Your team is making decisions on data they do not trust.
Shopify says one thing, GA4 says another, and the ad platforms each claim credit for the same sale. Without a measurement framework, every budget meeting is a debate.
Tests run without statistical rigor
Peeking at results early, tiny sample sizes, no guardrails. You declare winners that are just random luck.
Your funnel leaks and nobody knows where
Conversion drops between steps go undiagnosed. Without friction analysis, you optimize the wrong pages and leave revenue on the table.
Marketing and Finance disagree on attribution
Every platform takes credit. Nobody reconciles. Budget decisions get made on whichever report reached the inbox first.
Measurement that replaces guesswork with evidence
Structured experimentation, friction analysis, and cross-channel reconciliation refined across 30 plus e-commerce brands.
A/B testing with proper methodology
One success metric defined upfront. Statistical guardrails. Sequential analysis. No peeking. No early calls.
Funnel analysis that finds real friction
Step-by-step drop-off diagnosis with heatmaps, session replay, and prioritized recommendations by estimated impact.
Cross-channel attribution clarity
GA4 attribution model audit, platform reconciliation, and multi-touch journey analysis. One source of truth for budget decisions.
KPI frameworks your team actually uses
Stakeholder-specific dashboards connected to BigQuery marts. Automated reports with trend analysis and anomaly flags.
Rigorous, defensible experimentation.
Platform-agnostic A/B testing methodology with proper success metric definition, sample size calculation, guardrails, and sequential analysis.
What you get:
- Success metric definition and guardrail setup
- Sample size calculation and power analysis
- Sequential testing to stop early when safe
- Platform-agnostic (AB Tasty, Kameleoon, ContentSquare, Optimizely)
Find the friction. Fix what matters.
Multi-step funnel optimization with heatmaps, session replay, and friction detection. Prioritized recommendations ranked by estimated revenue impact.
What you get:
- ContentSquare and Hotjar friction analysis
- Step-by-step funnel drop-off diagnosis
- Prioritized recommendations by estimated impact
- Cross-device journey mapping
One source of truth for budget decisions.
GA4 attribution model comparison, Shopify vs GA4 vs ad platform discrepancy resolution, and multi-touch reporting across channels.
What you get:
- GA4 attribution model audit
- Platform reconciliation (GA4 vs Shopify vs Meta vs Google Ads)
- Multi-touch journey analysis
- Channel performance benchmarking
Dashboards that answer questions, not raise them.
Define KPIs by stakeholder role, automate performance reports, flag anomalies, and deliver quarterly business reviews with actionable insights.
What you get:
- Stakeholder-specific KPI definitions
- Automated weekly and monthly reports
- Trend analysis with statistical context
- Quarterly business review framework
From hypothesis to confident decision.
Measurement audit
We assess your current testing, attribution, and reporting stack. What works, what is missing, what is misleading.
Experiment design
Hypothesis, sample size, duration, success metric, guardrails. Everything documented before execution begins.
Execution and analysis
Proper holdout, randomization, and monitoring. Statistical analysis with confidence intervals and practical significance.
Reconciliation
Cross-platform data aligned. GA4, Shopify, and ad platform discrepancies resolved. One set of numbers your team trusts.
Reporting and action
Insights translated into dashboards, budget recommendations, and a quarterly test calendar. Measurement without action is expensive curiosity.
“Structured experimentation and funnel optimization deployed for e-commerce brands, with attribution reconciled across GA4, Shopify, and ad platforms.”
Evidence, not opinions
Concrete deliverables your team can actually use. No slide decks, only tested artifacts.
Experiment Design
Hypothesis, sample size, duration, and success criteria documented before any test launches.
A/B Test Results
Statistical analysis with confidence intervals and practical significance assessment.
Funnel Audit
Friction map with prioritized optimization recommendations ranked by estimated revenue impact.
Attribution Report
Cross-platform comparison with reconciliation and budget allocation insights.
KPI Dashboard
Looker Studio performance dashboard connected to BigQuery marts. Stakeholder-specific views.
Measurement Roadmap
Quarterly test calendar with prioritized hypotheses and structured performance review framework.
12 measurement guides. 30 plus e-commerce brands optimized.
A/B testing frameworks, funnel optimization playbooks, and attribution methodology refined across real client engagements. Not theory from a blog post.
Is this the right engagement for you?
Best fit
- E-commerce brands running tests without rigor
- Teams where Marketing and Finance disagree on attribution
- Companies with multi-step funnels losing conversions
- Organizations needing structured performance reviews
Not ideal for
- Businesses with very low traffic (insufficient sample sizes)
- Companies not yet collecting reliable tracking data
Common questions
What testing platforms do you support?
AB Tasty, Kameleoon, ContentSquare, Optimizely, and custom setups. The methodology is platform-agnostic.
Can you reconcile our Shopify data with GA4?
Yes. Cross-channel reconciliation is a core service. We resolve discrepancies between GA4, Shopify, and ad platforms so your team works from one source of truth.
Do you build the dashboards too?
Yes. Looker Studio connected to BigQuery and dbt marts. Dashboards are part of the measurement stack, not a separate engagement.
Certified Analytics Engineer
DataBird 2025
GA4 Certified
GTM Server-Side Specialist
BigQuery Certified
Google Cloud
Enterprise Track Record
Carrefour. Airbus. Club Med. Ubisoft
Luxury and Premium Clients
Sezane. ByRedo. Valrhona
50 plus Client Engagements
Artefact. Sleekery. MadMetrics
Your team is making decisions on data they do not trust. Ready to fix that?
We audit your measurement stack, identify the gaps, and build the testing and reporting infrastructure your team actually needs.