Predictive Analytics & Forecasting
We build predictive analytics systems that help companies forecast leads, revenue, demand, user behavior, and operational performance — using machine learning, time-series modeling, and AI-driven scoring tailored to your business data.
We build predictive analytics systems that help companies forecast leads, revenue, demand, user behavior, and operational performance — using machine learning, time-series modeling, and AI-driven scoring tailored to your business data.
Our predictive models are designed for real-world reliability: transparent, explainable, and fully GDPR-compliant.
We integrate them directly into your dashboards, internal tools, and workflows to support better decisions across sales, marketing, product, operations, and finance.
What We Deliver
Lead & Conversion Forecasting
- •Predict lead volume and traffic trends
- •Qualification scoring based on historical patterns
- •Conversion probability models
- •Marketing spend efficiency predictions
- •Cross-channel attribution improvements
Sales & Revenue Forecasting
- •Revenue and MRR forecasting
- •Churn prediction for SaaS and subscription products
- •Pricing and discount impact simulation
- •Pipeline probability scoring (CRM-integrated)
- •Cohort and lifecycle predictions
Demand & Operational Forecasting
- •Inventory and supply-demand prediction
- •Staffing and workload forecasting
- •Logistics and delivery time estimation
- •Operational risk scoring
- •Seasonality and trend decomposition
User Behavior & Product Analytics
- •Feature adoption prediction
- •User retention risk scoring
- •Recommendation engines
- •Anomaly detection for product usage
- •Customer segmentation with ML clustering
Why Companies Choose Our Predictive Analytics
When You Need Predictive Analytics
This service is ideal when you need:
Tools & Technologies
Machine Learning & Modeling
Forecasting models (ARIMA, Prophet, advanced time-series), clustering, classification, regression, anomaly detection, embeddings
Data & Pipelines
PostgreSQL, BigQuery, ClickHouse, Supabase, dbt, Airflow, Kafka/Redpanda
AI & Vector Layer
OpenAI models, Llama/Mistral local models, vector databases, semantic enrichment
Frontend & Dashboards
Next.js, React, custom UI components, real-time dashboards
Integrations
CRM (HubSpot, Pipedrive, Bitrix24), ERP, internal tools, marketing platforms
Infrastructure
Vercel EU, Supabase EU, AWS EU, Docker, CI/CD
Process: How We Build Predictive Analytics
Step 1 — Data Audit & Preparation
- •Identify relevant data sources
- •Clean, normalize, and transform data
- •Feature engineering and enrichment
Step 2 — Model Development
- •Time-series and ML model creation
- •Training, tuning, cross-validation
- •Explainability and interpretation checks
Step 3 — Integration Into Your Systems
- •Embedding predictions into dashboards
- •CRM scoring fields (lead score, churn score)
- •Operational automations based on forecasts
Step 4 — Monitoring & Improvement
- •Continuous model performance monitoring
- •Drift detection and updates
- •Long-term optimization
Example Predictive Analytics Work (Case Studies)
Lead conversion forecasting for a European B2B company
ML model predicting lead conversion rates with 85% accuracy
Revenue prediction model integrated into a SaaS dashboard
Real-time revenue forecasting with MRR predictions and churn scoring
Demand forecasting for an e-commerce brand
Inventory and supply-demand prediction reducing stockouts by 40%
Churn scoring model reducing subscription loss by 30%
Predictive churn model with early intervention recommendations
Operational forecasting for workload and staffing
Staffing prediction model optimizing resource allocation
FAQ
Do predictive models need large datasets?
Not always — we use statistical models for smaller datasets and ML for larger ones.
Can predictions be integrated into our CRM?
Yes — we can write scores and forecasts directly into HubSpot, Pipedrive, or Bitrix24.
Is everything GDPR compliant?
Yes — all models run on EU-based servers with strict data controls.
Can models run continuously?
Yes — we support automated retraining, pipelines, and real-time scoring.
Can predictions appear in dashboards?
Absolutely — we integrate them into your existing dashboards or build new ones.
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We work with companies in Berlin and across Germany, delivering predictive analytics systems, ML forecasting models, and AI-driven scoring for leads, revenue, demand, and user behavior. Our Berlin-based team specializes in time-series modeling, transparent ML models, CRM-integrated predictions, and GDPR-compliant forecasting systems for B2B SaaS platforms and enterprise analytics.