Daily Food Delivery Data Insights

Weekly I’ll upload an Excel file that captures the Multiple activity on our food-delivery channel: total orders, discount amounts, burn, coupon redemptions, funnel movement from menu views through check-out, and a few campaign tags. I need these numbers turned into clear, immediately usable guidance—what levers can we pull today to boost sales and, ultimately, double delivery revenue? regression analysis & Variable Analysis so we can isolate which variables actually drive order volume and ticket value. Correlation checks, significance testing, and quick visualisations are welcome if they sharpen the story, but regression will be the core technique. Here’s what I’ll count on you to send back—every weekday, ideally within a few hours of receiving the sheet: May involve intially few video calls for discussion to understand the business , the numbers , product options and variables within swiggy Zomato • A concise insight summary (1-2 paragraphs) highlighting the strongest predictors of orders and revenue for that day • A brief recommendation list of actions to test immediately (e.g., raise free-delivery threshold, shift coupon value, refine menu placement) • The supporting model output or dashboard view, so I can trace your reasoning and share it internally Priority will go to freelancers who can show past work and experience in e-commerce or food-tech analytics, especially where daily or high-frequency decision cycles were involved. If you already have template notebooks or scripts that automate much of this, please mention it; faster turnaround is a plus. Let’s translate raw metrics into revenue-driving moves, starting with tomorrow’s sheet.

Project ID: 40550295