Dastellar is a data engineering and data science consultancy that works exclusively with retailers.

Most retail companies collect more data than they use. Sales history sits in one system, inventory in another, customer data in a third and the teams making purchasing, marketing, and pricing decisions work from spreadsheets that took someone three days to build. The tools aren't the problem. The data underneath is.

We fix that. Then we build on it.

Our work falls into three areas:
- Demand forecasting: SKU-level models that replace gut-feel purchasing with forecasts your ops team can act on. One engagement cut excess inventory by 18% and reduced lost sales by 22%.
- Customer lifetime value prediction: models that score every customer by expected future value, so retention budgets go where the money is. In one project, we identified 95% of future revenue concentrated in just 25% of the customer base.
- Retail data platforms: we consolidate disconnected systems into a single pipeline with automated reporting. One client went from 3 days of manual reporting to 4 hours across 5 unified data sources.

We work on a time-and-materials basis with a senior team that does nothing but data for retail. No bench of juniors, no proprietary lock-in - you keep the code, the models and the documentation.

Full case studies with methodology at dastellar.com.

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