We detected 643 customers using Fraud Blocker, 101 companies that churned or ended their trial, and 23 customers with estimated renewals in the next 3 months. The most common industry is Retail (15%) and the most common company size is 11-50 employees (31%). Our methodology involves detecting JavaScript snippets or configurations on customer websites.
Note: We can only detect companies that installed the Fraud Blocker script on their website and not companies using server-side log analysis or API-based integrations (rare)
About Fraud Blocker
Fraud Blocker detects and blocks click fraud from bots, competitors, and other fraudulent sources on Google Ads and Meta platforms by tracking visitor IP addresses and devices for suspicious behavior.
🔧 What other technologies do Fraud Blocker customers also use?
Source: Analysis of tech stacks from 643 companies that use Fraud Blocker
Commonly Paired Technologies
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Shows how much more likely Fraud Blocker 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 Fraud Blocker users are heavily focused on conversion optimization and visitor analytics. These companies aren't just driving traffic to their websites. They're obsessively measuring what happens once people arrive, which makes sense when you're also concerned about fraudulent clicks eating into your ad budget. The concentration of tools like Truconversion, Microsoft Clarity, and Plerdy suggests these are businesses running significant paid advertising campaigns where every click costs money and conversion rates matter enormously.
The pairing of Fraud Blocker with ClickRack is particularly telling. ClickRack specializes in phone call tracking, meaning these companies are likely running campaigns where phone calls are a primary conversion goal, probably in higher-ticket B2B or local services. When you combine that with Salespanel for B2B visitor identification, you see a pattern: these businesses want to know exactly who's visiting their site and how those visitors convert into sales conversations. They're protecting their ad spend with Fraud Blocker while simultaneously trying to extract maximum intelligence from every legitimate visitor.
The full stack reveals marketing-led companies in growth mode, likely spending tens of thousands monthly on paid ads across Google, Facebook, or other platforms. They're sophisticated enough to use visitor session recording (Microsoft Clarity, Plerdy) but still lean toward point solutions rather than enterprise-grade platforms. This suggests mid-market companies or growing small businesses that have reached a scale where click fraud is a meaningful budget concern but haven't yet consolidated into all-in-one suites.
👥 What types of companies is most likely to use Fraud Blocker?
Source: Analysis of Linkedin bios of 643 companies that use Fraud Blocker
Company Characteristics
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Shows how much more likely Fraud Blocker 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
Funding Stage: Seed
11.9x
Industry: Retail
5.3x
Country: CA
4.7x
Country: AU
4.5x
Industry: Hospitals and Health Care
4.3x
Industry: Technology, Information and Internet
4.2x
I noticed that Fraud Blocker's typical customers operate in surprisingly traditional, high-touch industries where trust and reputation are everything. These aren't SaaS unicorns or tech disruptors. They're home builders like Atlantic Builders and Miller & Smith, automotive dealerships like Toyota of Orange and Empire Automotive Group, healthcare providers like Elder Care Homecare and GentleCare Therapy, and construction companies like JR & Co. Many run brick-and-mortar operations: restaurants (Acropolis Greek Taverna), furniture retailers (Roseland Furniture, National Business Furniture), hospitality venues (York Harbor Inn), and specialty suppliers (Gosford Quarries Sandstone, Western Pump).
These are mature, established businesses. The employee counts cluster around 50-200, suggesting companies large enough to have real revenue and ad budgets but not enterprise-scale. Very few show venture funding. When they do (like bttn with $20M Series A or SchoolAI with $25M), they're exceptions. Most have been operating for decades without external capital, which signals profitability and traditional business models that generate consistent cash flow.
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