Data Intelligence for eCommerce
Your data. Your next decisions.
We connect data, technology and AI to help marketing, eCommerce and management understand what is happening, recognise opportunities and decide how to act.
We design tailored systems: dashboards, conversational analytics and agents that bring information and operational proposals into your team's workflows.
Your view of the business.
For each role, a signal, a question for the data and a proposal to approve. Hover over the columns to see how the reading changes.
Illustrative example · no real data
eCommerce manager
Sales up. Margins below target.
- eCommerce manager asks“Where are we losing margin this week?”
- AI answersThe drop is concentrated on promoted products. Returns and acquisition cost need a closer look before changing investments.
- AI proposesCheck returns and acquisition cost on current promotions before changing investments.
Marketing
More traffic. Lower-value customers.
- Marketing asks“Which channels bring customers who come back?”
- AI answersCustomers acquired through discount campaigns repurchase less than others. Before moving budget, check whether the difference holds by segment and by period.
- AI proposesCompare channels by 90-day customer value before revising the budget.
Management
Revenue on track. Margin is not.
- Management asks“If we keep this pace, where will we close the quarter?”
- AI answersOn current data, revenue stays close to target; margin does not. The estimate is indicative and depends on the promotions planned for the coming weeks.
- AI proposesBring two scenarios to the next committee, with and without the end-of-quarter promotions.
From data to the next step.
- 01
Reliable data and shared KPIs.
Tracking, integrations and data quality: a common model for reading eCommerce, retail, marketing and internal systems.
Example · The same margin, with the same number, in every meeting.
- 02
Dashboards and conversational analytics.
Role-based views and questions in natural language: answers with sources, definitions and context, available where they are needed.
Example · “Which products have the most returns this month?” The answer is the list, with the orders behind it.
- 03
Proactive signals and scenarios.
Monitoring of anomalies and opportunities, contextual alerts and, where the data allows, forecasting models and scenario analysis.
Example · An alert on a margin drop in a category, alongside the promotions running in the same period.
- 04
Tailored agents and workflows.
Assistants connected to business systems that dig into signals and prepare actions, within defined rules, permissions and approvals.
Example · The agent prepares the promotions proposal and goes ahead only after sign-off from the person accountable.
Technologies with a clear role.
Measure, connect, read and activate: we choose components based on the decisions to be made, the data available and the client's systems.
- GA4
- Google Tag Manager
- CMP
- BigQuery
- Data Studio
- API
- LLM
- MCP
- n8n
Data-driven projects.
All projects
- UX Research
- UX/UI Design
- Shopify
YepponA Shopify Plus eCommerce site designed to handle large catalogues and complex processes.
- UX/UI Design
- Shopify
- Experience Management
Rigoni di AsiagoA D2C experience that showcases the brand and its relationship with customers.
- Content Creation
- Experience Management
Prolon+280% revenue with marketing automation.
Capability.
Measurement plan , GA4 , eCommerce tracking , Google Tag Manager , Consent Mode and CMP , Data quality check , BigQuery , Data Studio , KPI design , Executive dashboards