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TV Advertising Pricing at Regional Broadcast Network (B)
Popescu, Dana; Goldberg, Rebecca Case QA-0967 / Published January 4, 2024 / 3 pages. Collection: Darden School of Business
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Product Overview

Eric Hughes, advertising sales manager at Regional Broadcast Network (RBN), needs to avoid a takeover by increasing revenue from ad sales. Currently, ad plans are created for advertisers by combining ad spots from a fixed inventory of shows, making an effort to meet requirements such as a preferred split of prime/non-prime shows and views (impressions) in target demographics. Ad plans are priced using rate cards (RCs) based on industry norms, and are often discounted to meet budget requirements. Revenue is not usually optimized using this system because the RCs do not accurately reflect the value of inventory. In this case, which builds on "TV Advertising Pricing at Regional Broadcast Network (A)," Hughes uses the full historical sales dataset to conduct a multivariable regression analysis and better understand what drives the price of a plan. Students are challenged to create their own analysis and rationale, and to develop a guide for pricing each advertiser's plan. This case set presents emerging best practices in maximizing revenues in the ad industry. Students are given supplementary Excel workbooks containing sample data and use the Solver module and regression analysis to complete the assignment. This case set is suitable for use when teaching pricing analytics, decision analysis, statistics, quantitative analysis, or operations management. It may be used with a graduate, undergraduate, or executive education audience.




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  • Overview

    Eric Hughes, advertising sales manager at Regional Broadcast Network (RBN), needs to avoid a takeover by increasing revenue from ad sales. Currently, ad plans are created for advertisers by combining ad spots from a fixed inventory of shows, making an effort to meet requirements such as a preferred split of prime/non-prime shows and views (impressions) in target demographics. Ad plans are priced using rate cards (RCs) based on industry norms, and are often discounted to meet budget requirements. Revenue is not usually optimized using this system because the RCs do not accurately reflect the value of inventory. In this case, which builds on "TV Advertising Pricing at Regional Broadcast Network (A)," Hughes uses the full historical sales dataset to conduct a multivariable regression analysis and better understand what drives the price of a plan. Students are challenged to create their own analysis and rationale, and to develop a guide for pricing each advertiser's plan. This case set presents emerging best practices in maximizing revenues in the ad industry. Students are given supplementary Excel workbooks containing sample data and use the Solver module and regression analysis to complete the assignment. This case set is suitable for use when teaching pricing analytics, decision analysis, statistics, quantitative analysis, or operations management. It may be used with a graduate, undergraduate, or executive education audience.

  • Learning Objectives