We detected 600 customers using Mediamath, 160 companies that churned or ended their trial, and 10 customers with estimated renewals in the next 3 months. The most common industry is Retail (10%) and the most common company size is 51-200 employees (29%). Our methodology involves detecting JavaScript snippets or configurations on customer websites.
Note: We're unable to detect companies that use Mediamath via server-side conversion APIs
About Mediamath
Mediamath provides a demand-side platform that enables brands and agencies to execute programmatic advertising campaigns across omnichannel media including display, video, mobile, and connected TV using customizable technology, transparent AI-driven bidding algorithms, and log-level data access for performance optimization.
📊 Who in an organization decides to buy or use Mediamath?
Source: Analysis of 100 job postings that mention Mediamath
Job titles that mention Mediamath
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Based on an analysis of job titles from postings that mention Mediamath.
Job Title
Share
Director of Programmatic Media
18%
Senior Director of Digital Marketing
15%
VP of Business Development
12%
Account Director, Programmatic
10%
I noticed that MediaMath buyers are predominantly senior-level marketing and media leaders. Directors of Programmatic Media (18%), Senior Directors of Digital Marketing (15%), and VPs of Business Development (12%) lead purchasing decisions, followed by Account Directors focused on programmatic (10%). These leaders sit within agency holding companies like GroupM, Havas, and Publicis, as well as retail media networks and in-house brand teams. Their strategic priorities center on building programmatic capabilities at scale, particularly for financial services, healthcare, and retail sectors.
The day-to-day users are programmatic traders, campaign managers, and media buyers working across DSPs. I found these practitioners managing campaign setup in DV360, The Trade Desk, and MediaMath itself, handling trafficking, optimization, and performance reporting. They're responsible for audience segmentation, bid management, creative QA, and troubleshooting delivery issues. One posting described needing "advanced knowledge of audience segmentation and targeting strategies, including first-party data onboarding, lookalike modeling, and contextual targeting."
The core pain point revolves around scaling programmatic capabilities while maintaining accountability. Companies want to "establish and scale programmatic advertising capabilities" and deliver "measurable, meaningful moments between brands and people." Another posting emphasized the need to "make media smarter and more effective" through "smart, efficient, high-impact execution." The recurring theme is transforming from traditional media buying to data-driven, automated programmatic strategies that prove ROI and deliver performance at enterprise scale.
🔧 What other technologies do Mediamath customers also use?
Source: Analysis of tech stacks from 600 companies that use Mediamath
Commonly Paired Technologies
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Shows how much more likely Mediamath customers are to use each tool compared to the general population. For example, 287x means customers are 287 times more likely to use that tool.
I noticed that companies using Mediamath are clearly sophisticated programmatic advertising buyers running multi-channel campaigns at scale. The presence of tools like TheTradeDesk, Simpli.fi, and StackAdapt tells me these are organizations that don't rely on a single demand-side platform. Instead, they're running parallel campaigns across multiple programmatic platforms, which suggests they have dedicated media buying teams and substantial advertising budgets.
The pairing of Mediamath with TheTradeDesk is particularly revealing. These companies aren't just testing programmatic advertising, they're committed to it as a core strategy and want optionality in their platform choices. The strong correlation with TVSquared, a television attribution platform, shows they're bridging traditional TV and digital advertising. They're measuring how their programmatic campaigns influence television viewing and vice versa, which requires both budget and analytical sophistication. The presence of Spotify Ads alongside these tools confirms they're buying across premium inventory sources, not just standard display.
My analysis shows these companies are definitely marketing-led organizations, likely agencies, large e-commerce players, or brands with substantial direct-to-consumer operations. They're past the experimental phase with digital advertising and have reached a maturity level where they need multiple programmatic platforms, cross-channel attribution, and premium publisher relationships. The diversity of their stack suggests teams of 10 or more people managing media buying, with enough budget to justify paying for multiple enterprise-level platforms simultaneously.
👥 What types of companies is most likely to use Mediamath?
Source: Analysis of Linkedin bios of 600 companies that use Mediamath
Company Characteristics
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Shows how much more likely Mediamath customers are to have each trait compared to all companies. For example, 2.0x means customers are twice as likely to have that characteristic.
Trait
Likelihood
Industry: Banking
47.8x
Industry: Motor Vehicle Manufacturing
14.0x
Company Size: 1,001-5,000
10.2x
Industry: Real Estate
6.7x
Company Size: 51-200
4.6x
Country: US
4.3x
I noticed that Mediamath's customers span an incredibly diverse range of industries, but they share a common thread: they're primarily service-based businesses and retailers operating in highly competitive local or regional markets. Real estate agencies and brokerages appear most frequently, alongside financial services firms (banks, credit unions, mortgage lenders), automotive dealerships (particularly Lexus dealers), healthcare providers, educational institutions, and home service companies (plumbing, HVAC, pest control). These aren't software companies or B2B tech firms. They're businesses that need to reach consumers directly in specific geographic markets.
These are overwhelmingly mature, established businesses. I see founding dates from the 1800s through the 1990s, employee counts typically in the 50-500 range, and very few venture-backed startups. Most have no funding information listed, suggesting they're privately held or traditionally financed. They're not scaling rapidly or seeking exits. They're stable businesses focused on maintaining market position and competing for customers in crowded local markets.
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