About
PostHog
PostHog has evolved from a single-product analytics tool into a multi-product developer platform designed to help engineering teams build, ship, and improve software without relying on fragmented tooling. What began as product analytics has expanded into a tightly integrated system that connects feature flags, session replay, error tracking, experimentation, and user feedback, all anchored to a shared event-based data model.
Mine Kansu, who leads Revenue Operations at the company, has operated inside that evolution firsthand. “We started as a product analytics company,” Mine recalls. “Now we’re a platform with more than 15 products, all centered around helping product engineers build better products more easily.”
At the core of the platform is an event-based architecture that lets teams define the behaviors that matter, from onboarding flows to feature adoption, and act on them in real time. “It’s a system in which everything lives in one place,” she says. “You’re not stitching together different platforms for different parts of the same workflow.”
That same architectural philosophy of centralizing signal and reducing fragmentation has shaped more than just the product. As Mine explains, the company applied the same thinking to go-to-market operations, where knowing when and how to engage customers became as critical as understanding their behavior inside the platform.
A product-led model that depends on timing
PostHog is deeply product-led. Most users discover the platform, sign up, and begin using it without ever speaking to Sales. “We don’t do outbound,” Mine explains. “We primarily sell to engineers, and they don’t want to sit through traditional sales calls. So dev-tool culture shapes how we operate a go-to-market motion.” Growth comes from self-serve adoption and expansion. But that model creates a structural risk: engagement that happens too late.
In a purely self-serve environment, customers can configure the product imperfectly, miss optimization opportunities, or scale usage without fully understanding cost implications. Revenue Operations may have thousands of active accounts, but the harder question is which ones are entering a phase where guidance would add value. By the time frustration surfaces, the relationship is already strained. “At that point, it may be too late,” Mine adds. “Even if the issue is solvable—maybe it’s a configuration problem that would reduce costs significantly—the moment for intervention has passed.”
The challenge is recognizing when engagement will be welcomed early enough to guide rather than repair. That is where Harmonic enters the picture.
From lagging revenue to leading momentum
To solve the timing problem, Revenue Operations needed earlier indicators of organizational change. Prior to Harmonic, PostHog relied on traditional enrichment tools to contextualize accounts. “We were using Clearbit, and I built additional workflows in Clay,” Mine recalls. “But because our customer base is heavily startup-focused, many traditional data sources just didn’t provide the depth or accuracy we needed.” The team could see who their customers were, but it was harder to detect when those customers were entering a phase of meaningful growth.
“If you think about the traditional signal—a customer signs up and eventually starts spending a lot—that pattern is inherently lagging,” Mine explains. “By the time usage ramps, they’ve already instrumented events, rolled the product into their workflows, and made architectural decisions. At that point, we’re reacting rather than guiding.”
Harmonic provided startup-native signal density aligned with PostHog’s ICP. Its continuously refreshed dataset spans more than 30 million companies and 190 million people profiles, automatically surfacing headcount trends, hiring velocity, funding activity, and other indicators of organizational expansion. “For example, if an engineering team grows 50% in three months,” Mine says, “that’s a strong signal they’re about to invest more heavily in tooling like ours.”
Crucially, Harmonic doesn’t prioritize based on a single metric. Its AI-agent, Scout, can now combine growth trends, sector alignment, founder background, network signals, talent density, and recent activity into a composite view of startup momentum, tailored to your exact preference. That composite layer is evaluated alongside PostHog’s internal product, billing, and engagement data. “When internal engagement aligns with external company momentum,” Mine adds, “we have much higher confidence that outreach will be timely and useful.”
Now, rather than manually monitoring hundreds of startup accounts, the team prioritizes accounts based on growth inflection. Instead of waiting for churn risk to surface, PostHog can engage customers while expansion is still forming.
Harmonic as a retention lever
Retention in a product-led developer platform rarely fails because a competitor wins a head-to-head deal. More often, it breaks down through misconfiguration, underutilized features, or cost structures that no longer match how a team is actually using the product. As usage scales and the tool becomes embedded in workflows, small implementation gaps compound. Months later, a billing spike surfaces, and what was once aligned now looks inefficient.
“But when we engage customers at the right moment, retention improves dramatically,” Mine says. For PostHog, that “right moment” isn’t defined by revenue alone. It’s defined by infrastructure change. Rapid engineering hiring, expanded product activity, or new technical leadership often signal that a company is rethinking how it builds and ships. That’s when configuration quality, cross-product alignment, and cost architecture matter most.
Harmonic allows Revenue Operations to see those shifts early enough to influence them. Sales and Customer Success step in while teams are actively building, focusing on implementation integrity, broader product fit, and usage patterns that will scale cleanly. Conversations are grounded in context: how the company is growing, how its engineering team is evolving, and how PostHog fits into that trajectory.
“We’ve absolutely seen retention improve since structuring the team around these signals,” Mine adds. “Our retention is top-quartile, and the impact has been clear internally.”
Harmonic as a small-team force multiplier
PostHog operates with a deliberately lean team. “We’re not scaling the headcount dramatically,” Mine says. “It’s very much PLG.” That structure places a premium on operational efficiency. Signal detection must live inside the workflow.
Rather than asking reps to check another dashboard, PostHog integrates Harmonic directly into its systems. Enrichment runs continuously across all accounts, and structured signals flow into Salesforce via the API, syncing into tools like Vitally for customer success. “We pipe the data straight into Salesforce,” Mine explains. “By the time someone opens an account record, the context is already there.”
That embed changes the operating model. Prioritization becomes systemic rather than manual. Reps don’t need to hunt for startup momentum or cross-reference tools. The intelligence surfaces automatically inside the systems they already use.
The impact is structural: small teams gain continuous visibility into startup momentum without adding process overhead or expanding headcount. As such, Harmonic has become part of PostHog’s operating foundation. “If we lost it,” Mine says, “we’d have to rethink how we source and maintain that level of startup intelligence. Replacing it would be hard.”
Clarity as competitive advantage
Mine sees a broader shift underway in modern product-led companies. “Small teams can do much more than they used to,” she says. “But that only works if you know where to focus.”
For PostHog, startup momentum is no longer something inferred after the fact. It’s visible in real time and embedded directly into the company’s operating systems. Accounts are prioritized based on growth inflection rather than lagging revenue signals. Engagement aligns with expansion instead of reacting to churn.



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