Case Study: Optimization WEAR A MASK CAMPAIGN

In light of the 2nd/3rd wave of COVID-19 in the US as we approach the holidays, the American Hospital Association is launching a Wear a Mask Campaign. They are encouraging people across the country to continue to practice safe measures to stop the spread of COVID-19. Their “campaign aims to offer resources on proper mask-wearing and care practices in addition to advice from health leaders to better equip our nation with the information they need to keep themselves, their family, and their communities safe.” They are encouraging people “to follow science: continue social distancing, washing hands for at least 20 seconds, and most importantly, to wear a face covering when outside the home.” The AHA is looking for assistance from students to help further the public service campaign to millennials throughout the country regarding the continued importance of wearing masks in public and maintaining social distancing to help reduce the spread of COVID-19. The AHA is requesting advice on how to distribute this marketing budget across Television (including ads on streaming video services), Social Media (Instagram/TikTok), and Outdoor Ads (such as billboards, buses, train stations). The budget has been set at $3,750,000.
The following information is provided about each of these options: about the potential effectiveness rating (Exposure Rating) per ad, their estimate of the number of millennials reached per ad, and the cost for each ad:
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The exposure rating is a measure of the value of the ad to the listeners/viewers. It is a function of such things as image, message, recall, visual and audio appeal, and so on. As expected, the more expensive television advertisements has the highest exposure effectiveness rating along with the greatest potential for users to follow the recommendations.
At this point, it is believed that the data concerning exposure and reach were only applicable to the first few ads in each medium. For Television, the exposure rating of 97.2 and the 700K millennials reached per ad were reliable for the first 17 Television ads. After 17 ads, the benefit is expected to decline. It is recommended to reduce the exposure rating to 59.4 and the estimate of the number of people reached 380K for any Television ads beyond 17. For Social Media, the preceding data are reliable up to a maximum of 33 ads. Beyond 33 ads, the exposure rating declines to 32.4 and the number of millennials reached declines to 200K per ad. Similarly, for Ads (Outdoors), the preceding data are reliable up to a maximum of 40; the exposure rating declines to 1.1 and the potential number of people reached declines to 25K for additional ads.
The objective of the marketing campaign would be to maximize total exposure rating, across all media. Because the importance of the messaging, the campaign must reach at least 25 million millennials. To balance the campaign and make use of all media, the following guidelines must be incorporated:
• Use at least twice as many Social Media advertisements as Television advertisements
• Use no more than 20 Television advertisements.
• The Television budget should be less than $1,600,000
• The Social Media advertising budget is restricted to a maximum of $2,000,000
• The Ads (Outdoors) budget is to be at least $300,000
Recommend how the $3,750,000 advertising budget should be allocated among the choices. Develop a mathematical programming model that can be used to determine the advertising budget allocation. (HINT: you should define two variables for each media option (eg. T1 = number of Television advertisements with rating of 97.2 and the 700K millennials reached and T2 = number of Television advertisements with rating of 59.4 and 380K millennials reached, and so on). Enter the problem into Excel and use Solver to solve for the optimal solution.

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