About me

I care about the moment analysis becomes a decision.

Commercial data analyst with three and a half years across e-commerce, marketplace and agency analytics. I build the reporting layer commercial teams run on — plan versus actual, price-volume-mix, margin, and channel P&L — and the controls that prove it reconciles: multi-source reconciliation and automated quality gates. I would rather hand over a number with its limits stated than a cleaner one without them.

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I build the bridge between a stakeholder question and a decision-ready data product. That means the metric definition, the data-quality checks, the model or experiment, and the final recommendation all need to agree.

My perspective

Commercial curiosity, analytical discipline.

My background spans digital marketing, e-commerce, and growth analytics, where imperfect tracking and fast operating decisions are normal. That experience shapes how I work as an analyst: define the metric before building the chart, preserve the business context, and make uncertainty visible.

I am comfortable moving between stakeholder language and implementation detail. One conversation may be about channel efficiency or margin; the next may be about data grain, leakage, a parallel-trends assumption, or a DAX measure that does not reconcile.

The best outcome is not the most complex model. It is a decision that is useful, explainable, measurable, and honest about what the data cannot prove.

Relevant Professional Experience

Commercial context behind the analytical work.

Jul 2025 - Dec 2025Laptop SGNVietnamese tech e-commerce retailer · 100K+ GA4 rows

E-commerce Analyst (Freelance)

Analysed 100,000+ GA4, acquisition-channel, product and transaction records in BigQuery, SQL and Excel to find where revenue was leaking: 21.5% of product-page visitors reached the cart, against 63.5% of checkout visitors completing — mid-funnel, not checkout.
Built the definition layer the reporting ran on — five documented tables across sessions, users, funnel events, transactions and segments, every column typed and every derived rule written, so conversion and revenue carried one definition in every report.
Built the customer view: recency, frequency and order-value segments with a named action each, and a derived cross-category browsing measure separating focused buyers from comparison shoppers — which set the repeat-purchase baseline at 36.4% second purchase, 17.8% third.

Apr 2024 - Sep 2025Golden Owl SolutionsSoftware agency and SaaS client work · 15 client businesses, 250K+ monthly users

Digital Marketing Analyst Project leadership

Turned open-ended questions from Marketing and Business teams across 15 client businesses and 250,000+ monthly users into measurable funnel, customer, and performance analyses.
Built the lead-quality reporting — roughly 3,100 leads a year by source, country, sales owner and status, of which close to a quarter were spam or unqualified — so every per-lead metric had been running on an inflated denominator.
Delivered 70+ analyses across GA4, Looker Studio and Search Console, including a rate-versus-mix decomposition showing one account's falling click-through rate came from impressions widening into lower-intent queries, not from declining performance.

Sep 2022 - Apr 2024Canawan GlobalEtsy/Amazon marketplace and dropshipping operations · 1,000+ SKUs

Digital Marketing Executive Project leadership

Owned the data loop for a 1,000+ SKU Etsy and Amazon catalogue: weekly product, acquisition and conversion reporting in GA4 and Looker Studio showing which products carried the revenue.
Automated WooCommerce workflows with n8n and Google Sheets; analyzed paid and organic performance that generated 114,000+ ad clicks at a 1.37% conversion rate and grew organic traffic by approximately 40% to 15,000 monthly visits.

Project leadership: I translated management goals into KPIs and milestones, allocated resources, trained and guided contributors, and owned project delivery. Professional reporting used GA4, Looker Studio and Excel; Power BI experience comes from independent projects.

30%less recurring reporting time

15businesses supported

70+analyses delivered

114K+ad clicks generated

What I can do

From source trust to a stakeholder decision.

Data and BI delivery, statistical inference, commercial analytics and leakage-controlled predictive work, rather than four separate jobs.

Data and BI

Build analytical foundations and self-service products across SQL, Power BI, Excel, Python, GA4, and Git.

SQL: T-SQL, DuckDB, PostgreSQL, BigQuery · Power BI: DAX, Power Query, data modelling · Excel: Power Pivot, Power Query, PivotTables · Python: pandas, NumPy, scikit-learn

Statistics and experimentation

Quantify uncertainty and test whether a measured difference supports a business decision.

A/B testing, pooled two-proportion z-tests, confidence intervals, p-values, relative uplift, Cramer's V association analysis, sensitivity analysis

Customer and commercial analytics

Diagnose lifecycle, concentration, efficiency, and unit economics across growth and e-commerce decisions.

Cohort retention, funnel analysis, RFM, K-means, elbow and silhouette selection, Gini and Lorenz analysis, forecasting, CAC/CIR, unit economics, KPI design

Predictive and decision analytics

Validate models at the real scoring moment and convert scores into practical targeting or review workloads.

Logistic regression, random forest, stratified cross-validation, leakage control, confusion matrix, precision/recall, ROC-AUC, PR-AUC, lift/capture, permutation importance, threshold simulation

Data delivery

Move from source data to governed metrics, decision products, and recommendations that stakeholders can audit and act on.

ETL/ELT, dimensional and star-schema modelling, decision marts, data contracts, reconciliation, dashboard design, executive reporting, stakeholder recommendations

Core stack

Tools are useful when the analytical contract is clear.

SQL & data modelling

T-SQL, DuckDB, PostgreSQL, BigQuery, dimensional and star-schema modelling, decision marts, data contracts

Business intelligence

Power BI, DAX, Power Query, dashboard design, executive reporting, source-to-output reconciliation

Python analytics

pandas, NumPy, scikit-learn, statistical inference, classification, cross-validation, model interpretation, automation

Excel & measurement

Power Pivot, PivotTables, Power Query, GA4, funnel and cohort analysis, forecasting, CAC/CIR and KPI design

Education & development

A business foundation strengthened by technical practice.

Bachelor of Business Administration, University of Economics Ho Chi Minh City (2018 - 2022)

TheHau Data Analytics Mentoring Program, selected 15-person cohort (Mar 2025 - Jul 2025)

IELTS Overall Band 7.5 (2022)

Contact

Open to Commercial Data Analyst and BI Analyst roles.

E-commerce, marketplace and retail. Ho Chi Minh City, on-site or hybrid.

Emailphanhoaithu114@gmail.com Phone0817 375 930 LinkedInphanhoaithu114 GitHubkath-pahotu