Customer Trend Prediction Analysis Model -- 2
Budget: ₹750 – ₹1,250 INR
I have a comprehensive collection of customer data and my priority is to turn it into a reliable model that can predict upcoming customer trends. The raw information covers the whole spectrum of what we track—transaction history, on-site behaviour, social engagement and any other fields stored in our CRM. Everything will be shared in its original format so you can dive straight into exploration.
What I need is a complete analytical workflow: data cleaning, feature engineering, exploratory insights and, most importantly, a predictive model that flags patterns worth acting on. I am comfortable with you choosing proven tools such as Python (pandas, scikit-learn), R, SQL or similar; visual output in Tableau or Power BI is welcome if it speeds up interpretation.
Deliverables
• A documented notebook or script that ingests the full dataset and produces a trained model ready for deployment
• A concise report (slides or PDF) highlighting key drivers behind the forecast and actionable recommendations
• Optional dashboard or interactive visual that lets non-technical stakeholders inspect the forecasts
Acceptance criteria
– Model accuracy validated with cross-validation or a clear hold-out set
– Code reproducible on my machine with instructions
– Insights presented in plain language alongside supporting metrics
Timelines are flexible but I want regular checkpoints so the approach stays aligned with the business context.
What I need is a complete analytical workflow: data cleaning, feature engineering, exploratory insights and, most importantly, a predictive model that flags patterns worth acting on. I am comfortable with you choosing proven tools such as Python (pandas, scikit-learn), R, SQL or similar; visual output in Tableau or Power BI is welcome if it speeds up interpretation.
Deliverables
• A documented notebook or script that ingests the full dataset and produces a trained model ready for deployment
• A concise report (slides or PDF) highlighting key drivers behind the forecast and actionable recommendations
• Optional dashboard or interactive visual that lets non-technical stakeholders inspect the forecasts
Acceptance criteria
– Model accuracy validated with cross-validation or a clear hold-out set
– Code reproducible on my machine with instructions
– Insights presented in plain language alongside supporting metrics
Timelines are flexible but I want regular checkpoints so the approach stays aligned with the business context.