Data analysis that tells you what to do next.
AI joins data from your shop, CRM and orders and answers the board in plain language: what is happening, why and what to do about it.
What is data analysis.
It means examining a company’s data to answer a specific question: what is happening, why, what will happen and what to do about it. With AI, analysis doesn’t stop at a chart. It joins several sources, looks for causes and gives a conclusion you can check in the data.
Four types of data analysis on one example
Online sales fell in October compared with September.
The product page takes 6 seconds to load instead of 3, and half of customers leave before buying.
If the page keeps loading this slowly, sales will fall in a similar way in November.
Speed up the product page and put the new account wizard on hold.
Data analysis vs business intelligence.
Business intelligence shows what is happening: reports and dashboards. AI data analysis goes further. It joins sources, looks for causes and suggests what to do.
Business intelligence
Shows what is happening
- dashboards and reports from one or several systems
- answers questions set in advance
- a person draws the conclusions
AI data analysis
Tells you why and what to do
- joins sales, operations and customer feedback
- answers questions asked in plain language
- gives a conclusion with a link to the data
If you already have dashboards, for example in Power BI, we work alongside them. You don’t need to change tools.
What we analyse.
We start from the questions the board answers on gut feeling today, and from the data you already have.
Sales and customers
What customers buy, who stops buying and why, which products drive the results.
Purchase path
Where customers drop out in the shop or the app and what stops them.
Operations
Order handling time, downtime, costs and their effect on sales.
Customer feedback
Tickets, complaints and reviews grouped into topics, with the number of cases.
Product
What customers use, what they don’t, and what is worth developing next.
Board report
Every week: what changed, why and what we suggest doing.
Questions first, then data.
- 01
Discovery Sprint
In one week we gather the board’s questions, check what data you have and where it lives, and pick where to start.
€1,900 · deducted from the build
- 02
Joining the data
We connect the sources and clean up the data, so numbers from different systems match.
- 03
Answers and reports
The board asks questions in plain language and gets a weekly report with conclusions.
- 04
Handover
Code, documentation and a trained team. The analysis stays with you, not with us.
Common data analysis mistakes.
A dashboard nobody looks at.
Instead of another chart, the board gets an answer and a conclusion about what to do.
Analysis without a question.
We start from the decisions that need making and only then look for data.
Numbers that don’t match.
The same metric in two systems gives two results. We clean up the data before analysing it.
A conclusion you can’t check.
Every answer links to the data it came from.
This is for you if
Companies come to us when the decision on AI is made and the plan isn't there yet.
- Your company has up to a hundred people and is growing.
- You’re hiring an AI person, or it is already part of someone’s role.
- You don't have an IT department, or your tech team is a few people.
- Your team has tried new tools, but the way you work hasn’t changed.
Let's talk.
Tell us what isn’t working today. We’ll tell you straight whether we can help and which model to start with.
- 30 minutes with a founder, not a salesperson
- A concrete answer on where to start
- No commitment
Typical reply within 24h.
Prefer to pick a time right away?
Questions about data analysis.
The questions we hear most before a rollout. If yours isn’t here, ask us on a call.
It means examining a company’s data to answer a specific question: what is happening, why, what will happen and what to do about it. There are four types: descriptive, diagnostic, predictive and prescriptive.
Business intelligence shows what is happening in reports and dashboards. AI data analysis joins several sources, looks for causes and suggests what to do, with a link to the data.
Data from your online shop, CRM, order system and ERP, customer service, product analytics and spreadsheets. We start with the data that answers the board’s questions.
Not always. With a few sources, joining and cleaning them is often enough. Whether a data warehouse makes sense for you is something we settle in the Discovery Sprint.
It can, which is why every answer links to the data it came from and can be checked. People make the decisions based on the analysis.
Before the rollout we agree what data we analyse, where it is processed and who has access to it. Personal data is handled in line with GDPR, and we write the rules down together with you.
We start with a Discovery Sprint: one week for €1,900, deducted from the build. After it you know which questions we will answer, from which data, and what it costs.