Partner · Commerce & Analytics
Product-led growth measured on PostHog.
BRCG implements and runs PostHog for product-led SaaS and consumer apps — event taxonomy design, Feature Flags + Experiments, Session Replay, Cohorts, SQL Insights, and LLM observability. Self-hosted or PostHog Cloud, our choice based on your data residency and scale.
PostHog partner agency
Product-led SaaS and consumer apps that need event analytics, feature flagging, A/B testing, session replay, and LLM observability in one open-source-rooted stack.
What we ship on PostHog
Capabilities.
Production-grade PostHog work, not theoretical knowledge. Each line below maps to programs we've shipped — across the platform's actual surface area, not the marketing site's.
Implementation
Event taxonomy + autocapture.
Event taxonomy design (named events vs. autocapture trade-off). PostHog SDK installed across web, mobile, server. Identity stitching for cross-device sessions.
Feature Flags
Feature Flags + Experiments.
Flag-based gradual rollouts. Experiments with statistical-rigor gating and sequential-safe stopping rules. Multi-arm tests and feature flag cohorts.
Session Replay
Session Replay + Heatmaps.
Session Replay for funnel debugging — see why users dropped off PDP, cart, or onboarding. Heatmaps for static UX review. PII scrubbing rules configured.
Cohorts + SQL
Behavioral cohorts + SQL Insights.
Behavioral cohorts (e.g., 'users who completed activation but never returned'). SQL Insights for custom queries beyond the UI.
LLM observability
LLM observability (Q4 2025).
PostHog's LLM observability product — tracking prompts, outputs, latency, cost across your AI surfaces. Useful for AI agent rollouts in production.
Surveys
In-product surveys.
NPS, CSAT, and custom in-product surveys triggered by behavioral events. Results piped into PostHog cohorts and downstream tools.
PostHog · in production
Fluent in PostHog.
PostHog's proprietary surface area, defined — the primitives we ship in every day, not vocabulary we picked up reading the docs once.
Autocapture
Automatic event capture (clicks, page views) without named-event instrumentation
Feature Flag
Boolean or multivariate flag that gates a feature for a cohort
Experiment
Statistically-rigorous A/B or multivariate test built on Feature Flags
Session Replay
Recording of a user session for funnel and bug debugging
Cohort
Dynamic or static group of users defined by behavior or properties
SQL Insights
Custom SQL queries inside PostHog (beyond the visual builder)
LLM Observability
Tracing prompts + outputs + cost + latency across AI surfaces (Q4 2025)
PostHog Cloud / Self-hosted
Two deployment options — Cloud (managed) or Self-hosted (your infra)
How we work
Phased delivery.
Each phase has a defined output. Nothing ships without one.
Week 1-2
PostHog audit.
Event taxonomy review, SDK install health, Feature Flag usage, Experiment rigor, Session Replay PII configuration.
Week 3-5
Taxonomy + SDK.
Event taxonomy rebuild. SDK install across surfaces. Identity stitching. Cohort migration.
Week 5-8
Experiments + flags.
Experimentation infrastructure live. Statistical-rigor gating in place. Sequential-safe stopping rules documented.
Month 3+
LLM obs + iterate.
LLM observability deployed if applicable. Quarterly taxonomy + cohort review. Weekly readouts.
Proof
It works on PostHog.
FAQ
Questions we hear.
Is BRCG a PostHog partner?
Yes. BRCG implements and runs PostHog for product-led SaaS and consumer apps. We handle event taxonomy design, Feature Flag + Experiment infrastructure, Session Replay, and LLM observability.
When does PostHog make sense vs. Amplitude or Mixpanel?
PostHog wins when you want product analytics + feature flags + A/B testing + session replay + LLM observability in one stack — and the open-source roots matter (data ownership, self-hosting option). Amplitude wins on aggregate cohort reporting and the Tracking Plan governance product. Mixpanel sits in between.
Can BRCG help with event taxonomy design?
Yes. Event taxonomy is the foundation — if it's wrong, every downstream chart and cohort is wrong. BRCG designs named-event taxonomy (vs. relying on autocapture alone), documents it as a tracking plan, and enforces it via PR review in your codebase.
Does BRCG handle Experiments and feature flagging on PostHog?
Yes. We implement PostHog's Experiments product with statistical-rigor gating (minimum sample size, sequential-safe stopping rules, multiple-comparison corrections where it matters). Feature flag rollouts are tied to cohorts and tracked in the experiment dashboard.
What about PostHog's LLM observability?
PostHog's LLM observability (Q4 2025) traces prompts, outputs, latency, and cost across your AI surfaces. BRCG implements it for clients rolling out AI agents in production — useful for prompt regression detection, cost monitoring, and output quality review.
In their words
What the teams say.
BRCG operates like they're part of our team. Senior people doing the actual work, fast turnarounds, and they understand the complexity of our scale without needing hand-holding.
Director of CRM
Discord
Discord
Not sure if PostHog is right for you?
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