You're drowning in data, starving for insight.
You have GA4, spreadsheets, BI tools, maybe a CDP—but when leadership asks a sharp question, it still takes days to answer.
Analyze Pillar · Decision Intelligence
You don't need more reports—you need sharper decisions.
Analyze is where clean data becomes direction. We design models, dashboards, and narratives that help your team answer hard questions quickly—and align around what to do next.
- Clear visibility into funnels, cohorts, LTV, and channel profitability.
- Dashboards that tell a story—not just visualize a data dump.
- A decision cadence: what you review weekly, monthly, and quarterly.
Built for teams that are done guessing: growth, product, finance, and leadership.
From Data Chaos → Decision Clarity
Today
- 5–6 dashboards, nobody fully trusts any of them.
- Key questions answered via one-off exports.
- Weekly meetings stuck on “what happened?”
With Analyze
- One source of truth for revenue and performance.
- Dashboards designed around the questions you ask.
- Meetings focused on “what we're doing next.”
Visibility
Clear views of funnels, cohorts, and margins.
Alignment
Shared definitions so teams stop arguing over metrics.
Momentum
Decisions turn into experiments, not endless debates.
The Cost of Shallow Analytics
When analytics is just "reporting," you move slower than you should.
You don't need more charts. You need a small number of views that tie directly into how you grow, retain, and monetize customers. Analyze is where we build that layer.
Every team has their own "truth."
Marketing, product, and finance pull different numbers for the same metric. Nobody agrees on what "good" looks like.
Dashboards are pretty, but not persuasive.
You have charts and filters—but they don't ladder into clear decisions, tradeoffs, or priorities.
There's no decision cadence.
Reviews are reactive. You're pulled into fire drills instead of consistently spotting leading indicators.
What Analyze Delivers
A decision layer built on top of your data foundation.
Analyze turns the tracking foundation from Track into models, dashboards, and rituals that consistently push the business forward.
Clarity
A small set of core dashboards that answer 80% of your recurring questions without extra digging.
Consistency
Metric definitions, filters, and segments aligned across teams and tools so decisions use the same baseline.
Speed
Questions that used to take days of exports answered in minutes from a single, trusted place.
Narrative
Insights framed in plain language so stakeholders understand not just what changed, but why it matters.
Analyze Services
Services inside the Analyze pillar.
We meet you where you are: from “we have GA4 but no real insight” to “we need a fully modeled warehouse and board-ready views.”
KPI & Metric Architecture
Agree on what matters before visualizing anything.
- Define North Star metrics and supporting KPIs by team.
- Standardize metric formulas, filters, and time windows.
- Create metric dictionaries accessible to all stakeholders.
- Document ownership and review cadence for each KPI.
Funnel & Journey Analytics
See where customers actually get stuck—not just who converts.
- Acquisition → activation → retention funnel design.
- Multi-step funnels across web, app, and CRM.
- Drop-off and time-to-convert analysis by segment.
- Prioritized list of friction points with potential impact.
Cohort & Retention Modeling
Understand which customers stay, pay, and grow over time.
- Cohort definitions by signup date, channel, or product.
- Retention curves and payback period analysis.
- Churn signal identification and early-warning indicators.
- Segment-level LTV and margin visibility.
Channel & Profitability Analytics
Move beyond last-click into real contribution and tradeoffs.
- Channel mix and marginal ROI analysis.
- CAC, LTV, and payback period wiring into your stack.
- Attribution views aligned with how you actually buy media.
- Budget scenario modeling with clear assumptions.
Executive & Team Dashboards
One view for the boardroom, deeper views for operators.
- C-level summary dashboards focused on trends and risk.
- Team-level views for growth, product, and lifecycle.
- Alerting patterns for leading indicators and anomalies.
- Dashboard hygiene: fewer tabs, cleaner views, clearer stories.
Data Storytelling & Enablement
Help your team read, challenge, and use the data you have.
- Recurring insight reviews with your leadership team.
- Playbooks on how to interpret key metrics and charts.
- Template narratives: “What happened, why, what we’ll do.”
- Training so non-analysts can self-serve safely.
Data Warehouse & BI Alignment
Connect GA4 and product data with finance-grade numbers.
- Modeling GA4 + backend + CRM in a warehouse (e.g. BigQuery).
- Looker/Power BI/Tableau views aligned with GA4 and Ads.
- Data quality checks for joins, duplicates, and gaps.
- Roadmap for evolving from scrappy to scalable analytics.
Experimentation-Ready Measurement
Set the stage for Optimize: tests that actually read correctly.
- Baseline data stability checks before experimentation.
- Guardrail metrics definition and monitoring.
- Test readout templates and standard report structures.
- Handover for experimentation roadmap in Optimize.
Track → Analyze → Optimize
Track makes the data reliable. Analyze turns it into direction.
Analyze sits between instrumentation and experimentation. It's where we agree on what matters, how we'll read it, and how it feeds into marketing, product, and strategy decisions.
Track
Wire the events correctly.
Clean, consistent measurement across GA4, Ads, CRM, and product—your data foundation.
Analyze
Make sense of the noise.
Models, dashboards, and cadences that help you see what's working, what's not, and why.
Optimize
Act on what you've learned.
Experiments, campaigns, and product changes prioritized and measured using the Analyze layer.
Selected Analyze Engagements
Where we've turned noisy data into clear direction.
Different industries, same pattern: lots of data, not enough signal. Analyze is where we build the views and models that unlock confident decisions.
E-commerce · Revenue and Margin Intelligence
Problem: The team could see topline revenue and ROAS, but had no clear view on profit after discounts, fees, and returns.
What we did: Modeled net revenue and margin by channel and cohort, blending GA4, Shopify, and finance data into a single view.
Impact: Reallocated spend toward channels with real margin; cut wasted budget without hurting growth.
SaaS · Activation & Retention Analytics
Problem: Signups looked healthy, but activation and long-term retention were inconsistent and hard to diagnose.
What we did: Defined activation events, built cohort retention views, and tied usage patterns to upgrade behavior.
Impact: Product and growth teams had a shared activation target and clear levers to pull when cohorts underperformed.
Healthcare · Capacity & Demand Insight
Problem: Leads and appointments were tracked, but there was no combined view of demand, capacity, and show rates.
What we did: Joined marketing, booking, and attendance data into dashboards that showed demand vs availability by region.
Impact: Marketing spend and staffing were aligned; fewer gaps in schedules, fewer frustrated patients.