We detected 345 customers using Thoughtspot, 141 companies that churned or ended their trial, and 21 customers with estimated renewals in the next 3 months. The most common industry is Software Development (27%) and the most common company size is 51-200 employees (26%). Our methodology involves discovering URLs with known URL patterns through web crawling, certificate transparency logs, or modifications to subprocessor lists.
About Thoughtspot
Thoughtspot provides an agentic analytics platform that enables users to query data and generate insights using natural language search, featuring an AI analyst called Spotter that delivers real-time, actionable analytics embedded within apps and workflows across cloud data platforms like Snowflake, BigQuery, and Databricks.
📊 Who in an organization decides to buy or use Thoughtspot?
Source: Analysis of 100 job postings that mention Thoughtspot
Job titles that mention Thoughtspot
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Based on an analysis of job titles from postings that mention Thoughtspot.
Job Title
Share
Director of Data Analytics
14%
Data Engineer
10%
Data Analyst
10%
Director of Product Management
6%
I noticed that 50% of the roles are leadership positions, with Director of Data Analytics leading at 14%, followed by Data Engineer and Data Analyst roles at 10% each. The buyers are primarily senior leaders in data and analytics functions who are building out modern data platforms and BI capabilities. These directors and VPs are focused on democratizing data access, driving adoption of self-service analytics, and modernizing legacy reporting systems. Product and engineering leaders also purchase ThoughtSpot when building customer-facing analytics or embedded intelligence solutions.
The day-to-day users span a wide range, from data engineers building pipelines and maintaining data quality to business analysts creating dashboards and generating insights. I found roles requiring hands-on work with ThoughtSpot alongside other modern tools like Snowflake, dbt, Databricks, and Tableau. These practitioners are designing semantic layers, developing automated reporting, and enabling business users to explore data independently without constant IT support.
The core pain points revolve around scaling analytics capabilities and reducing manual work. Companies want to "transform complex data into actionable insights," "democratize data across the organization," and "drive data-driven decision-making." Many descriptions mention eliminating bottlenecks by moving from "gut feeling" to "hard facts" and building "self-service" capabilities. The recurring theme is empowering non-technical users to access trusted data quickly while maintaining governance and data quality at scale.
🔧 What other technologies do Thoughtspot customers also use?
Source: Analysis of tech stacks from 345 companies that use Thoughtspot
Commonly Paired Technologies
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Shows how much more likely Thoughtspot 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 Thoughtspot users are predominantly B2B SaaS companies focused on customer success and data-driven operations. The combination of tools suggests these are mid-market to enterprise businesses that have graduated beyond basic analytics and need sophisticated self-service business intelligence. They're building extensive data ecosystems where multiple teams need to explore and visualize data independently.
The pairing with Atlan is particularly telling. Companies using data catalog software alongside Thoughtspot are managing complex data governance challenges, which means they have enough data sources and users that discovery and lineage matter. Mindtickle's presence suggests these companies run substantial sales enablement programs, indicating large or rapidly scaling go-to-market teams that need continuous training. The Qualtrics correlation reinforces this pattern of experience management maturity. These aren't just tracking operational metrics, they're systematically measuring customer and employee experience at scale.
My analysis shows these are primarily sales-led organizations in growth or scale-up phases. The prevalence of Rocketlane, a customer onboarding platform, and Decagon AI for customer support suggests they've moved past pure acquisition mode into retention and expansion. They're investing heavily in post-sale experiences because they likely have annual contracts with complex implementation cycles. The data sophistication indicates they're past the startup phase where everyone shares a single dashboard. They need democratized analytics because different departments are making independent decisions based on data.
👥 What types of companies is most likely to use Thoughtspot?
Source: Analysis of Linkedin bios of 345 companies that use Thoughtspot
Company Characteristics
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Shows how much more likely Thoughtspot 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
8.7x
Company Size: 51-200
1.3x
Country: US
1.1x
I analyzed these companies and found that ThoughtSpot's typical customer operates in data-intensive industries where understanding complex information drives business value. These aren't simple retail or services businesses. They're companies managing massive transaction volumes (Worldpay processing 40 billion transactions, DoorDash's logistics network), providing specialized B2B platforms (ModMed's healthcare EHR systems, Epicor's industry-specific software), or operating in regulated environments where data compliance matters (financial services, healthcare, insurance). Many are building technology that connects multiple stakeholders like Dockwa connecting marinas and boaters, or ProducePay linking growers and buyers in produce supply chains.
These are predominantly growth-stage to mature enterprises. The employee counts tell the story: I see many companies in the 200 to 2,000 employee range, with significant representation from both publicly traded firms (ServiceNow, Qualcomm, Booking.com) and well-funded private companies with Series C, D, or E rounds completed. Very few are early-stage startups. They've reached the complexity threshold where spreadsheets and basic BI tools no longer suffice.
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