CASE:

Pandora is the Internet’s most successful subscription radio service. In May 2014, Pandora had 77 million registered users. Pandora accounts for over 9 percent of total U.S. radio listening hours. The music is delivered to users from a cloud server, and is not stored on user devices.

It’s easy to see why Pandora is so popular. Users are able to hear only the music they like. Each user selects a genre of music based on a favorite musician or vocalist, and a computer algorithm puts together a “personal radio station” that plays the music of the selected artist plus closely related music by different artists. The algorithm uses more than 450 factors to classify songs, such as the tempo and number of vocalists. These classifications, in conjunction with other signals from users, help Pandora’s algorithms select the next song to play.

People love Pandora, but the question is whether this popularity can be translated into profits. How can Pandora compete with other online music subscription services and online stations that have been making music available for free, sometimes without advertising? “Free” illegally downloaded music has also been a significant factor, as has been iTunes, charging 99 cents per song with no ad support. At the time of Pandora’s founding (2005), iTunes was already a roaring success.

Pandora’s first model was to give away 10 hours of free music and then ask subscribers to pay $36 per month for a year once they used up their 10 free hours. Result: 100,000 people listened to their 10 hours for free and then refused to pay for the annual service. Facing financial collapse, in November 2005 Pandora introduced an ad-supported option. In 2006, Pandora added a “Buy” button to each song being played and struck deals with Amazon, iTunes, and other online retail sites. Pandora now gets an affiliate fee for directing listeners to sites where users can buy the music. In 2008, Pandora added an iPhone app to allow users to sign up from their smartphones and listen all day if they wanted. Today, 70 percent of Pandora’s advertising revenue comes from mobile.

In late 2009 the company launched Pandora One, a premium service that offered no advertising, higher quality streaming music, a desktop app, and fewer usage limits. The service costs $4.99 per month. A very small percentage of Pandora listeners have opted to pay for music subscriptions, with the vast majority opting for the free service with ads. In fiscal 2013 Pandora’s total revenue was $427.1 million, of which $375.2 million (88 percent) came from advertising.

Pandora has been touted as a leading example of the “freemium” revenue model, in which a business gives away some services for free and relies on a small percentage of customers to pay for premium versions of the same service. If a market is very large, getting just 1 percent of that market to pay could be very lucrative— under certain circumstances. Although freemium is an efficient way of amassing a large group of potential customers, companies, including Pandora, have found that it is challenging to convert people enjoying the free service into customers willing to pay. A freemium model works best when a business incurs very low marginal cost, approaching zero, for each free user of its services, when a business can be supported by the percentage of customers willing to pay, and when there are other revenues like advertising fees that can make up for shortfalls in subscriber revenues.

In Pandora’s case, it appears that revenues will continue to come overwhelmingly from advertising, and management is not worried. For the past few years, management has considered ads as having much more revenue-generating potential than paid subscriptions and is not pushing the ad-free service. By continually refining its algorithms, Pandora is able to increase user listening hours substantially. The more time people spend with Pandora, the more opportunities there are for Pandora to deliver ads and generate ad revenue. The average Pandora user listens to 19 hours of music per month.

Pandora is now intensively mining the data collected about its users for clues about the kinds of ads most likely to engage them. Pandora collects data about listener preferences from direct feedback such as likes and dislikes (indicated by thumbs up or down on the Pandora site) and “skip this song” requests, as well as data about which device people are using to listen to Pandora music, such as mobile phones or desktop computers. Pandora uses these inputs to select songs people will want to stick around for, and listen to. Pandora has honed its algorithms so they can analyze billions more signals from users generated over billions of listening minutes per month.

As impressive as these numbers are, Pandora (along with other streaming subscription services) is still struggling to show a profit. There are infrastructure costs and royalties to pay for content from the music labels. Pandora’s royalty rates are less flexible than those of its competitor Spotify, which signed individual song royalty agreements with each record label. Pandora could be paying even higher rates when its current royalty contracts expire in 2015. About 61 percent of Pandora’s revenue is currently allocated to paying royalties. Advertising can only be leveraged so far, because users who opt for free ad-supported services generally do not tolerate heavy ad loads.

QUESTION:

For Pandora, what business strategies are being supported by the use of data mining? Explain your answer.

Case

Pandora is the Internet’s most successful subscription radio service. In May 2014, Pandora had 77 million registered users. Pandora accounts for over 9 percent of total U.S. radio listening hours. The music is delivered to users from a cloud server, and is not stored on user devices.

It’s easy to see why Pandora is so popular. Users are able to hear only the music they like. Each user selects a genre of music based on a favorite musician or vocalist, and a computer algorithm puts together a “personal radio station” that plays the music of the selected artist plus closely related music by different artists. The algorithm uses more than 450 factors to classify songs, such as the tempo and number of vocalists. These classifications, in conjunction with other signals from users, help Pandora’s algorithms select the next song to play.

People love Pandora, but the question is whether this popularity can be translated into profits. How can Pandora compete with other online music subscription services and online stations that have been making music available for free, sometimes without advertising? “Free” illegally downloaded music has also been a significant factor, as has been iTunes, charging 99 cents per song with no ad support. At the time of Pandora’s founding (2005), iTunes was already a roaring success.

Pandora’s first model was to give away 10 hours of free music and then ask subscribers to pay $36 per month for a year once they used up their 10 free hours. Result: 100,000 people listened to their 10 hours for free and then refused to pay for the annual service. Facing financial collapse, in November 2005 Pandora introduced an ad-supported option. In 2006, Pandora added a “Buy” button to each song being played and struck deals with Amazon, iTunes, and other online retail sites. Pandora now gets an affiliate fee for directing listeners to sites where users can buy the music. In 2008, Pandora added an iPhone app to allow users to sign up from their smartphones and listen all day if they wanted. Today, 70 percent of Pandora’s advertising revenue comes from mobile.

In late 2009 the company launched Pandora One, a premium service that offered no advertising, higher quality streaming music, a desktop app, and fewer usage limits. The service costs $4.99 per month. A very small percentage of Pandora listeners have opted to pay for music subscriptions, with the vast majority opting for the free service with ads. In fiscal 2013 Pandora’s total revenue was $427.1 million, of which $375.2 million (88 percent) came from advertising.

Pandora has been touted as a leading example of the “freemium” revenue model, in which a business gives away some services for free and relies on a small percentage of customers to pay for premium versions of the same service. If a market is very large, getting just 1 percent of that market to pay could be very lucrative— under certain circumstances. Although freemium is an efficient way of amassing a large group of potential customers, companies, including Pandora, have found that it is challenging to convert people enjoying the free service into customers willing to pay. A freemium model works best when a business incurs very low marginal cost, approaching zero, for each free user of its services, when a business can be supported by the percentage of customers willing to pay, and when there are other revenues like advertising fees that can make up for shortfalls in subscriber revenues.

In Pandora’s case, it appears that revenues will continue to come overwhelmingly from advertising, and management is not worried. For the past few years, management has considered ads as having much more revenue-generating potential than paid subscriptions and is not pushing the ad-free service. By continually refining its algorithms, Pandora is able to increase user listening hours substantially. The more time people spend with Pandora, the more opportunities there are for Pandora to deliver ads and generate ad revenue. The average Pandora user listens to 19 hours of music per month.

Pandora is now intensively mining the data collected about its users for clues about the kinds of ads most likely to engage them. Pandora collects data about listener preferences from direct feedback such as likes and dislikes (indicated by thumbs up or down on the Pandora site) and “skip this song” requests, as well as data about which device people are using to listen to Pandora music, such as mobile phones or desktop computers. Pandora uses these inputs to select songs people will want to stick around for, and listen to. Pandora has honed its algorithms so they can analyze billions more signals from users generated over billions of listening minutes per month.

As impressive as these numbers are, Pandora (along with other streaming subscription services) is still struggling to show a profit. There are infrastructure costs and royalties to pay for content from the music labels. Pandora’s royalty rates are less flexible than those of its competitor Spotify, which signed individual song royalty agreements with each record label. Pandora could be paying even higher rates when its current royalty contracts expire in 2015. About 61 percent of Pandora’s revenue is currently allocated to paying royalties. Advertising can only be leveraged so far, because users who opt for free ad-supported services generally do not tolerate heavy ad loads.

CASE QUESTION:

What type of e-commerce is Pandora? What is Pandora’s ecommerce business model? Explain your answer?

Consider a study that compares the Atkins diet to a conventional diet. A study at the University of Pennsylvania selected a sample of 63 subjects from the local population of obese adults. Researchers randomly assigned 33 to the Atkins diet and 30 subjects to a conventional diet. Test whether there is a significant difference in the mean weight loss (measured in pounds) across the two different diet programs.

Using software:

Generate summary statistics (central tendency and variability measures) for the two samples and briefly summarize what they say.

b. Conduct a test of significance for the difference between the mean weight across the different diet programs. Be sure to show the output from the software and interpret the results.

c. Construct a 95% confidence interval for the difference parameter in mean weight lost and make an interpretation.

d. Finally, are there any other factors, besides the type of diet, that could possibly influence weight loss (identify at least 2)? Include a brief explanation of each.

Atkins   Conventional  
27   26  
31   26  
34   29  
31   24  
28   25  
32   22  
33   27  
27   24  
34   25  
25   28  
31   30  
26   27  
28   25  
30   23  
26   20  
26   22  
31   29  
34   28  
27   21  
28   25  
33   22  
26   24  
26   22  
30   25  
26   29  
34   24  
25   26  
32   21  
29   22  
33   21  
27      
29      
25      
      
      

Consider a study that compares the Atkins diet to a conventional diet. A study at the University of Pennsylvania selected a sample of 63 subjects from the local population of obese adults. Researchers randomly assigned 33 to the Atkins diet and 30 subjects to a conventional diet. Test whether there is a significant difference in the mean weight loss (measured in pounds) across the two different diet programs.

Using software:

1. Generate summary statistics (central tendency and variability measures) for the two samples and briefly summarize what they say.

b.         Conduct a test of significance for the difference between the mean sales across the two different locations in the store. Be sure to show the output from the software and interpret the results.

c. Construct a 95% confidence interval for the difference parameter in mean sales and make an interpretation.

d. Finally, are there any other factors, besides where the product is placed, that could possibly influence sales (identify at least 2)? Include a brief explanation of each.

Consider a study that compares the Atkins diet to a conventional diet. A study at the University of Pennsylvania selected a sample of 63 subjects from the local population of obese adults. Researchers randomly assigned 33 to the Atkins diet and 30 subjects to a conventional diet. Test whether there is a significant difference in the mean weight loss (measured in pounds) across the two different diet programs.

Using software:

Generate summary statistics (central tendency and variability measures) for the two samples and briefly summarize what they say.

b. Conduct a test of significance for the difference between the mean sales across the two different locations in the store. Be sure to show the output from the software and interpret the results.

c. Construct a 95% confidence interval for the difference parameter in mean sales and make an interpretation.

d. Finally, are there any other factors, besides where the product is placed, that could possibly influence sales (identify at least 2)? Include a brief explanation of each.

Atkins   Conventional  
27   26  
31   26  
34   29  
31   24  
28   25  
32   22  
33   27  
27   24  
34   25  
25   28  
31   30  
26   27  
28   25  
30   23  
26   20  
26   22  
31   29  
34   28  
27   21  
28   25  
33   22  
26   24  
26   22  
30   25  
26   29  
34   24  
25   26  
32   21  
29   22  
33   21  
27      
29      
25      

Journal Entries and Trial Balance

On October 1, 2018, Jay Pryor established an interior decorating business, Pioneer Designs. During the month, Jay completed the following transactions related to the business:

Enter the following transactions on Page 2 of the two-column journal:

Required:

1. Journalize and insert the posting references for each transaction in a two-column journal beginning on Page 1, referring to the following chart of accounts in selecting the accounts to be debited and credited. For a compound transaction, if an amount box does not require an entry, leave it blank.

Managers are required to make many tough decisions over the course of a workday. One of the tough decisions a manager may be faced with is the decision to drop an existing customer from their portfolio.

Some companies refuse to drop customers (including non-profitable customers) in the hopes that these unprofitable customers will become profitable in the future.

Other companies do not want unprofitable customers impacting their bottom-line year after year and choose to drop them.

In your opinion, when should unprofitable customers be dropped (if at all)? Provide an example from a newspaper or other media sources from the past three months to support your argument.

The Harvard Business Review released a case study, included in our readings this week, on “When to Drop an Unprofitable Customer.” You may choose to discuss this case analysis as part of your response; however it is not required.

Jordan, Inc., is a leading manufacturer of sports apparel, shoes, and equipment. The company’s 2015 financial statements contain the following information (in millions):

A note disclosed that the allowance for uncollectible accounts had a balance of $117 million and $104 million at the end of 2015 and 2014, respectively. Bad debt expense for 2015 was $45 million. Assume that all sales are made on a credit basis.

Required:

1. What is the amount of gross (total) accounts receivable due from customers at the end of 2015 and 2014?
2. What is the amount of bad debt write-offs during 2015?
3. Analyze changes in the gross accounts receivable account to calculate the amount of cash received from customers during 2015.
4. Analyze changes in net accounts receivable to calculate the amount of cash received from customers during 2015.

Minta Corporation is a leading manufacturer of sports apparel, shoes, and equipment. The company’s 2017 financial statements contain the following information ($ in millions):

A note disclosed that the allowance for uncollectible accounts had a balance of $37 million and $61 million at the end of 2017 and 2016, respectively. Bad debt expense for 2017 was $58 million. Assume that all sales are made on a credit basis.

Required:
1. What is the amount of gross (total) accounts receivable due from customers at the end of 2017 and 2016?
2. What is the amount of bad debt write-offs during 2017?
3. Analyze changes in the gross accounts receivable account to calculate the amount of cash received from customers during 2017.
4. Analyze changes in net accounts receivable to calculate the amount of cash received from customers during 2017.
  

Minta Corporation is a leading manufacturer of sports apparel, shoes, and equipment. The company’s 2017 financial statements contain the following information ($ in millions):

A note disclosed that the allowance for uncollectible accounts had a balance of $30 million and $54 million at the end of 2017 and 2016, respectively. Bad debt expense for 2017 was $51 million. Assume that all sales are made on a credit basis.

Required:
1. What is the amount of gross (total) accounts receivable due from customers at the end of 2017 and 2016?
2. What is the amount of bad debt write-offs during 2017?
3. Analyze changes in the gross accounts receivable account to calculate the amount of cash received from customers during 2017.
4. Analyze changes in net accounts receivable to calculate the amount of cash received from customers during 2017.