We detected 314 customers using DataDome, 52 companies that churned or ended their trial, and 1 customers with estimated renewals in the next 3 months. The most common industry is Retail (13%) and the most common company size is 51-200 employees (29%). Our methodology involves detecting JavaScript snippets or configurations on customer websites.
Note: We can't detect customers with API-only implementations or using it in mobile apps only (edge cases)
About DataDome
DataDome protects businesses from cyberfraud and bots in real time by securing websites, mobile apps, ads, and APIs using AI-powered detection that analyzes billions of signals daily.
๐ Who in an organization decides to buy or use DataDome?
Source: Analysis of 100 job postings that mention DataDome
Job titles that mention DataDome
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Based on an analysis of job titles from postings that mention DataDome.
Job Title
Share
Information Security Engineer
24%
DevOps Engineer (SRE)
19%
Backend Engineer
10%
Security Team Manager
5%
My analysis shows that DataDome is primarily purchased by security and infrastructure teams. Information Security Engineers represent 24% of roles, DevOps/SRE Engineers account for 19%, and various security-focused positions like DevSecOps Engineers and Application Security Engineers make up a significant portion of the remainder. These buyers are focused on bot management, fraud prevention, and protecting public-facing web properties. Their strategic priorities center on building scalable security architectures that can defend against sophisticated automated threats while maintaining site performance and availability.
Day-to-day users are hands-on engineers who integrate DataDome into their security and monitoring workflows. They configure WAF rules alongside other edge security tools, implement bot mitigation strategies, monitor traffic patterns, and respond to incidents. These practitioners work across cloud platforms like AWS and Azure, managing DataDome within broader observability stacks that include CloudWatch, monitoring dashboards, and CI/CD pipelines. They're embedding security controls into development processes and automating threat detection.
The core pain point is protecting against increasingly sophisticated bot attacks and online fraud. Companies describe needing to defend against threats from providers like Cloudflare, Akamai, and PerimeterX, seeking to "detect and block the most sophisticated bad bots in real time" and "protect against automated attacks and ensure application availability." Organizations want solutions that provide "robust, resilient and automated" security while supporting their goal to "free the web from fraudulent traffic" and safeguard critical e-commerce infrastructure serving millions of users globally.
๐ง What other technologies do DataDome customers also use?
Source: Analysis of tech stacks from 314 companies that use DataDome
Commonly Paired Technologies
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Shows how much more likely DataDome 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 DataDome's customers are predominantly digital publishers and media companies with sophisticated advertising operations. The presence of tools like Pubmatic, Teads, and Lotame tells me these companies generate revenue primarily through programmatic advertising and rely heavily on complex ad tech infrastructure. They're running high-traffic websites where both user experience and ad revenue optimization are critical business priorities.
The pairing with Pubmatic makes perfect sense since it's a supply-side platform that helps publishers monetize their inventory programmatically. When you're managing millions of ad requests daily, bot traffic becomes an existential threat to revenue and advertiser trust. Marfeel appearing so frequently is equally revealing because it's a content optimization platform specifically designed for publishers to improve engagement and reader retention. These companies are clearly focused on balancing monetization with user experience. The Lotame correlation reinforces this, as it's a data management platform that helps publishers build audience segments for more valuable ad targeting. Bot protection becomes essential when your business model depends on accurate audience data.
The full tech stack reveals these are mature, marketing-led organizations operating in a highly competitive digital publishing environment. They're not early-stage startups but established media companies dealing with scale challenges. The presence of Akamai MPulse for performance monitoring alongside DataDome shows they understand the technical complexity of their operations and invest in infrastructure that protects both revenue and user experience. These companies face constant pressure from both advertisers demanding clean traffic and readers expecting fast, reliable content delivery.
๐ฅ What types of companies is most likely to use DataDome?
Source: Analysis of Linkedin bios of 314 companies that use DataDome
Company Characteristics
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Shows how much more likely DataDome 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
Company Size: 1,001-5,000
17.2x
Country: FR
4.8x
Country: GB
3.7x
Company Size: 51-200
2.9x
Country: US
2.3x
Company Size: 11-50
1.1x
I noticed DataDome's customers span an incredibly diverse range of industries, but they share a crucial commonality: they all have significant digital properties that attract public traffic. These are companies running e-commerce platforms, publishing content to millions, operating marketplaces, or providing online services. I see major retailers like Schnuck Markets and London Drugs, media outlets like The Globe and Mail and The Oregonian, manufacturing giants like Bissell and Amway, and specialized platforms like WeddingWire and Talent.com. What unites them is that they all depend on their websites and digital channels to reach customers, readers, or users at scale.
These are predominantly mature, established enterprises rather than early-stage startups. The employee counts tell the story clearly: I see many companies with 500+ employees, several with over 1,000, and multiple with 5,000+. Most show no recent funding rounds, suggesting they're profitable, established businesses rather than venture-backed growth companies. The few funded companies that appear are typically Series B or later, already operating at scale.
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