*Net Promoter® and NPS® are registered trademarks of Bain & Company, Inc., and Fred Reichheld, and Satmetrix Systems, Inc.
Yoshimi Kamachi (hereafter, Kamachi): Our mission is to provide appropriate after-sales service to overseas customers who purchase our home appliances. Ultimately, we believe that one of our roles is to optimize services from the customer's perspective and contribute to creating fans of our company.
That said, it is the local sales companies that directly communicate with customers. So, we in Japan support improving and strengthening the operations of contact centers and after-sales services deployed by each sales company.
Kamachi: The local sales companies have accumulated vast amounts of VoC through customer communication, such as contact center activities. However, while we were aware of the increasing emphasis on CX improvement in recent years, we could not fully utilize VoC, which became a challenge.
While these sales companies were motivated to utilize BI tools to aggregate metrics such as post-customer interaction NPS® and the number of cases by channel, this only allowed us to grasp general trends. To link this information to CX improvement, it was necessary to properly analyze all data, including comments, and delve deeper into customers' feelings. However, with limited resources, it was challenging to capture all comments. For example, we were so focused on capturing and responding to customer complaints that we couldn't pay attention to all the comments, including compliments, even though we knew we could uncover clues for CX improvement hidden in those comments.
One day, one of our sales companies in Brazil contacted us, asking, "Is there any way to properly analyze the comments we receive from customers and utilize them for CX improvement?" I believe it was in the first half of 2022.
Kamachi: When we received the inquiry from the sales company in Brazil, we were also unsure of what to do. Just then, Nikkei Research, which had business dealings with our Consumer Marketing Division, held a workshop for our company. I had the opportunity to participate and consult with their personnel. That was the start of the project.
Kamachi: The first thing that came to mind when I saw the analysis results was, "Of course, that makes sense." However, there is a significant difference between perceiving something intuitively and having it revealed by data. The value of data analysis is that it clarifies priorities. With limited budgets and resources, it became clear what to tackle first.
Kamachi: The analysis report included specific proposals for priority measures, which was very helpful, and we sent it to the local company as feedback. We don’t know the details of the actual measures the local sales company implemented. However, it seems the feedback was useful for various improvement activities, not only for training contact center operators and repair technicians on customer interactions but also for optimizing the distribution environment, which had received many customer complaints.
In a similar analysis conducted the following year, the NPS® of the prioritized areas improved significantly, and the overall NPS® results were also favorable. So there is no doubt that the improvement activities based on the analysis results were successful.
Kamachi: We requested similar analyses because our sales companies in the EU could also only grasp general trends regarding VoC and NPS®.
The analysis revealed that resolving customer dissatisfaction with the website, such as "the method of registering warranties on the website is unclear" and "we want the website to be more mobile-friendly," is a high priority for increasing NPS®. The local sales company was aware of this issue, secured a budget, and was about to move into the implementation phase. Addressing such needs incurs considerable costs but knowing that the data analysis results matched their thinking gave them more confidence to take action and assured them that the investment was not a mistake.
Currently, they want to re-analyze the situation after implementation to see the improvement has resolved issues.
Kamachi: We provided feedback on the analysis reports in English to the local teams. However, it was helpful that they could refer to the original data in the local language linked to the analysis results when they wanted to delve deeper. This feature was particularly beneficial in EU countries, where different languages are used.
What I like about KeyExplorer is that the accuracy of the analysis is exceptionally high. While some of our business units use text mining tools in their operations, we often hear that "the results from using a text mining tool were not as expected." However, I don’t get that impression from the KeyExplorer’s result. The results are convincing so we can use them with confidence.
Kamachi: When I briefed my colleagues on this initiative, some domestic CS personnel seemed interested in KeyExplorer. They mentioned that they could use it in various ways in their work.
Kamachi: For the initiatives in Brazil and the EU, we at the Sales Company Support Center requested analysis from Nikkei Research and provided the companies with feedback on the results. In the future, we would like the local sales companies to take the initiative to learn how to use KeyExplorer and analyze it independently, which will speed up decision-making and eliminate time lags in evaluating and improving measures.
Kamachi: VoC is a hidden treasure trove of clues for achieving customer satisfaction. Its analysis will reveal those clues that support what we aim to do. It is critical because we cannot act based on "just a feeling." We hope not only to collect data but also to utilize it effectively and develop it to the point of creating fans for our company.