Human Behavior

What do they actually do

Human Behavior connects to your session replay source and uses AI to process every recording. It automatically detects and labels key moments like hesitations, rage clicks, and failures, turning qualitative video into searchable insights and behavioral metrics you can query and track (product tour, home page).

Product teams search behaviors in natural language, view aggregated KPIs and reports, cluster similar sessions, and triage issues with built‑in workflows or export insights to their stack (product tour). Pricing is sales‑led with data‑retention limits on PLG tiers (e.g., 90‑day retention) and enterprise options like custom integrations, project‑level models, and client‑specific security/retention policies (pricing, enterprise). Public materials name early customers (e.g., Delve, Conduit) and press notes a recent seed raise focused on product teams (YC page, TechCrunch).

Who are their target customer(s)

• Product managers at PLG/growth-stage SaaS companies: They can’t instrument every meaningful user action and spend weeks diagnosing funnel drop‑offs or feature adoption problems; they need behavioral signals without heavy engineering (product tour, PLG solutions).
• Growth/activation leads: They struggle to identify in‑product behaviors tied to conversion or PQLs and to validate hypotheses quickly; they need fast, evidence‑based signals surfaced from real usage (PLG solutions, product tour).
• UX researchers and designers: They must watch large volumes of session videos and manually label issues, which is slow and inconsistent; they need automatic detection of patterns like hesitations and rage clicks (home page).
• Engineering/platform teams at larger companies: They field constant requests for new instrumentation while ensuring security, compliance, and retention; they want enterprise controls and integrations that reduce instrumentation toil (enterprise, pricing).
• Customer Success / revenue operations at product‑led businesses: They lack timely behavioral evidence to flag churn risks or upsell opportunities and to tie support tickets to specific in‑app behaviors; they need aggregated KPIs and grouped problem sessions to prioritize outreach (product tour).

How would they acquire their first 10, 50, and 100 customers

• First 10: Founder‑led outreach to YC/network companies with short, paid pilots on a few critical funnels, delivering a prioritized report of labeled sessions and guaranteed insights (e.g., top 3 UX blockers) to convert pilots into logos.
• First 50: Open self‑serve via integrations with major session‑replay sources and marketplaces so PMs can connect data and see auto‑labeled moments in minutes; pair with tactical content and targeted outreach to growth teams, plus onboarding templates and automated reports to drive upgrades and referrals.
• First 100: Run a hybrid motion with a small SDR/AE team for focused outbound into growth‑stage SaaS, standardized paid pilots that scale to enterprise deals, and partnerships/co‑marketing with replay/analytics vendors; productize enterprise controls and use quantified pilot outcomes to justify pricing and expansions.

What is the rough total addressable market

Top-down context:

Session‑replay software is estimated at about $460M in 2025, while broader Digital Experience Monitoring is several billion (≈$3.4B in 2024) and growing, placing the combined opportunity in the low‑to‑mid single‑digit billions today (FMI, StellarMR).

Bottom-up calculation:

Assuming a few thousand target PLG/mid‑market/enterprise SaaS buyers globally and enterprise ACVs around $25k–$50k (benchmarked to LogRocket and FullStory deal data), scenarios range from tens to several hundred million ARR (e.g., 3,000 × $40k ≈ $120M) (Statista, Exploding Topics, Vendr LogRocket, Vendr FullStory).

Assumptions:

• A sizable subset of global SaaS companies fits PLG/mid‑market/enterprise profiles with active product teams.
• Enterprise ACVs for AI‑labeled session replay/behavioral analytics align with $25k–$50k based on comparable vendors.
• Buyers view AI labeling + behavioral search as a complement/upgrade to existing replay/analytics rather than a pure replacement.

Who are some of their notable competitors

• FullStory: Digital experience analytics with session replay and product insights used by product and growth teams; strong enterprise presence (site).
• LogRocket: Session replay plus performance monitoring and product analytics, popular with engineering and product teams (site).
• Contentsquare: Enterprise experience analytics including replays, heatmaps, and journey analysis; notable at large scale (site).
• PostHog: Product analytics platform with session replay and self‑hosted options appealing to developer‑led teams (site).
• Hotjar: SMB‑oriented session replay and feedback tools used for quick UX insights and basic behavior analysis (site).