We detected 925 customers using Rudderstack and 39 customers with estimated renewals in the next 3 months. The most common industry is Software Development (13%) and the most common company size is 11-50 employees (30%). Our methodology involves detecting JavaScript snippets or configurations on customer websites.
Note: We detect companies that deploy Rudderstack client-side (most cases), but not companies that use it purely on the server-side. We are also unable to detect churned customers for this vendor, only new customers
About Rudderstack
Rudderstack collects, transforms, and delivers customer event data in real time to business tools, data warehouses, and streaming platforms with over 200 pre-built integrations while maintaining data ownership through warehouse-native architecture that enables automated governance, consent management, and data quality controls.
📊 Who in an organization decides to buy or use Rudderstack?
Source: Analysis of 100 job postings that mention Rudderstack
Job titles that mention Rudderstack
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Based on an analysis of job titles from postings that mention Rudderstack.
Job Title
Share
Data Analyst
17%
Data Engineer
16%
Director of Analytics
16%
Backend Engineer
6%
I noticed that Rudderstack buyers span both leadership and technical roles, with 21% being leadership positions like Director of Analytics, Director of Product, and Head of CRM. The remaining 79% are individual contributors, primarily data analysts (17%), data engineers (16%), and backend engineers (6%). The purchasing decisions come from analytics, product, and marketing technology leaders who are prioritizing customer data infrastructure, product-led growth strategies, and cross-channel marketing measurement. These buyers are focused on building scalable data foundations that support AI initiatives, personalization, and unified customer views.
Day-to-day users are predominantly data professionals who implement and maintain customer data pipelines. Data engineers architect event streaming systems and build ETL processes, while analytics engineers create data models and transformation logic. Product analysts and marketing technologists configure audience segments, set up tracking schemas, and instrument event collection across web and mobile properties. Many postings emphasize hands-on work with tag management, server-side tracking, and identity resolution.
The pain points reveal companies struggling with data fragmentation and measurement accuracy. I saw phrases like "spearhead advanced digital analytics initiatives related to identity and clickstream data," "own and advance our server-side, mobile app and headless tracking set-up," and "design privacy-compliant analytics tracking capabilities." Organizations want to "create a single source of truth," enable "real-time personalization," and build "scalable, privacy-aware measurement." The emphasis on event-based architectures, CDP implementation, and marketing attribution shows companies investing in infrastructure that connects customer touchpoints across their entire tech stack.
🔧 What other technologies do Rudderstack customers also use?
Source: Analysis of tech stacks from 925 companies that use Rudderstack
Commonly Paired Technologies
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Shows how much more likely Rudderstack 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 Rudderstack users are sophisticated marketing and advertising technology companies that prioritize precise audience targeting and programmatic advertising. The overwhelming presence of ad tech platforms like Zemanta, Adform, and TheTradeDesk tells me these companies are deeply invested in paid acquisition strategies and need robust data pipelines to power their advertising campaigns across multiple channels.
The pairing of Rudderstack with TheTradeDesk and Adform makes perfect sense for companies running complex programmatic advertising operations. These tools need clean, well-structured customer data to build audience segments and optimize ad spend. Zemanta's strong correlation suggests these companies are also focused on native advertising and content discovery, requiring even more sophisticated data routing. The presence of Forethought, an AI customer support platform, indicates these companies are scaling rapidly and need automation to handle growing customer inquiries while maintaining data connectivity across their entire stack.
My analysis reveals these are marketing-led companies in growth or scale-up stages. They're past the early startup phase where simple analytics might suffice. Instead, they're managing multiple marketing channels, running significant ad budgets, and need enterprise-grade data infrastructure to tie everything together. The high correlation with Rudderstack Enterprise confirms they're willing to invest in premium data solutions, suggesting annual revenues likely in the tens of millions or higher.
👥 What types of companies is most likely to use Rudderstack?
Source: Analysis of Linkedin bios of 925 companies that use Rudderstack
Company Characteristics
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Shows how much more likely Rudderstack 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: Series A
34.2x
Funding Stage: Series unknown
19.8x
Funding Stage: Pre seed
14.5x
Industry: Professional Training and Coaching
7.0x
Industry: Wellness and Fitness Services
5.8x
Company Size: 1,001-5,000
4.9x
I noticed that Rudderstack's users span an incredibly diverse range of industries, from tech startups building AI agents and data platforms to consumer brands selling coffee, mattresses, and beauty products. What unites them isn't what they sell, but rather that they're digital-first businesses with meaningful customer touchpoints. Many are direct-to-consumer brands, SaaS platforms, marketplaces, or media companies that need to understand user behavior across multiple channels. Whether it's Bitpanda tracking crypto investors, The GIST growing their newsletter audience, or Wyze monitoring smart home device usage, these companies live and die by their ability to capture, analyze, and act on customer data.
These are primarily growth-stage companies. While the list includes some mature enterprises like Procter & Gamble and Avalara, the majority are Series A through Series C startups or bootstrapped companies with 50-500 employees. Many mention recent funding rounds, rapidly expanding teams, or aggressive growth targets. They're past the earliest validation stage but still scaling aggressively, which is exactly when data infrastructure becomes critical.
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