Question

You are the buyer at a local apparel store with a $68,000 budget (Open-To-Buy) allocated for purchasing sweatshirts for the Fall season. Using the historical sales data and market trends, determine the optimal sweatshirt unit assortment using Microsoft Excel. Which of the following factors would you consider to ensure an effective assortment planning process and maximize the return on investment (ROI) for the Fall season?

a. Analyzing customer preferences and demand patterns to identify the most popular sweatshirt styles and sizes for the target market.

b. Estimating the total sales revenue and gross margin contribution for each sweatshirt unit based on the pricing strategy and market competitiveness.

c. Forecasting the inventory turnover rate and stock-to-sales ratio to optimize the inventory levels and minimize excess stock or stockouts during the Fall season.

d. Implementing a markdown optimization strategy and promotional calendar to strategically manage discounts and promotional offers, ensuring effective inventory clearance and maximizing profitability throughout the season.

Answer 1

Effective assortment planning for maximizing ROI involves analyzing customer preferences, revenue estimation, inventory forecasting, and applying markdown strategies, alongside using tools like Excel and models such as the Huff Model.

Step-by-step explanation:

To effectively plan an assortment using a $68,000 budget for sweatshirts in the Fall season, several factors should be considered to maximize return on investment (ROI):

• Analyzing customer preferences and demand patterns helps understand popular styles and sizes.
• Estimating sales revenue and gross margin contributes to pricing strategy effectiveness.
• Forecasting inventory turnover and stock-to-sales ratio is key for optimal inventory levels.
• Markdown optimization and a promotional calendar are crucial for inventory management and profitability.

To apply these considerations, you may use tools like Microsoft Excel for analysis and a model such as the Huff Model for predicting customer shopping behavior based on location, store attractiveness, and competition.