Companies that use Heap

Source: Analysis of 100 job postings that mention Heap

My analysis shows that Heap buyers are concentrated in analytics and product leadership roles. Directors of Product Analytics and Digital Analytics make up 25% of the decision makers, followed by Heads of Data (10%), VPs of Engineering (9%), and Directors of Product Management (8%). These leaders are hiring for teams focused on product-led growth strategies, customer journey optimization, and data-driven decision making. They prioritize building analytics capabilities that can scale across complex digital ecosystems.

The day-to-day users span product analysts, data engineers, and product managers who need to understand user behavior at scale. I found multiple references to teams using Heap alongside other tools like Mixpanel, Amplitude, and Snowflake to instrument events, track conversion funnels, and optimize product experiences. These practitioners are building dashboards, conducting A/B tests, analyzing user journeys, and translating behavioral data into actionable product improvements.

The job descriptions reveal companies struggling with activation, retention, and monetization challenges. One posting emphasized the need to "build growth loops and self-serve onboarding experiences that accelerate product adoption," while another sought someone to "identify friction points" in the user journey to "increase Activation and Revenue." A third described the mission to "illuminate the experience of our customers in our digital product journeys and connect those experiences to business outcomes." These companies need Heap to move faster, convert better, and make data accessible across teams without heavy technical overhead.

Source: Analysis of tech stacks from 3,124 companies that use Heap

I noticed companies using Heap are deeply invested in understanding user behavior through multiple analytical lenses. The strong presence of Contentsquare, Segment, and Amplitude alongside Heap tells me these are product-led B2B companies that treat analytics as a competitive advantage. They're not just tracking basic metrics but building sophisticated data infrastructure to capture every nuance of how users interact with their products.

The pairing of Heap with Segment makes particular sense because Segment acts as a data pipeline that feeds multiple analytics tools. These companies want flexibility in their analysis, using Heap's automatic event tracking alongside other specialized tools. The Amplitude correlation reinforces this: they're running parallel analytics systems to validate insights and catch blind spots. Meanwhile, Intercom Help Center appearing frequently suggests they're connecting user behavior data directly to support operations, likely using product analytics to reduce support volume and identify friction points before users need help.

My analysis shows these are typically growth-stage B2B SaaS companies operating with a product-led growth model. The presence of Reddit Ads indicates they're experimenting with diverse acquisition channels beyond traditional enterprise sales. Zoom Business being common suggests distributed teams that have scaled beyond startup size but haven't necessarily moved to enterprise communication platforms. They're data-sophisticated enough to maintain multiple analytics tools, which requires both budget and technical resources. This isn't a sales-led motion where a single CRM dominates the stack. Instead, the product itself is the primary growth engine, and they're investing heavily in understanding exactly how users experience it.

Source: Analysis of Linkedin bios of 3,124 companies that use Heap

I noticed Heap's customers span an incredibly diverse range of what they actually build and sell. There are SaaS platforms solving specific business problems (AI meeting schedulers, procurement automation, compliance software), consumer-facing marketplaces and e-commerce sites (furniture retailers, tile sellers, luxury fashion brands), hospitality businesses (hotels, restaurants, entertainment venues), healthcare and financial services providers, and even manufacturing companies. What unites them is less about their product category and more about their digital maturity. These are companies that depend on their websites, apps, or digital platforms as primary customer touchpoints.

The maturity levels vary wildly. I see early-stage startups with 2-10 employees and pre-seed funding alongside established enterprises with thousands of employees and mature operations. However, the sweet spot appears to be growth-stage companies, those in the 11-200 employee range who have achieved product-market fit and are scaling. Many have Series A or B funding, suggesting they're past the earliest validation stage but not yet massive enterprises. Even the larger, established companies often emphasize innovation and digital transformation in their messaging.