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Example $1\mathrm{.}1$: Retail Markdown Decisions

Most department stores clear seasonal inventory by reducing prices.

Kry purstive: When to reduce the price and by how much to

maximixe revenue? Potential applications of asalytic:

Descriptic analydics: examine historical data for similar protucts

Drodistivcanalydics predict sales band on pric

Irecriptisc analytios: find the best sets of pricing and advertising to

do it$.$ You can combine this with other information.

For example, you can combine this with your

Match different analytics to what they can do$.$

help companies classify their customers into segments to develop specific marketing campaigns.

help detect hidden patterns in large quantities of data to group data into Descriptive analytics sets to predict behavior.

can predict risk and find relationships in data not readily apparent with Predictive analytics traditional analyses.

can use mathematical techniques with optimization to make decision that take into account the uncertainty in the data.

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