female 18-24 | Female 25-34 | Female 35-44 | Female 45-54 | Female 55+ | Male 18-24 | Male 25-34 | Male 35-44 | Male 45-54 | Male 55+ | Total Male | Total Female | Grand Total |
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Data source: Meta Marketing API. Values may differ from Ads Manager.
Marketing interests
Marketing interests provide scale, but they do not represent “only marketers.” At this size, the audience typically includes a meaningful share of small business owners, junior specialists, freelancers, and people who follow marketing content without owning a buying decision. If your goal is lead generation quality, treat interests as a context layer and qualify with video-first creative that calls out role, business type, and minimum fit criteria early. In practice, this means segmenting messaging (e.g., operator vs manager vs exec) rather than pushing one generic offer to the entire interest pool.
Marketing interest examples
| Targeting | Female 18-24 | Female 25-34 | Female 35-44 | Female 45-54 | Female 55+ | Male 18-24 | Male 25-34 | Male 35-44 | Male 45-54 | Male 55+ | Total Male | Total Female | Grand Total |
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Data source: Meta Marketing API. Values may differ from Ads Manager.
Marketing software interests
Marketing software interests skew closer to practitioners because they align with real tooling and workflows (e-commerce platforms, CMS stacks, analytics, automation, CRM marketing). They still carry heavy SMB adoption, so lead quality improves when the creative matches a specific operating reality: stack compatibility, implementation depth, reporting expectations, and ownership model. Use video to separate “learning” audiences from buyers by stating the target role and the business context up front.
Marketing software examples
| Targeting | Female 18-24 | Female 25-34 | Female 35-44 | Female 45-54 | Female 55+ | Male 18-24 | Male 25-34 | Male 35-44 | Male 45-54 | Male 55+ | Total Male | Total Female | Grand Total |
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Data source: Meta Marketing API. Values may differ from Ads Manager.
Business software interests
Business software and ERP-style interests are usually more explicitly B2B and operational, but they often come with lower overall capacity than broad marketing layers. They work best as a qualifier when your SaaS offering requires governance, integrations, or structured processes. If you see mixed lead quality, split messaging for SMB operators versus structured teams, and use video to clarify the ICP (team size, system landscape, and decision ownership) before the click.
Business software examples
| Targeting | Female 18-24 | Female 25-34 | Female 35-44 | Female 45-54 | Female 55+ | Male 18-24 | Male 25-34 | Male 35-44 | Male 45-54 | Male 55+ | Total Male | Total Female | Grand Total |
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Data source: Meta Marketing API. Values may differ from Ads Manager.