Transformer-Powered Sales Forecasting for a Premium Portfolio
Unit-level property forecasting that combines historical performance with market signals.
- ThinkCol built a Transformer-based forecasting model for a property group that relied on manual, inconsistent sales forecasting.
- The solution integrates market trends and historical portfolio performance to generate unit-level projections.
- Forecast cycles that previously took hours can be reduced to seconds through an automated end-to-end pipeline.
A property group relied on manual, human-driven forecasting across a premium portfolio. Forecasting cycles were time-consuming, difficult to standardise, and dependent on individual judgement even though the organisation had valuable historical and market data available.
ThinkCol developed a Transformer-based forecasting model that combines historical portfolio performance with external market signals. The model generates unit-level projections, helping the team convert scattered market and sales data into structured foresight.
By automating the pipeline from raw data to forecast output, the solution reduces analyst bottlenecks and helps teams make faster, more consistent decisions. Forecasting work that previously required hours of manual review can be completed in seconds through a repeatable model-driven process.
Why customise? Pre-built forecasting tools are not trained on a property group's portfolio structure, sales patterns, and market conditions. Accurate unit-level forecasting requires a model designed around the organisation's own historical data and decision workflow.
