Data analytics & AI

Data analytics — decide on data, not gut feeling

Predictive models, automated reports and visual dashboards. I turn your data into strategic decisions — not just pretty charts.

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What I offer

You have the data. The question is whether you're getting the most out of it. AI analytics reveals patterns and trends the human eye misses.

Predictive models

Forecasting sales, customer churn, demand or cash flow. The AI model learns from your historical data and predicts what's coming.

Automated reports

Daily, weekly or monthly reports build and send themselves. No manual Excel copy-pasting — data flows automatically.

Visual dashboards

Interactive dashboards with key metrics in real time. For management, sales, marketing or operations.

Anomaly detection

AI watches your metrics and flags unusual values — a drop in orders, a spike in complaints, a cost swing. Before you'd notice yourself.

Customer segmentation

AI groups customers by behaviour, value and potential. Targeted communication instead of mass e-mails = higher conversion.

Market analysis

Competitor monitoring, price trends, market opportunities. Public-source data processed by AI into clear insights.

Who data analytics is for

E-commerce & retail

Demand forecasting, stock optimisation, customer behaviour analysis, personalised offers. Data-driven revenue growth.

SaaS & tech companies

Churn prediction, product analytics, cohort analysis, MRR forecasting. The metrics investors and boards want to see.

Manufacturing & logistics

Predictive machine maintenance, supply chain optimisation, quality control. Less downtime, lower costs.

Financial services

Client scoring, fraud detection, risk analysis, regulatory reporting. Precise data for precise decisions.

What you get

The technical solution

  • A data pipeline (collection, cleaning, transformation)
  • Predictive ML models trained on your data
  • Interactive dashboards (Metabase, Looker or custom)
  • Automated reports with distribution
  • An API to connect your systems

The results

  • Decisions based on data instead of intuition
  • Prediction accuracy tested on data held out from training
  • Hours saved on manual reporting
  • Hidden trends and opportunities uncovered

Sound interesting?

Describe your problem — I'll design a solution and calculate the ROI. The 30-minute call is free and non-binding.

Illustrative example: measuring analytics impact

These figures are illustrative, not a client's result. They show what to measure before and after a change; a difference alone does not prove its cause.

Before (assumption)
CAC €33
Churn 5% / month
Starting metrics for comparing campaigns and customer departures.
After (assumption)
CAC €24
Churn 3.5% / month
Compare measured values with seasonality, budget and other changes.
Difference in this example
−€9 CAC
−1.5-point churn
CAC fell by about 27%. Return can only be calculated with actual revenue and costs.

Frequently asked questions

Did not find your answer? Try the full FAQ.

Yes, Excel is a great start. I work with data in any format — Excel, CSV, databases, APIs, Google Sheets. What matters is the data itself, not the format.

It depends on the goal, quality and variability of the data. In a pilot, I compare a simple baseline with a model on previously unused data. If the evidence is too thin, I'll recommend collecting more data or starting with a dashboard.

Of course. Dashboards are web-based — a link is all it takes. I set up access rights so everyone only sees the data relevant to their role.

A dashboard may take around 2–4 weeks; a predictive model with data preparation and validation may take 4–8 weeks. The schedule depends on data access and quality and is confirmed in the proposal. We begin with a pilot.

No. I handle the data pipeline, dashboards and models, then train your team to interpret the outputs. The first 30 days of support are included; further changes can be agreed separately.

A basic solution with automated reports and a dashboard sits in a different bracket from predictive modelling. Pricing follows data scope and the number of metrics you want to track — you'll get an exact quote after the intro consultation.

Ordinary cash-flow, demand or CAC forecasting is usually not high-risk; classification depends on the system's specific purpose. High-risk uses include certain hiring and creditworthiness decisions. If you use an AI system, support the AI literacy of people working with it on your behalf as its provider or deployer. See this guide.

Related reading

Data is what gives AI real context

In this article I show how AI is changing the way small companies work — and why it often starts with a better grip on data, reports and decisions.

Read the article

Got data but no insights?

Tell me what data you collect and what you'd like to know. The 30-minute call is free and non-binding.