Analysis Report Three - Privacy and Customer Profiling

Executive Summary

The readings we had to read this week argued that organizations seem to really depend on customer data to show personalized experiences and to increase decision-making. Although that can be considered a good thing, the use and collection of customer information creates challenges when talking about privacy, trust, and honesty. Organizations should show customers the benefits of personalized experiences and ensure that their personal information will not be at risk and will be protected. The Harvard Business Review “Customer Data: Designing for Transparency and Trust” talks about how companies should view data from customers as something that is worth a lot of value instead of just something that is collected and holds no value. It is a fact that customers are more trusting and willing to share more of their information when they feel that their information is fully protected and that they have the most control over what happens with their information. “How Retailers Became Ad Platforms” is an article that shares similar ideas to the previous article but kinds of add a little bit more to it. It shows how retailers use this certain data to create these platforms. Also, since retail media shows multiple opportunities for organizations to better increase their strategies on how to target certain customers and increase their profit, that can lead to certain concerns about accountability and trust between manufacturers and retailers. Everyone knows about the increase of AI usage nowadays but does anyone know about the problems it creates when talking about data for customers and personalization. It is no secret that most organizations are trying to incorporate AI into their systems somehow and someway but most organizations do not factor in that AI is not a human and they have to think about how personalization influence these relationships with customers.

Introduction

Technology has been increasing so fast these days that it is getting hard for organizations to keep up with their data. Organizations now have the ability to get and collect information from phones, AI systems, etc. The data they collect from these devices gives the organizations the ability to create personalized experiences and increase decision-making in a good way. Even though this can come across as a good thing, some risks can come along with it as well. There are some concerns with security, privacy, and if organizations fully understand how to use the data to show the customers how to support it. An important factor in The Harvard Business Review “Customer Data: Designing for Transparency and Trust” is the idea of transparency and the creation of value. Transparency means organizations need to clearly communicate what information they get and how they will use the information that they get. Customer control gives customers their choice on how their data and information are shared across different platforms and lets them manage their privacy. Creation of value makes sure that these customers are thanked and gets many benefits for being vulnerable in sharing their information. The readings this week show how for data strategies to be successful, organizations need to do more than just collect the large amounts of data. Organizations need to come up with systems that clearly work and can be trusted so that customer’s information are protected and but they are still creating personalized and valued experiences.

Privacy vs Profiling

One of the biggest concerns today for organizations is trying to balance the ability to come up with personalized experiences that are detailed and nice while thinking about how customer’s are concerned with the security and privacy of it all. The modern companies use information from customers to understand behavior, personalize their recommendations, and just improve their efforts overall. However, these strategies can cause problems when customers do not know what kind of their information is being collected and where it is going. The Harvard Business Review “Customer Data: Designing for Transparency and Trust” argues that many customers do understand that organizations do collect information about them, but do not understand the specific about it. The lack of knowledge creates a distance between an organization’s ability to collect and profile customer information and customer’s understanding of the process of profiling. This article highlights three categories of customer data including profile data, digital exhaust, and self-reported data. Profiling data is showed when organizations use various sources to predict a customer’s behavior. Digital exhaust means information that is generated through, for example, browser history. Self-reported data talks about information that customers provide like an email address. Even though profiling has many benefits, customers focus more on protecting their information. The article explained that customers were concerned more with health and financial information. Customers were more vulnerable to share this data when organizations were willing to improve or increase their products. Different examples from modern organizations show different strategies on how to handle when customers complain about their privacy being affected. The article “Disney’s Magical Big Data Transformation” explained that Disney’s Magicband system collects customer information to try and help guests enjoy every single second of their experience by allowing the access to hotel rooms be easier by just using the band and buy items. Even though Disney seems to collect a lot of information, they make it known that the guest’s privacy is secure and safe. This is where transparency is used because the Disney company clearly states what is being done and helps the customers better understand. Finally, AI contributes to the Privacy and Profiling argument because AI depends on customer data for personalized experiences but these personalization techniques can shape a customer’s view on technology. If in the future AI forms too closely with someone’s specific views, it may show existing beliefs rather than actual information. Companies that prioritize transparency and the creation of value and make customers fully understand the benefits are more likely than another organization to build that trust and loyalty. Organizations that have useful data strategies help build a better balance between using customer information while also listening to their privacy concerns.

Profiling Example

SELECT Categories.CategoryName,
SUM(Products.UnitPrice * "Order Details".Quantity) AS total_revenue
FROM Customers
INNER JOIN Orders
ON Customers.CustomerID = Orders.CustomerID
INNER JOIN "Order Details"
ON Orders.OrderID = "Order Details".OrderID
INNER JOIN Products
ON "Order Details".ProductID = Products.ProductID
INNER JOIN Categories
ON Products.CategoryID = Categories.CategoryID
WHERE Customers.CompanyName = "Around the Horn"
GROUP BY Categories.CategoryName
HAVING SUM (Products.UnitPrice * "Order Details".Quantity) > 0

ggplot(data = myquery1,
       aes ( x = reorder(CategoryName, total_revenue),
             y = total_revenue)) +
  geom_col() +
  labs(
    title = "Around the Horn Revenue by Product Category",
    x = "Product Category",
    y = "Total Revenue"
  )

Recommendations for Industry

Some recommendations for organizations are that they need to come up with an approach on how to manage and collect data by focusing on the customer and putting their best interest at heart. Even though collecting customer information can create great value, organizations need to understand how much success they can have for the long road if they build customer trust and loyalty. As said in the readings, organizations need to prioritize clear communication, not only what data is being collected but also how it is being used. Also, organizations should allow customers to have priority over their own personal information. Organizations need to put a priority on creating value in hopes for that customer data. Organizations should increase accountability when using this customer data because it will show to the customers that they are being put first. Finally, organizations need to look at customer data that is a relationship created by trust, not just something that is collected.

References

Morey, T., Forbath, T., & Schoop, A. (2015). Customer data: Designing for transparency and trust. In Harvard Business Review. https://hbr.org/2015/05/customer-data-designing-for-transparency-and-trust

How Retailers Became Ad Platforms. (2024). In Harvard Business Review. https://hbr.org/2024/06/how-retailers-became-ad-platforms

Ward, L. (2024). Beware When a Company Says It Is Trustworthy. In WSJ. The Wall Street Journal. https://www.wsj.com/finance/investing/ethics-companies-trust-b182f2b5

Disney’s Magical Big Data Transformation - Digital Innovation and Transformation. (2023). In Digital Innovation and Transformation. https://aiinstitute.hbs.edu/platform-digit/submission/disneys-magical-big-data-transformation/