Marketing Analytics: Case Studies

MARKETING ANALYTICS: Case Study Name: ______

Case No. / Chapters / Case Title
6 / 6 / Business Operations: Forecasting

Background:

You are the marketing manager for Acme Realty, a real estate company specializing in listings in upscale Hillsborough, California. You have been asked to forecast sales for the coming year.

You have two sets of data at your disposal.

· Home Sales History: The history data set shows the average home sales price for every month from January 2008 through August 2010.

· Home Sales Detail: The detail data set shows details of recent home sales, including the sales price, the house size in square feet, the lot size in square feet, and the number of bedrooms and bathrooms.

To be thorough, you plan to build two models. The first will use time series regression to forecast future sales, based on historic sales. The second will use causal regression to forecast sales prices based on the house size and lot size.

1. Forecast home sales for 2011. Use time series forecasting with the Home Sales History data set.

Forecasting Attribute / Results
Y-intercept
X (time) coefficient
Time series equation
Forecast for 2011

2. Forecast the price for a house size of 4000 sq. ft. and a lot size of 22000 sq. ft. Use causal regression.

Forecasting Attribute / Results
Y-intercept
X1 (House size) coefficient
X2 (Lot size) coefficient
Causal equation
Forecast

3. Record your observations about the forecasting process. How accurate is it? How could you improve it?

Observations / Results
Accuracy
Improvements
Other