Project Description
I’m rolling out a market-expansion strategy and need a full predictive-analytics design that turns raw market-trends data into clear, actionable forecasts. The goal is simple: surface which regions, segments, and timing windows will give us the highest return as we scale.
Here’s what I’m looking for:
• A data-pipeline blueprint that pulls, cleans, and stores external market trends feeds (think industry reports, macro indicators, social-buzz dashboards).
• A modeling approach—Python with scikit-learn, TensorFlow, or a comparable framework—that can forecast demand shifts and flag emerging opportunities at least one quarter ahead.
• Visual outputs (dashboards or notebooks) that make it easy for non-technical stakeholders to compare expansion scenarios.
• A short technical document so my in-house team can retrain or fine-tune the model later.
My primary dataset is market-trends data, but if you see quick wins in layering sales or behavioral signals, note them in your proposal. Accuracy, clarity, and reproducibility will be the key acceptance criteria.