To build a MMM for ElecKart Ontario based ecommerce company
ElecKart is an e-commerce firm based out of Ontario, Canada specialising in electronic products. Over the last year, they had spent a significant amount of money on marketing. Occasionally, they had also offered big-ticket promotions (similar to the Big Billion Day). They are about to create a marketing budget for the next year, which includes spending on commercials, online campaigns, and pricing & promotion strategies. The CFO feels that the money spent over the last 12 months on marketing was not sufficiently impactful, and, that they can either cut on the budget or reallocate it optimally across marketing levers to improve the revenue response.
Imagine that you are a part of the marketing team working on budget optimisation. You need to develop a market mix model to observe the actual impact of different marketing variables over the last year. Using your understanding of the model, you have to recommend the optimal budget allocation for different marketing levers for the next year.
You can download the dataset from this link.
You have to use the data from July 2015 to June 2016. The data consists of the following types of information:
Order level data
• FSN ID: The unique identification of each SKU
• Order Date: Date on which the order was placed
• Order ID: The unique identification number of each order
• Order item ID: Suppose you order 2 different products under the same order, it generates 2 different order Item IDs under the same order ID; orders are tracked by the Order Item ID.
• GMV: Gross Merchandise Value or Revenue
• Units: Number of units of the specific product sold
• Order payment type: How the order was paid – prepaid or cash on delivery
• SLA: Number of days it typically takes to deliver the product
• Cust id: Unique identification of a customer
• Product MRP: Maximum retail price of the product
• Product procurement SLA: Time typically taken to procure the product
Apart from this, the following information is also available:
• Monthly spend on various advertising channels
• Days when there was any special sale
• Monthly NPS score – this may work as a proxy to ‘voice of the customer’
• Stock Index of the company on a monthly basis
You have to create market mix models for three product subcategories - camera accessory, home audio and gaming accessory. Also, the models have to be built at a weekly level for each of the sub-categories.
As the E-commerce company is situated in the Ontario region. Here, we will include its climate data to analyse if it has any effect on the revenue. Create as many features as possible with the available data. Macro-economic data like climatic information on a daily basis can be extracted from the link. Create separate columns if Pay date (if 1st or 15th of the month) and holidays by creating a flag as a 0 or 1. For eg. if Holiday is there, the value will be 1.