Analysis Report Three - Privacy and Customer Profiling

Executive Summary

Organizations are very dependent when it comes to information on their customers. This allows the organization to grow while collecting data and improving decision making. Though collecting data isnt capable of supporting long term sustainability, having customer trust is what support long term sustainability for improving through collecting customer data. The readings in this past week highlighted how organizations need to communicate and be more clear with customers about their intent with data in order to have a more trusting relationship between the business and it’s customers. Organizations also need to create a value when it comes to customers information and what specific information will be collected for an activity. Also, as AI increases into organizations their top priority is data strategies for offense and defense. Organizations need to continue to reinvest into how they maintain data defense through high data governance and high quality data.

Introduction

Organizations depend on the customer data to improve their performance, personal services, and strategic decision making. As organizations continue to collect customer information through AI and technology, these organizations also need to have a healthy balance for innovation from humans to help with decision making from the AI. The past weeks reading focuses on the transparency, customer trust, and data defense with strong governance to establish a strong data strategy. Organizations that communicate with the customer about what information is being collected can help establish a long term sustainability through customer trust.

Privacy vs Profiling

Organizations need to continue to collect customer data to improve their strategic decision making, customizations, and recommendations. But, collecting customer data for these companies also creates a privacy risk and concern for the customer whenever the organizations dont properly communicate. The HBR article focuses on how companies need to communicate with their customers and spread simple knowledge in order to gain long term trust and sustainability in the organizations. One example would be in the previous weekly video where Uber was using their customer data in a way were it create privacy concerns and risk from customers about the most popular cities with the highest one night stands count on valentines day. Lastly, this overall weekly readings highlight how organizations need to reinforce clear and concise communication to their customers in order to create better sustainable customer trust.

Profiling Example

The selected profiling example highlights on the customer, which is “Around the Horn”, from the North wind database. North wind can have better decision making when understanding the trends of data collected.

Visualization 1

This visualization focuses on the individual freight charges for orders placed by the customer “Around the Horn.” Each bar represents a separate order, while the y-axis shows the freight cost connected to that order. This gives Northwind the ability to review the customer’s individual shipping costs before grouping the data by employees.

SELECT Employees.LastName, SUM(Orders.Freight) AS TotalFreight
FROM Customers, Orders, Employees
WHERE Customers.CustomerID = Orders.CustomerID
AND Orders.EmployeeID = Employees.EmployeeID
AND Customers.CompanyName = 'Around the Horn'
GROUP BY Employees.LastName;

ggplot(data = myquery,
       aes(x = LastName,
           y = TotalFreight)) +
  geom_col() +
  labs(
    title = "Total Freight by Employee",
    x = "Employee",
    y = "Total Freight"
  )

Visualization 2

The visualization above focuses on the number of orders that were shipped by each company for the customer who is “Around the Horn”. Using the shipping company to group the data allows the organization to indicated which carrier is being used the most which can lead to better strategic decision making. The United Package handled the highest number of orders compared to the rest of the shipping companies which were “Federal Shipping” and “Speedy Express”. Lastly, the visualization allows the organization to gather data on the customer’s information to build and support better decision making for the future.

SELECT Shippers.CompanyName, COUNT(*) AS NumberOfOrders
FROM Customers, Orders, Shippers
WHERE Customers.CustomerID = Orders.CustomerID
AND Orders.ShipVia = Shippers.ShipperID
AND Customers.CompanyName = 'Around the Horn'
GROUP BY Shippers.CompanyName

ggplot(data = myquery2,
       aes(x = CompanyName,
           y = NumberOfOrders)) +
  geom_col() +
  labs(
    title = "Orders by Shipping Company",
    x = "Shipping Company",
    y = "Number of Orders"
  )

Recommendations for Industry

Overall, Organizations need to prioritize being clear and communicating what customer information is being collecting and for what reason. When the organization allows customers to have control on what they share, that creates value and trust between the organization and the customers. As the organizations continue to collect information through AI and customer personalization, they need to mainly invest in the strong data strategy to support offense and defensive strategies like high quality data and governance. Organizations can improve their decision making while gaining customer trust and long term sustainability.

References

(article?){dallemule2017s, title={What’s your data strategy}, author={DalleMule, Leandro and Davenport, Thomas H}, journal={Harvard business review}, volume={95}, number={3}, pages={112–121}, year={2017} }

(article?){dobkin2018information, title={Information fiduciaries in practice: data privacy and user expectations}, author={Dobkin, Ariel}, journal={Berkeley Technology Law Journal}, volume={33}, number={1}, pages={1–52}, year={2018}, publisher={JSTOR} }