Adoption of IBM SPSS to Support Customer-Oriented Sales Activities
Achieved Improved Contract Rates, Streamlined Data Analysis, and Cost Reduction
Founded on March 1, 1888, Asahi Mutual Life Insurance Company (hereafter referred to as Asahi Life) celebrated its 130th anniversary in March 2018. With “sincere service” as its core management philosophy, Asahi Life consistently offers comprehensive insurance products tailored to meet customer needs. The company has pioneered the industry, winning the Good Design Award for the first time with its “Anshin Kaigo” long-term care insurance for seniors in 2013. Asahi Life continues to expand its business, focusing on services targeted at women and mid-sized business owners.
As a company that has long been engaged in building information systems such as data warehouses and CRM, Asahi Life leveraged its accumulated data in a “data analysis project” aimed at supporting sales activities. By adopting IBM SPSS (hereafter referred to as SPSS), the company achieved significant results, including an increase in contract closing rates, improved efficiency in data analysis tasks, and cost reductions.
Challenges Before Introducing SPSS: Maximizing the Use of Existing Accumulated Data to Support Sales Activities
Asahi Mutual Life Insurance Company, which provides “peace of mind” to both individual and corporate clients through its life insurance business, currently focuses on three key customer segments: senior citizens, women, and small to medium-sized business owners. Guided by its fundamental philosophy of “service with sincerity,” the company aims to create a top-quality salesforce that offers exceptional customer support. In pursuit of this goal, Asahi Life has proactively built a strong data infrastructure from early on to maximize data utilization in its operations.
Regarding data utilization at Asahi Life, Mamoru Shimada from the Sales Planning Department explains, “We began building the foundation for data utilization fairly early, starting with the implementation of a Data Warehouse (DWH) in 2001 and the creation of a CRM system called ‘ACTION’ in 2012.” These systems were developed with the aim of integrating customer information—including household data and all interaction points between Asahi Life and its customers—such as call centers, sales activities, and the company’s website. The goal of this integration was to maximize sales efficiency by leveraging all data accumulated in the ACTION system.
A few years ago, the “Data Analysis Project” was initiated. This project involved a limited-time pilot implementation of an analytical system to establish an in-house data analysis structure and to verify whether effective analytical work could be achieved. While some results were obtained, it was determined that the outcomes were not sufficient to cover the associated implementation and operational costs, leading to a reevaluation of the project. However, the analysts involved felt confident that if the cost-related challenges could be addressed, they could successfully establish an in-house data analysis capability. Consequently, the company began searching for new analytical products that could leverage the analytical capabilities it had developed over time.
Amidst this situation, the company learned about a seminar on SPSS hosted by AIT. They sent two representatives to participate in the seminar, where they compared their experiences with the other products they were using at the time and the features those products could offer. As a result, the advantages of SPSS became evident in various aspects, leading the company to decide to conduct a proof-of-concept trial using SPSS as part of a reevaluation of the “Data Analysis Project.”
Background of SPSS Adoption: The company decided to adopt SPSS after evaluating its essential features, which are provided as standard, and appreciating that there was no need for additional programming languages.
A significant advantage identified for SPSS was its “variable selection feature.” Mr. Shimada stated, “In the previously trialed competitor products, this feature was not available, and we had to use a tool developed by an external consulting firm for variable selection. Transforming the data format was also necessary to conduct actual analysis, requiring programming in a system-specific language. With SPSS, we found that we could configure settings through the GUI rather than programming, which was a major advantage. Moreover, SPSS provides standard functionality for classifying data with optimal thresholds. In our case, we needed to set 600 to 700 thresholds for the data we were analyzing, making manual handling virtually impossible.”
Additionally, Mr. Kamiya from Asahi Life’s Sales Planning Department mentioned the language of the screen display, stating, “In other companies’ systems, only English is available, but with SPSS, everything can be handled in Japanese. This is a significant advantage in terms of user convenience.”
After deciding to evaluate SPSS, the company conducted a Proof of Concept (PoC) using both SPSS and another company’s product. Mr. Shimada commented on the results, stating, “With the other company’s product, data formatting had to be adjusted to fit the product’s unique specifications, and the specialized development language required for this was a significant hurdle for our employees. In contrast, SPSS allows input in common data formats like EXCEL and TEXT files without the need for coding or any special development language. This significantly reduced the time and effort required for preliminary preparations before analysis.” Through the evaluation process, the company recognized the advantages of SPSS and began its operational use in actual business activities.
Effects of SPSS Implementation: The introduction of SPSS has led to remarkable results in sales activities through the utilization of analysis outcomes. It has also achieved efficiencies in operations and cost reductions.
The effects of SPSS implementation have clearly manifested in two aspects. One is the improvement in sales performance achieved through the use of the newly established analytical framework. The other is in operational efficiency, where the workload, time, and costs associated with this initiative have been reduced compared to previous levels.
Regarding the effects on sales activities, Mr. Shimada stated, “In the cross-selling of the ‘Anshin Care’ insurance, we divided the target customers into two groups. One group of sales representatives received a simple customer list, while the other group was given a list marked with analysis results indicating customers with a high intention to enroll, based on behavior history and attribute information. The necessary data for the analysis was sourced from the data accumulated in the ACTION system. When we compared the top 10% from each group, it became clear that the sales group with the list of highly promising customers was achieving significantly better results than the other group. This difference was very pronounced; when we quantified the increase in contracts attributed to using the analysis list, it exceeded the total investment amount of this project, including the previous fiscal year. Additionally, for the sales team, SPSS’s decision tree analysis was very intuitive, providing new insights and a strong sense of conviction in the data analysis results, which was highly appreciated.” This fully met the expected benefits that were anticipated for the project’s reimplementation.
On the other hand, significant implementation benefits were also realized in terms of project operation load, time, and costs. Mr. Kamiya remarked, “Due to the very tight project schedule, we were unable to prepare the data needed for the logistic regression analysis we had previously conducted, which necessitated a sudden switch to decision tree analysis. However, with SPSS, there was no need for external consultants or development language requests. The intuitive operation and the Japanese-language UI allowed us to respond quickly and accurately on our own, which I consider a major implementation benefit.”
The success of this project not only provided benefits from a standalone initiative but also brought significant advantages in terms of maximizing the company’s past IT investments (such as DWH and CRM), which they had anticipated.
Future Outlook: Planning to Regularly Implement All Initiatives and Expand to Other Areas
The recent project has yielded significant results that meet expectations, and Asahi Life is already considering expanding the application of the “prospective customer list” utilizing SPSS. “Until now, we have positioned this as a spot trial implementation, but moving forward, we plan to apply data analysis using SPSS to all initiatives carried out regularly throughout the year. We aim to create models each time with the support of IBM and AIT, gradually changing the targets to facilitate horizontal expansion,” says Mr. Shimada.
Additionally, the company is considering the horizontal expansion of initiatives within the organization to include areas beyond sales and marketing, such as underwriting and new product development, utilizing data analysis. There has been increasing demand within the company for the application of AI and machine learning, and SPSS is well-equipped with robust machine learning models. This means that SPSS can potentially meet future needs for “automated decision-making,” and its range of applications is expected to expand even further.
Finally, Mr. Shimada mentioned AIT’s contributions, which were instrumental in the success of this project, and concluded with the following remarks, including the challenges faced during the project: “In fact, during the initial internal presentation of the analysis, we struggled to gain the understanding of the members from the department overseeing sales. As a result, when it became necessary to remake the initial model, AIT assigned multiple team members to assist us, working through the year-end and New Year holidays to help recreate the model. Additionally, they emphasized the necessity of internal analysis conducted by our own team to gain acceptance of the analysis results, providing us with the support needed for that. I truly appreciate AIT’s significant contribution in helping us build an analytical system with a level of service we never thought possible, which has led to the remarkable results achieved in this project.”
Asahi Life Insurance continues to provide services and insurance products that are always focused on customer needs. SPSS serves as the core of the analytical foundation that supports the efforts of each sales representative in considering the most suitable actions for every customer, maximizing its utilization daily to enhance customer satisfaction.
*Interview conducted in October 2017.
Company Profile: Asahi Life Insurance Mutual Company
| Location | Asahi Life Insurance Otemachi Building, 6-1, Yotsuya 1-chome, Shinjuku-ku, Tokyo 160-8570 |
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| Business Overview | Asahi Life Insurance provides “peace of mind” to individual and corporate clients through its life insurance business. Currently, the company focuses on three customer segments: seniors, women, and mid-sized business owners. |
You can download the PDF of the IBM SPSS case study for Asahi Life Insurance Company from the following link: Download PDF.