Data Storytelling | Dataset on Customer Complaints Part 2
Uncovering Key Trends and Insights in Consumer Complaints
Recap of the Problem Scenario
Delivering a positive customer experience is crucial for any business, especially in the financial services sector. In Part 2 of this project, I explored the Customer Complaints Database to uncover valuable insights that could help the Consumer Financial Protection Bureau (CFPB) improve customer service.
As an “analyst” working with CFPB, my goal was to analyze the data, identify trends and patterns, and present these findings to the COE within CFPB through a comprehensive storyboard.
Exploration & Visualization
After visualizing and exploring the dataset in Tableau, I identified several inconsistencies and areas where grouping was needed. These changes were essential for improving the overall interpretation of the data, ensuring that the insights provided are both meaningful and actionable.
Data Cleaning and Inconsistencies
While analyzing the dataset, I noticed some inconsistencies, especially with similar variables like ‘mortgage’ and ‘mortgages’, or ‘debt collection’ and ‘debt collections’. These variations were apparent during the data exploration process in Tableau. To ensure consistency across the dataset, I cleaned these discrepancies by standardizing the terms.
Grouping for Better Interpretation
The Product column contained a wide variety of products, which could be grouped to provide a clearer and more concise analysis. I discovered that there were 18 different products in the column, many of which had similar content. To simplify the dataset and enhance its interpretability, I grouped these products into 8 categories.
For example:
- Credit Reporting is grouped under Credit Card Services.
- Customer Loan is categorized under Loan Services.
This grouping technique helped streamline the dataset, making it easier to analyze and interpret the results.
Parameters for Interactive Analysis
A parameter is a workbook variable that replaces a constant value in a calculation, filter, or reference line. Unlike filters, which work at the worksheet level, parameters can be used across multiple worksheets within the same workbook. Parameters enhance interactivity, allowing users to narrow down the data or control inputs to observe the effects in real-time.
For this project, I created two key parameters:
- Top N Parameter: This parameter allows users to filter and interact with the graph by displaying the top N results based on a chosen metric.
- Dynamic Dimension Parameter: This parameter allows users to select a product dynamically. By using this parameter, users can interact with different types of graphs and update the displayed data based on their selection.
Big Idea:
The Big Idea is to identify the most common and similar products that are frequently mentioned in consumer complaints and introduce effective measures to resolve these issues. The primary goal is to educate and empower customers, helping them make informed decisions about financial products and services.
By addressing these recurring complaints, we can enhance the overall customer experience and satisfaction. Taking proactive steps will not only prevent complaints from escalating but will also help build trust between companies and consumers. If left unaddressed, however, the number of complaints is likely to increase over time, leading to greater dissatisfaction and potentially damaging the reputation of financial institutions.
StoryBoard:
- Introduction
Over the last five years, from 2016 to 2021, the number of consumer complaints has seen a significant increase, rising from 189,964 complaints in 2016 to 461,303 complaints in 2021. This upward trend highlights an ongoing issue that needs urgent attention.
Hook: If trend continues, by the end of 2022, it will reach to more than 500,000 complaints
The goal of this analysis is to identify the most common products that receive the highest volume of complaints. By pinpointing these issues, we can take targeted action to address and rectify them, ultimately minimizing the complaints and improving the overall customer experience.
2. What are they complaining about?
To analyze the trends in consumer complaints, I used a stacked bar chart to represent the breakdown of product groups over the years. This chart helps visualize the composition of each product group for a specific year, allowing us to track how the distribution of complaints changes over time.
In this chart, the horizontal axis represents the years, while the vertical axis shows the percentage of total complaints for each product group.
From the chart, it’s evident that the percentage of complaints related to credit card services has been steadily increasing across the years. This rising trend calls for a deeper look into the specific products under the credit card services category. Let’s drill down further to identify which products are driving this increase in complaints.
3. Drill down to Credit Card Services
As we drill deeper into the credit card services category, we observe a significant number of complaints stemming from “credit reporting, credit repair services, or other personal consumer reports”. This stands out as a major contributor to the rising complaint trend.
To better understand the specific issues, we need to examine this column further and identify which products within this category are receiving the most complaints. By isolating the key products causing these complaints, we can take targeted action to address them effectively.
As seen in the chart above, credit reporting stands out with a high percentage of complaints. Interestingly, there is also 9.03% labeled as N/A. During the data cleaning process, we discovered that the ‘credit reporting’ product did not have any associated sub-products, leading to missing values. To address this, we replaced the missing values with N/A.
Thus, the N/A in the graph can also be directly linked to credit reporting, which means that more than 90% of complaints in the credit card services group are related to credit reporting.
Now, we need to delve deeper into the issues and sub-issues within the credit reporting category to understand the specific concerns consumers are facing. Let’s explore these further to pinpoint the main causes of dissatisfaction.
As seen in the dashboard, a significant number of complaints are related to incorrect information on consumers’ credit reports. Specifically, the top sub-issue is that the information belongs to the wrong person.
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To gain more insight, you can hover over the issues in the dashboard, and the top sub-issue tooltip will appear, showing exactly what the most common complaints are under this category. This interactive feature makes it easy to pinpoint the root causes of the complaints and helps in identifying patterns for further investigation.
4. Climax
To gain insights into future trends, I used forecasting techniques to predict what the complaint numbers will look like in the next two years. Below, I’ve outlined the options I used for the forecast. To connect the actual data and the forecasted estimate, I changed the dimension to attribute, which allows for a clearer comparison.
The goal of forecasting is to calculate future data points based on historical trends, enabling us to make informed predictions about the direction of complaints. By looking at these projected trends, we can proactively plan to reduce future complaints and improve customer satisfaction.
In the line graph below, the blue line represents the actual data collected from the past years, while the purple line indicates the estimated future trend of complaints. This comparison allows us to visualize the anticipated increase in complaints and helps in strategizing solutions to address the rise.
As shown in the graph above, if the current trend continues, the number of complaints is projected to reach 623,552 by the end of 2023. This alarming increase highlights the need for proactive measures to address consumer dissatisfaction.
So far, we’ve analyzed complaints at a more generic level, focusing on products, sub-products/issues, and sub-issues. Now, let’s drill down further and examine complaints in more specific terms, breaking them down by companies and states. This will allow us to pinpoint the key areas contributing to the increase and identify opportunities for targeted improvements.
5. Falling Action:
State-wise Complaints
On the side of the dashboard, there is a Product Group Filter that allows you to filter the states and companies based on the selected product group. By selecting a state in the worksheet, the filter automatically updates the other worksheets, providing a comprehensive view of the data.
As you explore different states, it becomes clear that the highest number of complaints come from the credit card services product group. The top three companies receiving these complaints are Equifax Inc., Transunion Intermediate Holdings Inc., and Experian Information Solutions Inc..
The states with the highest number of complaints are:
- California: 232,694 complaints
- Florida: 210,498 complaints
- Texas: 187,212 complaints
This state-wise breakdown highlights the areas that require immediate attention and action to reduce complaints in specific regions.
Companies Wise Complaints
Looking more in depth in the companies, I created a visualisation showing the top 10 companies with the highest volume of complaints, along with the monthly count of complaints over the years. Additionally, I included a pie chart to illustrate whether the customer disputed the complaint or not.
You can interact with the company line graph to view the monthly complaint count for each individual company. This feature allows for a more granular analysis of complaint trends over time.
From the dashboard, we can observe that the top three companies with the highest volume of complaints are:
- Equifax
- Transunion International
- Experian Information Solutions Inc.
However, there is an important caveat regarding the customer dispute data. With 80% of the dataset labeled as N/A for customer disputes, it becomes challenging to draw reliable conclusions about whether a customer disputed their complaint or not. This high percentage of missing or unknown data diminishes the usefulness of this field for further analysis.
Recommendation:
- All companies need to reduce customer complaints raised in Credit Card Services.
2. Introduce measures to reduce complaints for credit card services specifically by 50% in 2 years
5. Narrative Framework Conclusion:
6. Data Findings & Recommendation
The Credit Card Services category has seen a significant increase in complaints across various states, with a broad range of issues being reported. This growing trend highlights the urgent need for the Consumer Financial Protection Bureau (CFPB) to take action and introduce measures aimed at reducing complaints within the credit card services group by 50%.
By addressing the most common issues faced by customers, CFPB can make a significant impact on the marketplace, improving overall customer satisfaction and trust in financial services.
Given the high volume of complaints within the credit card services group, it will require substantial manpower to address these issues if AI is not leveraged. In this case, it is crucial for CFPB to establish a dedicated team to manage and resolve these complaints efficiently.
Another key recommendation is for companies to provide timely responses to all customer complaints. Ensuring a quick and thoughtful response will directly impact customer satisfaction. Complaints that do not receive timely responses often escalate, leading to greater dissatisfaction.
For complaints that have not received timely responses, CFPB should collaborate with the companies involved, reminding them to provide prompt responses. Additionally, CFPB can work on strategies to reduce response delays and improve overall customer satisfaction.
By increasing the number of timely responses, we can significantly reduce the number of disputed complaints, leading to better overall customer satisfaction and improved customer relationships.
7: Conclusion
In conclusion, the analysis of the Customer Complaints Database has highlighted critical areas where improvements can be made to enhance customer experience in the financial services sector. By focusing on the credit card services group, identifying key issues, and forecasting future trends, we can proactively address rising complaint volumes.
Implementing AI solutions to manage complaints efficiently and creating a dedicated CFPB team will help alleviate the pressure caused by high complaint volumes. Moreover, ensuring timely responses from companies will play a significant role in improving customer satisfaction and reducing complaint disputes.
Through these measures, CFPB can effectively reduce complaints, improve customer relationships, and contribute to a more customer-centric marketplace.
