# Heap - Marketing Research Report Generated on: April 7, 2026 **Industry:** Marketing **Website:** https://www.heap.io ## The Takeaway Heap's moat is eliminating setup friction β€” automatic event capture means product teams skip months of engineering negotiation and start analyzing immediately. --- # Company Research ## Company Summary Heap is a digital insights platform company that provides analytics infrastructure and user behavior analytics solutions for businesses [1] **Founded:** Founded: 2013 [3] **Founders:** Founders: Ravi Parikh and Matin Movassate [3] **Employees:** Number of employees not publicly disclosed [5] **Headquarters:** Headquarters: California, United States [5] **Funding:** Series D funding of $110M with $960M valuation [4] **Mission:** Heap's mission is to provide analytics infrastructure that reduces the annoying parts of user analytics and helps businesses understand user behavior [1] **Strengths:** The company's strengths rely on the combination of automatic event tracking, comprehensive user behavior analytics, and seamless product-website data integration. [7] β€’ **Automatic Data Collection**: Captures all user interactions without manual event tracking setup, providing comprehensive behavioral insights [7] β€’ **Product-Market Integration**: Seamlessly connects product data and website data to provide unified analytics across customer touchpoints [8] β€’ **Advanced Analytics Features**: Offers conversion rate optimization, user behavior analytics, and AI-powered insights through Sense Contentsquare's AI assistant [7] ## Business Model Analysis ### 🚨 Problem ****Businesses struggle with fragmented analytics data and manual event tracking that creates blind spots in user behavior understanding** [1]** β€’ Companies face difficulties determining source of truth when web sessions and user data differ across analytics platforms [8] β€’ Manual event tracking requires significant engineering resources and often misses critical user interactions [7] β€’ Traditional analytics tools create silos between website traffic data and product usage data [8] β€’ Businesses lack actionable insights about user journey from initial visit to revenue conversion [9] ### πŸ’‘ Solution ****Heap provides automatic event tracking and comprehensive digital insights platform that captures all user interactions without manual setup** [1]** β€’ Automatic data capture of all user interactions eliminates need for manual event tracking implementation [7] β€’ Unified analytics platform connects website visits to revenue and product signups [8] β€’ AI-powered insights through Sense Contentsquare's AI assistant for advanced analysis [7] β€’ Comprehensive user behavior analytics including conversion rate optimization and trend analysis [9] β€’ Seamless integration between product data and website data for complete customer journey visibility [8] ### ⭐ Unique Value Proposition ****Heap offers automatic event tracking that captures complete user behavior data without requiring engineering setup, unlike traditional analytics platforms** [7]** β€’ Automatic data collection captures all user interactions without manual event implementation [7] β€’ Provides much more actionable data compared to basic web analytics tools like Google Analytics [10] β€’ Seamlessly connects product usage data with website traffic data in single platform [8] β€’ Offers unlimited enrichment sources and guides integrations in comprehensive package [7] ### πŸ‘₯ Customer Segments ****Heap serves small to enterprise SaaS companies, product teams, and digital businesses needing comprehensive user behavior analytics** [9]** β€’ Small and mid-market SaaS teams getting started with product analytics [9] β€’ Enterprise companies requiring advanced user behavior tracking and conversion optimization [7] β€’ Product managers and teams needing detailed user journey analysis [11] β€’ Digital businesses connecting website visits to revenue and product signups [8] β€’ Companies with high-traffic websites requiring scalable analytics solutions [6] ### 🏒 Existing Alternatives ****Heap competes with established analytics platforms including FullStory, Mixpanel, Amplitude, and Google Analytics in the digital insights market** [5]** β€’ FullStory provides session replay and user experience analytics [5] β€’ Mixpanel offers product analytics and user behavior tracking capabilities [10] β€’ Amplitude delivers product analytics and user journey analysis [12] β€’ Optimizely focuses on experimentation and conversion rate optimization [5] β€’ Google Analytics dominates web traffic analytics but provides less actionable product data [10] ### πŸ“Š Key Metrics ****Heap tracks session volume, user engagement, conversion rates, and customer journey analytics as primary business metrics** [6]** β€’ Monthly session limits determine pricing tiers starting at 10,000 sessions for free plan [6] β€’ User engagement tracking through in-app analytics and behavioral segmentation [9] β€’ Conversion rate optimization metrics connecting website visits to revenue [8] β€’ Customer retention and churn analysis through cohort analytics [18] β€’ Data history retention ranging from 6 months to 12+ months depending on plan [7] ### 🎯 High-Level Product Concepts ****Heap offers core analytics platform with automatic tracking, AI-powered insights, and comprehensive user behavior analysis tools** [7]** β€’ Core analytics charts with unlimited enrichment sources and integrations [7] β€’ Sense Contentsquare's AI-powered assistant for automated insights and recommendations [7] β€’ User behavior tracking including conversion funnels and trend analysis [9] β€’ Segmentation tools for detailed user group analysis and targeting [9] β€’ NPS surveys and in-app user engagement features integrated into analytics platform [9] ### πŸ“’ Channels ****Heap utilizes review platforms like G2, direct sales, and software marketplace listings for customer acquisition** [8]** β€’ G2 marketplace with customer reviews and product comparisons for lead generation [8] β€’ Direct sales for enterprise customers requiring advanced analytics solutions [7] β€’ Software review platforms including Capterra for business software discovery [20] β€’ Integration partnerships with tools like HubSpot, Intercom, and Google Analytics [12] β€’ Content marketing through product analytics comparisons and educational resources [12] ### πŸš€ Early Adopters ****Heap's early adopters were SaaS product teams and digital businesses needing automatic event tracking without engineering overhead** [9]** β€’ Small to mid-market SaaS teams seeking comprehensive product analytics without manual setup [9] β€’ Product managers frustrated with manual event tracking requirements of traditional analytics [11] β€’ Digital businesses needing to connect website traffic to product usage and revenue [8] β€’ Companies requiring more actionable data than basic web analytics could provide [10] ### πŸ’° Fees ****Heap uses session-based pricing model starting with free tier up to 10,000 monthly sessions, then paid plans scaling with usage** [6]** β€’ Free plan includes up to 10,000 monthly sessions with 6 months data history [7] β€’ Paid plans scale based on session volume with costs potentially reaching thousands annually for high-traffic sites [6] β€’ Growth plan includes unlimited users, 12 months data history, and email support [7] β€’ Enterprise pricing available with custom terms for large-scale implementations [7] β€’ Session volume-based pricing can escalate dramatically as website traffic grows [6] ### πŸ’΅ Revenue ****Heap generates revenue through subscription-based SaaS model with tiered pricing based on monthly session volume and feature access** [6]** β€’ Subscription revenue from paid plans scaling with customer session volume [6] β€’ Enterprise contracts for large customers requiring advanced features and support [7] β€’ Freemium model drives customer acquisition with conversion to paid plans as usage grows [7] β€’ Professional services and implementation support for enterprise customers [7] β€’ Revenue scales with customer growth due to session-based pricing model [6] ### πŸ“… History ****Heap was founded in 2013 by Ravi Parikh and Matin Movassate to solve user analytics tracking challenges** [3]** β€’ 2013: Company founded by Ravi Parikh and Matin Movassate [3] β€’ 2021: Completed Series D funding round raising $110M at $960M valuation [4] β€’ 2021: Achieved emerging unicorn status with near-billion dollar valuation [4] β€’ 2024: Integrated Sense Contentsquare's AI assistant into platform offerings [7] β€’ 2024: Expanded product analytics capabilities with advanced segmentation and trend analysis [9] ### 🀝 Recent Big Deals ****Heap completed $110M Series D funding round in 2021 achieving $960M valuation and emerging unicorn status** [4]** β€’ Series D funding of $110M closed to fuel future growth of digital analytics platform [4] β€’ Achieved $960M total company valuation establishing emerging unicorn status [4] β€’ Integration partnership with Contentsquare for AI-powered analytics capabilities [7] β€’ No major acquisitions or additional partnerships announced in the last 2 years [4] ### ℹ️ Other Important Factors ****Heap operates in competitive analytics market with escalating pricing concerns and data accuracy challenges compared to established platforms** [6]** β€’ Session-based pricing model can become cost-prohibitive for high-traffic websites [6] β€’ Data discrepancies between Heap metrics and Google Analytics can create source of truth challenges [8] β€’ Strong competition from established players like Mixpanel, Amplitude, and Google Analytics [5] β€’ Market positioned in growing B2B SaaS analytics segment with increasing demand for behavioral insights [15] --- # ICP Analysis ## Ideal Customer Profile Heap's ideal customers are **mid-market SaaS companies with 25-200 employees** operating product-led growth models who need comprehensive user behavior analytics without engineering overhead. These organizations have **dedicated product teams of 3-15 people** with product managers requiring detailed user journey analysis to optimize conversion rates and product adoption. They face challenges with **manual event tracking bottlenecks** in traditional analytics platforms and need **seamless integration between website and product data** to understand the complete customer journey from initial visit to revenue conversion. The ideal customer has **50K-500K monthly sessions** with established analytics budgets but values **automatic data capture** that eliminates setup complexity while providing actionable insights for product optimization. ## ICP Identification Framework | No. | Question | Answer | References | |-----|----------|--------|------------| | 1 | Which of our current customers makes the most out of our products and services? Who uses it the most? Who are your best users? | Best customers are **small to mid-market SaaS teams** with **5-50 employees** who need comprehensive product analytics without manual setup requirements. [9] These teams typically operate **high-growth digital businesses** connecting website visits to product signups and revenue. [8] They value **automatic event tracking** that eliminates engineering overhead while providing actionable behavioral insights. [7] | [7], [8], [9] | | 2 | What traits do those great customers have in common? | Common traits include **product-led growth focus** with dedicated product managers who require detailed user journey analysis. [11] They operate in **fast-paced environments** where manual event tracking creates bottlenecks and need **seamless product-website data integration**. [8] Most have **growing user bases** requiring scalable analytics solutions and value **unlimited users and reports** capabilities. [7] | [7], [8], [11] | | 3 | Why do some people decide not to buy or stop using our product? | Primary churn drivers include **escalating session-based pricing** as traffic grows, with costs reaching thousands annually for high-traffic websites. [6] Some customers experience **data accuracy concerns** when Heap metrics differ from Google Analytics, creating source of truth challenges. [8] Others find the platform **over-engineered** for basic analytics needs or prefer established alternatives. [10] | [6], [8], [10] | | 4 | Who is easiest to sell more to, and why? | Easiest expansion comes from **existing SaaS customers growing from startup to scale-up phase** as their session volumes and team sizes increase naturally. [9] [7] These customers already understand the value proposition and face **increasing analytics complexity** requiring advanced features like AI-powered insights and longer data retention. [7] **Product teams adding new features** consistently need expanded tracking capabilities. [9] | [7], [9] | | 5 | What do our competitors' best customers have in common? | Competitors' customers often prioritize **specific capabilities** like Google Analytics' traffic source tracking or Mixpanel's backend event integration. [10] [11] Opportunity exists with **product teams frustrated by manual event setup** in traditional analytics platforms and those needing **comprehensive behavioral insights** beyond basic web analytics. [10] **Growing SaaS companies** seeking unified product-website analytics represent key competitive targets. [8] | [8], [10], [11] | ## Target Segmentation ### πŸ₯‡ Primary Scale-Up SaaS Companies **Industry:** B2B SaaS, Digital Products, Technology **Company Size:** 25-200 employees, $1M-50M ARR **Key Characteristics:** β€’ **Product-led growth model**: Teams prioritizing user behavior insights for product optimization and conversion improvement β€’ **Dedicated product teams**: 3-15 person product organizations with product managers requiring detailed analytics without engineering bottlenecks β€’ **High session volumes**: 50K-500K monthly sessions requiring scalable analytics infrastructure with automatic event tracking **Rationale:** Highest revenue potential with predictable growth trajectory and established need for comprehensive product analytics beyond basic web metrics. ### πŸ₯ˆ Secondary Early-Stage SaaS Startups **Industry:** SaaS, Mobile Apps, E-commerce **Company Size:** 5-25 employees, $100K-5M ARR **Key Characteristics:** β€’ **Rapid iteration cycles**: Teams needing immediate insights without manual event implementation delays β€’ **Limited engineering resources**: Small teams requiring automatic data capture to avoid analytics setup overhead β€’ **Growth-stage funding**: Recently funded startups with budget for analytics tools but cost-conscious about scaling pricing **Rationale:** Strong expansion potential as they grow, but smaller initial contract values and price sensitivity limit immediate revenue. ### πŸ₯‰ Tertiary Enterprise Digital Teams **Industry:** Enterprise Software, Financial Services, Healthcare **Company Size:** 500+ employees, $50M+ revenue **Key Characteristics:** β€’ **Complex compliance requirements**: Teams needing advanced data governance and security features for regulated industries β€’ **Multiple product lines**: Organizations requiring unified analytics across various digital properties and customer touchpoints β€’ **Advanced analytics needs**: Teams leveraging AI-powered insights and custom integrations for sophisticated behavioral analysis **Rationale:** High-value contracts with advanced feature requirements, but longer sales cycles and complex procurement processes. ## Target Personas ### Persona 1: Sarah, The Scale-Up Product Leader *Segment: πŸ₯‡ Primary* **Demographics:** - Name: **Sarah, The Scale-Up Product Leader** - Age: **πŸ‘€ Age**: 32-38 - Job Title: **πŸ’Ό Job Title/Role**: VP of Product or Senior Product Manager - Industry: **🏒 Industry**: B2B SaaS Technology - Company Size: **πŸ‘₯ Company Size**: 50-200 employees - Education: **πŸŽ“ Education Degree**: MBA or BS in Computer Science/Engineering - Location: **πŸ“ Location**: San Francisco, Austin, or other tech hubs - Years of Experience: **⏱️ Years of Experience**: 8-15 years in product management **πŸ’­ Motivation:** Sarah needs **data-driven product decisions** to accelerate user acquisition and retention. **Manual event tracking** creates engineering bottlenecks that slow feature releases. **Unified analytics visibility** across the entire customer journey is critical for demonstrating product ROI. **🎯 Goals:** - Increase product adoption rates by 40% within 12 months - Reduce time-to-insight from weeks to hours for user behavior analysis - Demonstrate clear product-revenue correlation to executive leadership **😀 Pain Points:** - Engineering team overwhelmed with analytics setup requests delaying product development - Fragmented data sources making it impossible to understand complete user journey - Lack of real-time behavioral insights preventing rapid product iteration cycles ### Persona 2: Alex, The Startup Product Founder *Segment: πŸ₯ˆ Secondary* **Demographics:** - Name: **Alex, The Startup Product Founder** - Age: **πŸ‘€ Age**: 28-35 - Job Title: **πŸ’Ό Job Title/Role**: Co-Founder/Head of Product - Industry: **🏒 Industry**: Early-stage SaaS or Mobile Apps - Company Size: **πŸ‘₯ Company Size**: 8-25 employees - Education: **πŸŽ“ Education Degree**: BS in Computer Science or Business - Location: **πŸ“ Location**: Remote-first or major startup ecosystems - Years of Experience: **⏱️ Years of Experience**: 5-10 years in product or technical roles **πŸ’­ Motivation:** Alex needs **immediate product-market fit validation** through user behavior insights without technical complexity. **Limited resources** require automated solutions that provide maximum analytical value. **Investor reporting demands** clear user engagement and growth metrics. **🎯 Goals:** - Achieve product-market fit within 18 months using data-driven iteration - Implement comprehensive analytics without dedicated data engineering resources - Generate investor-ready growth metrics and user engagement reports **😀 Pain Points:** - No dedicated analytics engineer to implement complex tracking systems - Uncertainty about which user behaviors actually drive business value - Pricing concerns about analytics costs scaling with rapid user growth ### Persona 3: Michael, The Enterprise Analytics Director *Segment: πŸ₯‰ Tertiary* **Demographics:** - Name: **Michael, The Enterprise Analytics Director** - Age: **πŸ‘€ Age**: 40-50 - Job Title: **πŸ’Ό Job Title/Role**: Director of Product Analytics or Chief Data Officer - Industry: **🏒 Industry**: Enterprise Software, Financial Services, Healthcare - Company Size: **πŸ‘₯ Company Size**: 1,000+ employees - Education: **πŸŽ“ Education Degree**: MBA or MS in Data Science/Analytics - Location: **πŸ“ Location**: Major metropolitan areas with enterprise headquarters - Years of Experience: **⏱️ Years of Experience**: 15-25 years in analytics and data leadership **πŸ’­ Motivation:** Michael requires **enterprise-grade analytics infrastructure** supporting multiple product lines with advanced governance capabilities. **AI-powered insights** and predictive analytics are essential for strategic decision-making. **Compliance and security standards** must be maintained across all data collection. **🎯 Goals:** - Implement unified analytics platform across 5+ digital products and customer touchpoints - Leverage AI-powered insights for predictive customer behavior modeling - Ensure complete regulatory compliance while maximizing data utilization capabilities **😀 Pain Points:** - Complex procurement processes requiring extensive vendor evaluation and approval - Integration challenges across legacy systems and multiple technology stacks - Balancing advanced analytics capabilities with strict data governance requirements --- # Positioning & Messaging ## Positioning Statement **Heap** is a **digital insights platform** for **scale-up SaaS companies** that provides **automatic user behavior analytics and unified customer journey tracking** with/because of **zero engineering setup requirements and AI-powered actionable insights** ## Positioning Framework ### 1. Needs and Pain Points What are their customer's needs and pain points around the problem the product is trying to solve? β€’ Manual event tracking creates engineering bottlenecks that delay product development and feature releases [7] [11] β€’ Fragmented analytics data between website and product usage prevents understanding complete customer journey [8] β€’ Traditional analytics platforms require significant technical setup overhead that small teams cannot afford [9] β€’ Data accuracy inconsistencies across platforms create source of truth challenges for decision making [8] β€’ Lack of real-time behavioral insights prevents rapid product iteration cycles needed for competitive advantage [9] ### 2. Product Features What product features will address these needs and solve these pain points? β€’ Automatic event tracking captures all user interactions without requiring manual implementation or engineering resources [1] [7] β€’ Unified analytics platform seamlessly connects website visits to revenue and product signups in single dashboard [8] β€’ AI-powered insights through Sense Contentsquare's assistant provides automated analysis and recommendations [7] β€’ Unlimited enrichment sources and guides integrations eliminate data silos across customer touchpoints [7] β€’ Core analytics charts with customizable reporting enable immediate actionable insights without technical complexity [7] ### 3. Key Benefits What are the key benefits (rational and emotional) of those product features? β€’ Eliminates engineering overhead allowing product teams to focus on building features instead of analytics setup [7] [9] β€’ Provides complete customer journey visibility from initial website visit through product adoption and revenue conversion [8] β€’ Delivers actionable behavioral insights that drive data-driven product decisions and optimization [10] β€’ Reduces time-to-insight from weeks to hours enabling rapid iteration cycles and competitive advantage [9] β€’ Scales automatically with business growth without requiring additional technical resources or manual configuration [6] ### 4. Benefit Pillars Which of those benefits would be categorized as benefit pillars? πŸš€ Zero-Setup Analytics, πŸ”— Unified Journey Intelligence, ⚑ Instant Actionable Insights ### 5. Emotional Benefits What emotional benefits would the user have when they engage with or use the product? Core Emotional Promise: Empowers product teams with confident decision-making through comprehensive behavioral insights that eliminate guesswork and drive measurable business growth [8] [9] Supporting Emotions: β€’ Relief from engineering bottlenecks and technical complexity that previously blocked analytics initiatives [7] β€’ Confidence in data-driven product decisions backed by complete customer journey visibility [8] β€’ Control over product optimization with real-time insights enabling rapid iteration and competitive advantage [9] ### 6. Positioning Statement What are some positioning statements that could reflect its key benefits, product features, and value? Heap is a digital insights platform for scale-up SaaS companies that provides automatic user behavior analytics and unified customer journey tracking with zero engineering setup requirements and AI-powered actionable insights [1] [7] [8] ### 7. Competitive Differentiation How do they differentiate from other competitors? Heap uniquely provides automatic event tracking that captures complete user behavior without manual setup, unlike traditional analytics platforms that require extensive engineering resources [7] [10] vs. Google Analytics: Provides much more actionable product data beyond basic web traffic metrics, though GA maintains advantage in traffic source attribution [10] vs. Mixpanel: Eliminates manual event implementation requirements while providing unified product-website analytics that Mixpanel cannot match [10] [11] vs. Amplitude: Offers automatic data capture reducing technical overhead compared to Amplitude's manual event tracking approach [12] Key Differentiators: β€’ Automatic event tracking eliminates engineering setup requirements that competitors demand [7] β€’ Seamless product-website data integration provides unified customer journey visibility [8] β€’ AI-powered insights through Contentsquare partnership delivers advanced analysis capabilities [7] ## Messaging Guide | # | Type | Message | Priority | |---|------|---------|----------| | 1 | 🎯 Top-Line Message | Stop losing product insights to engineering bottlenecks - Heap automatically captures every user interaction to accelerate data-driven growth [7] | Primary | | 2 | πŸš€ Zero-Setup Analytics | Deploy comprehensive product analytics in minutes, not months, with automatic event tracking that requires zero engineering resources [7] | High | | 3 | πŸš€ Zero-Setup Analytics | Focus your engineering team on building features, not analytics infrastructure - Heap handles all the technical complexity automatically [7] | High | | 4 | πŸš€ Zero-Setup Analytics | Scale your analytics effortlessly as your user base grows without additional technical overhead or manual configuration [6] | Medium | | 5 | πŸ”— Unified Journey Intelligence | Connect every dot in your customer journey from first website visit to product adoption and revenue conversion [8] | High | | 6 | πŸ”— Unified Journey Intelligence | Eliminate data silos between website and product analytics to understand the complete customer experience [8] | High | | 7 | πŸ”— Unified Journey Intelligence | Bridge the gap between marketing attribution and product behavior with seamless cross-platform analytics integration [8] | Medium | | 8 | ⚑ Instant Actionable Insights | Transform user behavior into business growth with AI-powered insights that surface optimization opportunities automatically [7] | High | | 9 | ⚑ Instant Actionable Insights | Reduce time-to-insight from weeks to hours with automated analysis that drives immediate product optimization decisions [9] | High | | 10 | ⚑ Instant Actionable Insights | Make confident product decisions backed by comprehensive behavioral data that reveals what users actually do, not just what they say [10] | Medium | --- # References [1] Heap - Crunchbase Company Profile & Funding https://www.crunchbase.com/organization/heap [2] Heap 2025 Company Profile: Valuation, Investors, Acquisition | PitchBook https://pitchbook.com/profiles/company/56612-62 [3] Heap - 2025 Company Profile, Team, Funding & Competitors - Tracxn https://tracxn.com/d/companies/heap/__Sl1mRNJTh4tu_zUQWUYHf35O1c-6R1fsgRzDeWXmKD4 [4] Series D: Funding the Future of Digital Analytics - Heap.io https://www.heap.io/blog/series-d-funding-the-future-of-digital-analytics [5] Heap’s Competitors, Revenue, Number of Employees, Funding, Acquisitions & News - Owler Company Profile https://www.owler.com/company/heap [6] Heap product analytics: Features & pricing (+better alternative) https://usermaven.com/blog/heap-product-analytics [7] Pricing - Heap.io https://www.heap.io/pricing [8] Heap Reviews 2026: Details, Pricing, & Features | G2 https://www.g2.com/products/heap/reviews [9] Heap for Product Analytics: Features, Pricing, and Review https://userpilot.com/blog/heap-product-analytics/ [10] Google Analytics vs Mixpanel vs Amplitude vs Heap vs Woopra https://userguiding.com/blog/web-product-analytics-tools [11] r/ProductManagement on Reddit: What do you mainly use for product analytics? https://www.reddit.com/r/ProductManagement/comments/1cgssi7/what_do_you_mainly_use_for_product_analytics/ [12] Heap vs Amplitude vs Mixpanel for Product Analytics - Thoughts about Product Adoption, User Onboarding and Good UX | Userpilot Blog https://userpilot.com/blog/heap-vs-amplitude-vs-mixpanel-for-product-analytics/ [13] SaaS Market and Customer Segmentation. The Ultimate Guide. https://www.designwithvalue.com/customer-segmentation [14] GTM Segmentation Strategies for B2B SaaS: Frameworks That Actually Drive Revenue | Growigami https://pipelineroad.com/agency/blog/gtm-segmentation-strategies [15] B2B SaaS Market Size, Scope, Growth, Opportunities & Forecast https://www.verifiedmarketresearch.com/product/b2b-saas-market/ [16] 8 Best Methods for Market Segmentation for SaaS – Encharge https://encharge.io/best-segmentation-types-for-saas/ [17] B2B Enterprise Customer Segmentation Guide https://www.bettercommerce.io/blog/b2b-enterprise-customer-segmentation-drives-business-growth [18] r/SaaS on Reddit: Focused on G2 and Capterra for 6 months. 47 reviews. 23 customers. $41K in new ARR. https://www.reddit.com/r/SaaS/comments/1pisyig/focused_on_g2_and_capterra_for_6_months_47/ [19] 13 Capterra Customer Reviews & References | FeaturedCustomers https://www.featuredcustomers.com/vendor/capterra [20] Why Customer Success Should Care About Review Sites And Which Ones To Focus On https://churnzero.com/blog/why-customer-success-should-care-about-review-sites-and-which-ones-to-focus-on/