A Wolf in Sheep's Clothing. Enterprise Power. Medium-sized Enterprises Budget.

The system runs entirely on BigQuery – no extra BI platform, no separate license.

It connects to the sources you're probably already using: GA4, Google Ads, Meta, TikTok, or other ad platforms - like affiliates. Plus your store (Magento, Shopify, or a custom build), the sales database – this is where the real strength for profit analysis lies –, product and returns data.

An AI Agent takes over the analysis that would otherwise require your own data analyst. Typically live in a few weeks instead of months, because it connects to systems you already use – not a completely new setup.

Talk to your data, instead of staring at rigid dashboards.

Revenue is not profit.

Most dashboards show revenue, sessions, ROAS. What's missing: the margin after cost of goods, discounts, and shipping. I connect your advertising data with the real costs from your store – so you see what's actually left over, not just what comes in.

The AI Agent automatically flags it when margin starts to slip – before you even have to go looking. In a chat, or as a morning briefing by email.

Examples: Net revenue, gross margin, profit after vouchers – at a glance, instead of pieced together across three Excel tabs.

Which product actually turns a profit?

Some products generate a lot of revenue but barely any margin – others are quiet. Your real profit drivers, without anyone noticing.

The AI Agent breaks down every product to material, labor, and overhead costs – just ask which product is currently costing you margin instead of bringing it in.

Use cases: Best-sellers that barely generate gross profit – spotted before they get the next sale campaign's budget.

Which campaign actually contributes, nobody else will tell you.

Meta, Google, and GA4 each report their own, flattering number – and every platform has an incentive to make itself look good. Only when measured against your real store revenue does it become clear which campaign and ad group is actually pulling its weight.

The AI Agent answers that in one sentence, without you having to dig through spreadsheets yourself.

Examples: Retargeting performs far better than prospecting, brand search far better than demand gen – differences that get lost in the platform report.

Do you know your customers, or just their orders?

Without segmentation, every customer is worth the same – but they're not. From your order data, an AI automatically builds a segmentation model: by purchase behavior, basket value, and category preferences.

The AI Agent uses these segments directly: ask it which customers are about to churn, or which segment has the highest customer lifetime value – the answer comes in seconds, not after a manual data analysis.

Use cases: Segments like Champions, At Risk, or New Customers – always up to date, no manual upkeep. Which weekday and time of day customers buy from which category.

Personalized email marketing starts with segments that don't exist yet.

Without segmentation, every newsletter campaign stays a mass email. The same model from above produces a ready-to-use feed that you load into your existing email tool – the AI keeps it continuously up to date, without you having to maintain it manually.

The AI Agent goes even further: ask it which segment responds best to which messaging, or which campaign is due next for which group – you don't have to compile the analysis yourself.

Examples: Category affinity per customer, preferred weekday and time – ready to push to your newsletter provider.

Vouchers and discounts are repeat offenders when it comes to your margin.

Discount campaigns bring in revenue and feel like success – orders go up, the team is happy. But these are usually exactly the campaigns that hit your margin hardest, because the discount comes straight out of gross profit.

The AI Agent recognizes the pattern automatically: it detects when a sale campaign brings in revenue but gross margin collapses over that period – before it shows up in the quarterly results.

Use cases: A sale campaign that pushes gross margin from around 52% down to around 30% – caught early, not only in the annual accounts.

The solution: Your own data warehouse. Your own data analyst.

I make your important data understandable and actionable, so that AI Agents and interactive dashboards help you make better decisions. The data warehouse is built in your own BigQuery project – it belongs to you, not me.

Whether it's revenue, margin, campaign performance, or customer behavior – you don't need to know which table or dashboard has the answer. Just ask, and the AI Agent delivers it, straight from your real data.

Use cases: Management reports at a glance, KPI dashboards without an IT ticket, all channels in one place instead of five export spreadsheets, trends and outliers caught before they show up in the month-end close.

GDPR-ready for the data protection officer. Even if he happens to peek around the corner.

Your data warehouse is built in your own BigQuery project in the EU – your data stays with you, not with me, and you always have full control over it.

Data protection, data processing agreements, data minimization, and deletion concepts are built in from the start, not bolted on afterward.

Use cases: Pseudonymization, deletion concepts based on retention periods, role-based access rights, EU data centers, and a data processing agreement (DPA).