We implement Amplitude with a clean, deliberate event taxonomy — so funnel, retention, and cohort analysis actually reflect what your product does, not a guess.
Different teams log the same action under different event names, fragmenting funnel and retention analysis that should be one clear signal.
Hundreds of granular events instrumented with no clear analysis plan, producing noise instead of actionable insight.
Event definitions drift as the product changes without a designated owner, leaving old events stale and new features untracked.
Behavioral cohorts (power users, at-risk churners) identified in Amplitude but never connected to Braze or another tool to actually act on them.
Attributes that describe the user (plan tier, signup date) logged as event properties instead, making cohort analysis unreliable and duplicative across every event.
Development and QA testing events flowing into the same project as real user data, silently skewing funnel and retention numbers.
We design a consistent, documented event taxonomy — the single most important factor in whether your Amplitude analysis is trustworthy.
We build the funnel, cohort, and retention analyses that actually answer your team's real product questions.
We connect Amplitude to Snowflake or Databricks — exporting behavioral data for broader analysis, importing warehouse data to enrich profiles.
We connect Amplitude-defined behavioral cohorts to Braze so insight actually triggers campaigns, not just populates a dashboard.
We audit tracking plan drift and event quality over time — product changes constantly, and tracking needs to keep up.
The distinction that determines whether cohort analysis actually works.
plan_tier: "pro" | signup_date: "2026-03-14" | company_size: "50-200"
event: "Report Exported" -- format: "pdf" | report_type: "quarterly"
Getting this split right up front is what makes "show me retention by plan tier" a five-second query instead of a data cleanup project.
Amplitude defines who and why; Braze handles what and how — insight that actually reaches the customer.
We implement Amplitude alongside Braze, Snowflake, and Databricks — so behavioral insight actually drives engagement, not just dashboards.
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Founder & CEOOur Amplitude Analytics guide explains what the platform does and how it compares to alternatives. This page covers the actual implementation service — event taxonomy design, funnel setup, and connecting Amplitude to your broader data stack.
Event taxonomy design, without question — deliberate, consistent event naming and definition across your product determines whether every subsequent funnel, retention, and cohort analysis is trustworthy. This is the work most commonly under-invested in.
Yes — we set up bidirectional sync where relevant: exporting Amplitude event data to Snowflake or Databricks for broader analysis, and importing warehouse data (like CRM fields) into Amplitude to enrich user profiles beyond what product events alone capture.
Amplitude-defined behavioral cohorts — power users, at-risk churners, feature adopters — can be synced to Braze so that insight actually triggers real engagement campaigns rather than sitting in a dashboard nobody acts on.
Yes — an audit often finds inconsistent event naming, unused tracked events, and tracking plan drift as the product has evolved. We produce a prioritized list of fixes rather than a full rebuild when the underlying instrumentation is salvageable.
A focused event taxonomy design and core funnel setup can take a few weeks. More comprehensive implementations across a larger product surface with warehouse and Braze integration take longer.
Ideally a single designated owner internally — often a product analyst or PM with analytics responsibility — rather than leaving event definitions to whichever engineer builds a given feature. We can help establish this ownership structure as part of the engagement.
No, it has equally mature support for web product tracking, and most implementations track behavior across both web and mobile together for a complete cross-platform picture.
Yes — tracking plans need periodic review as your product evolves, and we offer ongoing governance to catch drift before it undermines trust in the data.
Reach out for a free assessment — we'll look at your current tracking setup (or lack of one) and give you an honest scope and recommendation.
A user property describes something true about the person regardless of what they're doing right now -- their plan tier, signup date, company size -- and persists across every event they trigger. An event property describes something specific to a single action -- which report format they exported, which button they clicked -- and only applies to that one event. Confusing the two is one of the most common taxonomy mistakes and makes cohort analysis unreliable.
No -- we set up separate projects or environment tagging so development and QA testing never contaminates real user funnel and retention numbers. This seems obvious in principle but is a surprisingly common gap in existing implementations we audit.