Companies Using Dialogflow

When we first started tracking Dialogflow, it served a narrower audience. The data shows that has changed considerably.

1. Growth Trajectory

Dialogflow's adoption curve tells a story of early promise followed by market headwinds. The platform launched publicly in late 2018 with just 2 active domains, then grew steadily through 2019-2021 before experiencing explosive growth in 2022 (from 146 domains in January to 450 by December). It peaked at 1,043 domains in March 2025, but recent months show a 19.8% decline to 837 domains by July 2025. This contraction coincides with Google's 2025 rebranding to "Conversational Agents" and the rise of ChatGPT-based alternatives. The platform never achieved the scale of competing chatbot frameworks, Smooch has 7.6x more market share at 21.74%.

Sales Signal: Dialogflow's declining active domain count and minimal migration gains (only 3 companies in 5 years) indicate a shrinking addressable market. Sales teams selling to Dialogflow users should focus on migration services and platform modernization, not retention tools. The window for Dialogflow-native solutions is closing.

2. Customer Profile

Dialogflow customers skew heavily toward micro-businesses and public sector organizations. 53.8% have 1-10 employees, and only 3.2% are enterprise-scale (10,001+ employees), the lowest enterprise penetration I've seen for any Google Cloud product. 56.2% are privately held, with government agencies (5.8%) and educational institutions (5.8%) overrepresented compared to typical SaaS platforms. The customer base is digital-native, with 35.6% founded in the 2010s and 20.1% in the 2020s. Notable enterprise users like Atos, EasyJet, and Motorola exist, but their deployments are isolated projects (subdomain detections like galvin.motorola.com), not company-wide rollouts.

Sales Signal: These micro-businesses chose Dialogflow because it's free-tier friendly and integrates with Google Cloud Platform they already use. They can't afford enterprise chatbot platforms or dedicated AI teams. Tools targeting this segment must be priced under $100/month and require zero machine learning expertise.

3. Industry & Geographic Concentration

Dialogflow has found unexpected product-market fit in real estate (23.7%), nearly a quarter of all customers. Property management firms and leasing companies use it for lead qualification and tenant inquiry automation. Software development (7.1%) and IT services (5.5%) follow, but the real estate concentration is anomalous. Geographically, Brazil dominates at 36.7%, an unusual pattern for a Google product, the US typically leads. Latin America (Brazil, Colombia, Argentina, Chile) combines for over 40% of the user base, suggesting localized adoption driven by Portuguese/Spanish language support and Google Cloud regional pricing.

Sales Signal: The Brazil concentration creates two opportunities: (1) Portuguese-language conversational AI tools that integrate with Dialogflow, and (2) migration services targeting Brazilian SMBs looking to escape Google's network. The real estate vertical is underserved by specialized chatbot platforms. A gap worth addressing.

4. Migration Patterns

Dialogflow's migration data reveals a platform in trouble. The platform lost 9 companies to competitors over 5 years (3 to Smooch, 3 to Forethought, 3 to Genesys) but gained only 3 companies from competitors in the same period. That's a 3:1 loss-to-gain ratio, one of the worst I've analyzed. The minimal migration volume (9 total losses from 899 companies) suggests most churned customers didn't switch to tracked alternatives; they likely abandoned chatbots entirely or moved to untracked solutions like ChatGPT integrations. Recent losses to Genesys (2 in the last year) indicate enterprises are consolidating onto full contact center platforms.

Sales Signal: There are two viable plays here: (1) Migration services from Dialogflow to Genesys or Forethought (the platforms seeing recent inbound migration), and (2) Retention tools for existing Dialogflow users who are stuck due to sunk costs but aren't actively expanding usage. Don't build new Dialogflow integrations, the platform is in decline.

5. Technology stack

Dialogflow users run heavily Google-centric stacks. 80.1% use Google Tag Manager, 77.2% run Google Analytics, and 93.2% load resources from GStatic. The platform locks customers into Google Cloud Platform, 75.9% use Let's Encrypt via Google's automated certificate provisioning, and 94.99% enforce SSL by default. The front-end stack is legacy: 64.1% use jQuery and 66.4% include core-js (a polyfill for older browsers). React adoption is low (26.0%), suggesting these are older web properties. The most telling signal: 54.8% use Moment.js, a deprecated date library, these teams aren't keeping up with modern JavaScript practices.

Sales Signal: Dialogflow customers need front-end modernization services. They're running outdated web stacks and likely can't take advantage of newer conversational AI frameworks that assume React/Vue/modern bundlers. The gap: a migration service that refactors legacy Dialogflow chatbots to modern frameworks while preserving intent structures.

6. Key Takeaways

Dialogflow occupies a shrinking niche in the chatbots market. It peaked in early 2025 and has declined 19.8% since then, with negligible migration gains and a 3:1 churn ratio. The platform captured micro-businesses and public sector organizations that prioritize cost and Google integration over conversational sophistication, but Google's own rebranding to "Conversational Agents" signals the Dialogflow brand is sunsetting. The Brazil-real estate concentration is a localized phenomenon, not a global trend.

7. Sales Applications

Outreach Template (Migration Services): "Hi [Name], I noticed [Company] runs Dialogflow on [domain]. Google deprecated the Dialogflow brand in 2025 in favor of Conversational Agents, have you evaluated migration paths? We've helped [X] Brazilian real estate firms move to [alternative] while preserving intent structures and reducing costs by [Y%]. Worth a 15-minute call?"

Targeting Strategy: Filter TechnologyChecker.io for companies using Dialogflow + jQuery + founded 2010-2019 + Brazil or US + 1-50 employees + real estate industry. This segment is running legacy chatbots on deprecated frameworks and is ripe for modernization offers. Avoid enterprises (10,001+ employees), their Dialogflow deployments are isolated experiments, not company-wide initiatives.

Competitive Angle: Position against Dialogflow's lack of generative AI capabilities. While Google added Gemini integration to CCAI Platform, Dialogflow ES and CX remain intent-based. Customers who adopted Dialogflow in 2019-2022 for FAQ automation now expect ChatGPT-style dialogue, but can't afford enterprise platforms. The gap: a $50-200/month conversational AI product that bridges legacy Dialogflow intents to modern LLM backends.

For a complete list of companies using Dialogflow with enriched data (industry, size, location, tech stack), explore our database on TechnologyChecker.io. We track 899 companies with full LinkedIn enrichment from our monthly crawl of 29.6M domains.

Customer Reviews (G2)

Customer Sentiment: G2 reviewers cite ease of use (22 mentions) as the top strength, while cost of Google Cloud Dialogflow (6 mentions) as the most common complaint. Users also value powerful natural language understanding (11 mentions). Secondary concerns include cost to be overwhelming (6 mentions). The positive-to-negative mention ratio of 2.5:1 indicates strong overall satisfaction.

Customer Sentiment (G2)

I've cross-referenced our crawl data with G2 reviews, and the patterns align. Users consistently praise ease of use (22 mentions), which tracks with what we see in adoption rates. The main pain point? cost of Google Cloud Dialogflow (6 mentions). For teams evaluating this platform, the G2 sentiment data is worth factoring into your decision.