02
Customer Intelligence
Segmentation, repeat behavior, retention, churn, cohorts and pattern discovery in customer behavior.
Business Analytics & Growth Intelligence
From business data to decisions that create growth
DiLoLid turns internal business data into a structured intelligence layer: what is happening, why it is happening, where the risks are, and which opportunities should be tested first.
Business DataAnalyticsOpportunity DiscoveryDecision Support
DiLoLid Intelligence Flow
01
Business DataSales, customers, products, CRM, ERP, Excel, SQL
↓
02
AnalyticsKPIs, cohorts, retention, churn, profitability
↓
03
Opportunity DiscoveryGrowth areas, anomalies, risks, hidden patterns
↓
04
Decision SupportPriorities, scenarios, next actions, experiments
Not justDashboards
ButBusiness Intelligence
Not justReports
ButGrowth Opportunities
Our first commercial product
DiLoLid Business Analytics & Growth Intelligence
At launch, we deliberately focus on one commercial direction: analyzing internal business data, identifying the drivers behind performance changes, and turning findings into prioritized growth opportunities.
01
Business Analytics Audit
An initial assessment of data and business performance: what can already be seen, which questions can be answered, and where the strongest potential lies.
Learn more →03
Revenue & Profitability Intelligence
Revenue, margin, products, categories, concentration and the factors shaping economic performance.
04
Growth Opportunity Discovery
Identification of segments, channels, products and scenarios where the data points to growth potential or hidden reserves.
05
KPI & Decision Reporting
Not just reporting, but management metrics and explanations designed to support better decisions.
06
Data Preparation & Automation
Preparation and standardization of Excel/CSV/CRM/BAF/SQL data for repeatable analysis and automated analytics.
DiLoLid Intelligence System
We are building decision logic, not a collection of reports
Analytics should not stop at “what happened?”. It should move toward “why did it happen?”, “where is the opportunity?” and “what should we do next?”.
01
Descriptive
What is happening in the business right now?
02
Diagnostic
Which factors explain changes in performance?
03
Opportunity
Where are the growth areas, hidden reserves and risks?
04
Decision
Which actions or experiments should be prioritized?
Delivery workflow
From a raw file to a management hypothesis
01
Acquire
Excel, CSV, CRM, ERP/BAF, SQL or other business sources.
02
Validate
We check structure, quality, completeness and consistency.
03
Analyze
We build KPIs, cohorts, segmentation, retention, profitability and other analytical views.
04
Discover
We identify anomalies, risks, drivers and growth opportunities.
05
Decide
We formulate priorities, next actions and questions for experiments.
Entry product
Business Analytics Audit
A starting point for companies that already have accumulated data but do not yet have a full data team or a systematic analytics function.
Data structure and quality review
Key KPIs and trends
Customer / product / revenue analytics
Retention / churn / repeat behavior
Anomalies, risks and weak signals
5–10 growth opportunities or management hypotheses
Recommended next analytics layer
Technology foundation
Technology follows the business question
The stack is built around reliable data processing, reproducible analytics and the ability to automate more of the decision process over time.
Data & Analytics
SQLPythonPostgreSQLDuckDBpandasPolars
BI & Reporting
Power BIExcelPower QueryGoogle Sheets
Business Systems
CreatioBAFBPMN 2.0REST API
Engineering & Reproducibility
GitGitHubAutomationData Validation
Built to expand
Today: internal business data. Tomorrow: a broader intelligence architecture.
DiLoLid starts commercially with Business Analytics & Growth Intelligence. The platform architecture is designed to later combine internal data, external research, legal intelligence and business processes.
Ideal starting clients
When you already have data, but analytics is still fragmented
E-commerce
Orders, customers, repeat purchases, categories and margins.
Retail & Distribution
Sales, assortment, regions, segments and performance.
Service Businesses
Utilization, repeat visits, revenue per client and retention.
B2B Companies
Pipeline, customer base, revenue concentration and churn risk.
Start with one question
What business question could your data help answer?
Tell us what data you have, how it is stored and what you want to understand. We will identify the most useful first analytical step.