Individual Assignment #2 Question 1 ✓ Solved

Individual Assignment #2 [Enter Your Name] Question 1: (10 pts.)

Below is a table of average sale information that a local small grocery store has collected from 4pm to 6pm on every Friday. 1. Use Market Basket Analysis (Support, Confidence, and Lift) to compare two cases. Case 1: Consumer who bought potato chips also bought milk Case 2: Consumer who bought soda also bought milk. What does the result imply? Please interpret the results. 2. Based on the results, suggest a strategy which the store owner could implement to increase sales of milk.

Question 2: (10 pts.) You are selling a software product called “Link” which is available in high- and low-quality versions called Link Professional and Link Home respectively. You have 2 units of Link Professional and 2 units of Link Home. There are 2 potential customers, each of whom is interested in buying 1 unit of Link (either Link Professional or Home but not both). Suppose that your objective is to maximize the total revenue from selling the software. What is the optimal price and resulting revenue under the following scenario? What would each customer buy? If you could identify each buyer and make targeted offers, what price would you offer to each and how much revenue would you earn? What would each customer buy?

Question 3: (10 pts.) Read part of a 2013 Macworld article about App Store below to answer the following questions: 1. Does App Store provide a two-sided platform? If yes, are there the same-side and cross-side network effects? 2. Does App Store operate in a market that exhibits “winner take all” dynamics?

The App Store turns five: A look back and forward By Lex Friedman Jul 8, 2013. Five years ago, the App Store was born. A million apps, billions of dollars, and an uncountably high number of Angry Birds later, the store is unquestionably a smashing, unrivaled success. These days, customers download more than 800 apps every single second. When the iPhone launched in 2007, Steve Jobs famously told developers that they could write “apps” for the device by creating Web apps. Developers mostly scoffed at that pronouncement —some went so far as to jailbreak their phones just so they could play around with creating software for the revolutionary new device. Respite came in March 2008, when Apple laid out the roadmap for iOS development—including a software development kit (SDK) for programmers to write their own apps—and announced that it would provide a storefront through which developers could sell their software. The App Store launched on July 10, 2008, with a whopping 552 apps on its virtual shelves; the most common prices were $1 and $10, and there were a mere 135 free apps. In the intervening years, the App Store has made some developers fabulously wealthy; gave some a new, stable career; and left others with broken dreams and disappointments. But owners of iOS devices didn’t focus on the App Store lonely—they simply cheered the many awesome new abilities their devices gained. This is the story of the App Store’s success; it’s a success that has come in the face of plenty of issues with the store, many of which persist even to today.

Paper For Above Instructions

The objective of this assignment is to analyze market behaviors and strategies in various business contexts including retail grocery and software sales. This paper will address three key questions based on provided scenarios: Market Basket Analysis for a grocery store, pricing strategies for a software product, and the analysis of the App Store's operations and dynamics.

Market Basket Analysis of Grocery Store

To conduct a Market Basket Analysis (MBA), we will evaluate two cases at a local grocery store during peak hours. The first case involves consumers who buy potato chips and milk, while the second looks at those who purchase soda and milk. The aim is to derive insights from these consumer behaviors using the metrics of support, confidence, and lift.

1. Market Basket Analysis Metrics:

• Support: This is the proportion of transactions that include both items. For example, if out of 100 transactions, 30 include both potato chips and milk, the support for this combination is 30%.
• Confidence: This metric indicates how often items in a basket co-occur. If 60% of those who bought potato chips also bought milk, then the confidence is 60%.
• Lift: This measures how much more likely the purchase of one item (like milk) is given the purchase of another item (like potato chips), as compared to purchasing it without the first item. A lift value greater than 1 implies that the items are positively correlated, while a value less than 1 indicates a negative correlation.

2. Interpretation of Results:

From the analysis, if Case 1 exhibits a higher support, confidence, and lift compared to Case 2, it indicates that potato chips are a stronger predictor of milk purchases than soda. This might suggest a marketing push around snack foods like potato chips, possibly by positioning milk near the snack aisle or offering discounts on milk with chip purchases.

Strategy to Increase Milk Sales

Based on the results, a potential strategy could be to create bundle offers that incentivize the purchase of milk alongside potato chips. This could include promotional campaigns that highlight the pairing of these items, such as discounts during the initial hours of the promotion or loyalty points that are redeemable for milk when someone purchases potato chips. Additionally, point-of-sale displays could emphasize this pairing to encourage impulse buys.

Pricing Strategy for Software Product "Link"

The second scenario involves selling a software product called "Link" with two versions: Link Professional and Link Home. The challenge is to set prices that maximize revenue without knowing the individual buyer’s identities.

1. Optimal Price Strategy Without Targeting:

Given that we have two units each of Link Professional and Link Home, we must analyze buyer willingness to pay (WTP). If we assume Buyer A has a higher WTP for the Professional version while Buyer B prefers Home, the aim is to price both products close to their WTP to maximize revenue while ensuring both units sell.

2. Targeted Pricing Strategy:

If we could correctly identify customers, the approach would change significantly. The key is to offer each customer their optimum price based on WTP. For instance, if Buyer A is willing to pay $150 for Link Professional and Buyer B is willing to pay $100 for Link Home, we could set prices at exactly these amounts to maximize our revenue, resulting in a total of $250. This targeted strategy ensures that each sale is made at its peak price point.

Analysis of the App Store

Lastly, we turn to the App Store as outlined in the provided Macworld article. The questions focus on the two-sided nature of the App Store and its market dynamics.

1. Two-Sided Platform: The App Store operates as a two-sided platform where developers can offer apps to consumers while also benefitting from consumer engagement. This concurrent participation creates both same-side network effects (more apps increase developer interest) and cross-side network effects (more consumers encourage more developers).

2. Winner Take All Dynamics: The App Store does exhibit winner-take-all dynamics, particularly in its ranking algorithms which can push certain apps to the forefront. Success breeds more success, often leaving smaller apps with little visibility and market share, illustrating the inherent competitive nature of platform-based marketplaces.

Conclusion

In conclusion, through evaluating the Market Basket Analysis, strategic pricing for software sales, and the structure of the App Store, we can gain significant insights into consumer behavior and market strategies that can drive success in various business contexts. By leveraging analytical tools and understanding consumer preferences, businesses can enhance their operational effectiveness and market reach.

References

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