3.3.2 Interpreting Marketing Data

What is the primary purpose of time series analysis?

• To predict future sales

• To reveal underlying patterns by recording and plotting data over time

• To measure the effectiveness of marketing campaigns

• To identify random fluctuations in data

Which of the following is NOT a characteristic of trends in time series analysis?

• Upward

• Constant

• Downward

• Random

What type of fluctuations repeat on a regular basis?

• Seasonal fluctuations

• Random fluctuations

• Major disturbances

• Unpredictable events

Which of the following is an example of a random fluctuation?

• Sales of ice lollies over a year

• The 2013 "horse meat" scandal

• Use of electricity over a 24-hour period

• Sales of a particular product over a number of years

How can time series analysis be used in marketing?

• To set sales targets

• To measure sales performance

• To look for links between sales and marketing activity

• To predict the average increase or decrease over a few years

What is extrapolation used for in the context of sales data?

• To reveal underlying patterns

• To forecast future sales

• To identify random fluctuations

• To measure the effectiveness of marketing campaigns

If sales have increased by 8% a year for the past five years, what will extrapolation predict?

• Sales will decrease in future years

• Sales will remain the same

• Sales will continue to increase by 8% a year

• Sales will fluctuate randomly

What is a major pitfall of using extrapolation for predicting future sales?

• It relies on past trends remaining true

• It can only be used for a few months ahead

• It does not account for seasonal fluctuations

• It is only useful in unstable market environments

What is the biggest pitfall for extrapolation according to the text?

• Seasonal fluctuations

• Random fluctuations

• Sudden unexpected events

• Constant trends

What is correlation?

• A measure of how closely two variables are related

• A measure of the average value of a variable

• A measure of the difference between two variables

• A measure of the total value of a variable