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Peer Review

Rethinking Retail

Reviewed:

Jan 22, 2026 by Business
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Ratings

Overall Rating: 4.8 stars
Content Quality: 4.5 stars
Effectiveness: 4.5 stars
Ease of Use: 5.0 stars
Overview:

Wharton’s Barbara Kahn, author of The Shopping Revolution: How Retailers Succeed in an Era of Endless Disruption, explains the latest trends in retail, how AI fits into the customer experience, and what’s to come for brick-and-mortar. This would be a good resource for a class on Retailing or Distribution.

Type of Material:

Podcast 

Recommended Uses:

  • In class
  • Lecture
  • Homework and discussions
  • Groups and role play
Technical Requirements:

Reviewer used Google Chrome to review and listen to the podcast and had no issues.

Identify Major Learning Goals:

  • Understand the new retail market
  • Utilize customer experiences in the retail market place
  • Learn about the influence of AI in the retail market
Target Student Population:

  • College Upper Division, Graduate School
  • Undergraduate Retailing or Principles of Marketing class 
Prerequisite Knowledge or Skills:

Students should have an understanding of the sales process and how customers decide to make purchases.

Content Quality

Rating:
Strengths:

  • This material is coming from leading experts in the field. 
  • These experts are seeing the trends as well as educating future generations.
  • The presenter is very knowledgeable and insightful; however, since it is unscripted, there may be gaps in the answers. 
  • The concepts discussed are not evergreen. With retailing changing so dramatically, this may be outdated quickly.  
  • The discussion of omnichannel is the current and future of marketing.  Customers view a retailer’s website, brick-and-mortar store, and app as a single seamless experience, although the company may separate them.   
  • The sales process is often nonlinear and multichannel, instead of being memory-based or institutional. 
  • Consumers move between channels based on preference, context, and device.  I can review on my smartphone and purchase later on my laptop.
Concerns:

  • As with many podcasts, this material is the opinion of the individual presenting the podcast.

Potential Effectiveness as a Teaching Tool

Rating:
Strengths:

  • There were no learning objectives presented. 
  • The material is easy to discern and create your own objectives for students. 
  • Students can learn a great deal of information in a short 18 minutes.
  • Biases in algorithms is an entire podcast or more. 
  • The reference to behavioral economics was apropos.  
  • Algorithmic biases arise from the data input for models and the prioritization of what is considered important.  
Concerns:

  • It would be nice to hear a differing opinion and allow the two opinions to discuss the similarities and differences on the topic.
  • The discussion should have included current trends in how AI search and generative AI responses change customer behavior, for example, online.  Fewer people are clicking on links early in the purchase process because AI provides answers here.
  • A discussion of retail pricing must include electronic shelf labels in brick-and-mortar stores that can instantaneously change prices to accommodate marketplace changes (e.g., competition, political policy, wars, supply chain disruptions, pandemics, and natural disasters).

Ease of Use for Both Students and Faculty

Rating:
Strengths:

  • The site was in working order at the time of the review.
  • The presenter was easy to understand
Concerns:

None

Other Issues and Comments:

The information contained in this podcast could be very beneficial as a starting point for class discussions.

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