Promarkia

AI data analysis

Turn raw marketing data into an analysis you can inspect

Analyze spreadsheets, CSV files, analytics exports, and business data to find patterns, build charts, test questions, and produce actionable findings.

Analyze your data

Direct answer

Promarkia's Data Scientist Squad works directly with supplied or connected datasets. It profiles data quality, performs calculations and comparisons, creates visualizations, explains methods and assumptions, and delivers reproducible findings.

Best for

Marketing operations, growth, finance, product, and analytics teams with raw data that needs investigation beyond a standard dashboard.

What this squad can do

  • Profile, clean, join, and analyze structured datasets
  • Calculate segments, cohorts, trends, correlations, and forecasts
  • Create charts, tables, and downloadable artifacts
  • Document assumptions, methods, limitations, and reproducible steps

What you get

  • Exploratory analyses
  • Charts and data tables
  • Segment and cohort findings
  • Reproducible notebooks or reports

From request to verified outcome

  1. Define the decision, unit of analysis, metric, and expected grain.
  2. Inspect schema, missing values, duplicates, and data quality.
  3. Choose the appropriate calculations and comparison design.
  4. Create interpretable charts and test the most important findings.
  5. Deliver conclusions, limitations, files, and reproducible steps.

Integrations

CSV and spreadsheet filesGoogle SheetsGoogle AnalyticsBigQueryPython analysis

Example prompts

  • Analyze this CSV for the strongest conversion patterns.
  • Build a cohort-retention analysis from these exports.
  • Create charts that explain which customer segments drive revenue.

Frequently asked questions

How is the Data Scientist different from Analytics?

Analytics focuses on connected marketing performance and reporting; Data Scientist handles deeper custom analysis of raw datasets and analytical questions.

Can it analyze CSV and spreadsheet files?

Yes. It can inspect and analyze structured files while documenting data-quality issues and methods.

Can it create charts?

Yes. Visualizations are selected to support the question rather than added decoratively.

Will it explain the method?

Yes. A useful result includes assumptions, transformations, limitations, and enough detail to reproduce or review the analysis.

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