Lecture 12

Question 1

Evolving retail analytics

Answer 1

• Description analytics
• Diagnostic analytics
• Predictive analytics
• Prescriptive analytics
• Autonomous analytics

Question 2

Description analytics

Answer 2

descriptive statistics of how much each item in the assortment sold in the past period

Question 3

Diagnostic analytics

Answer 3

a model that relates sales to marketing-mix activity (price, promo, shelf space) to explain past sales patterns

Question 4

Predictive analytics

Answer 4

an attribute-based version of the previous model that allows one to predict the sales for new line extensions based on the calibrated model

Question 5

Prescriptive analytics

Answer 5

the previous model + some optimization routine that searches for the best product line extension to add to the assortment

Question 6

Autonomous analytics

Answer 6

automated algorithm used in online setting that continuously updates itself and presents each visitor with an optimized assortment

Question 7

What is the effect of customer assistance on sales?

Answer 7

Diagnostic analytics

Question 8

How can we best predict product returns?

Answer 8

Predictive analytics

Question 9

How can we optimize an experiential store flyer?

Answer 9

Prescriptive analytics

Question 10

Decision support system components

Answer 10

1. Category sales model
2. Very large neighborhood search heuristic

Question 11

Category sales model

Answer 11

• Estimating the category sales response function
• Quantifying the effect of the amount of space in a store flyer on its own and cross-category space

Question 12

Very Large Neighborhood Search Heuristic

Answer 12

• Optimizing the composition of a flyer
• Simultaneously deciding on category selection and space allocation
• Heuristic that finds a neighbor of a flyer and when an improvement moves there -> in parallel on multiple computing cores from different starting solutions. Find the optimal flyer out of 450 Mio possible ones in less than 15 secondes

Question 13

New retail characteristics

Answer 13

• Digital supply chains
• Digital payments
• Platforms that collect lots of data
• In-store apps
• Super apps
• …

Question 14

Priorities of retailers: seven themes

Answer 14

1. Advancing analytics to build more resilient supply chains
2. More localizing of decisions at the store level
3. Improving measurement of in-store customer behavior via new technologies
4. Reinforcing omnichannel orientation through enhanced inventory-sharing and more efficient omnichannel distribution and delivery
5. Extending data access within the company across the value chain
6. Using more external and contextual data
7. Connecting different decision areas such as inventory optimization for product promotions, or demand forecasting with anticipatory returns

Question 15

New technology focus:

Answer 15

1. Get better at tracking assets such as inventory and shopping carts
2. Gain a better understanding of what happens in-store in terms of traffic and customer behavior
3. Cloud-based storage and computing to provide (near) real-time recommendations for mobile users