DataScience for Growth: Marugame Seimen's Method for Maximizing "Winning Probability" Through Data Science – The Key to Decision-Making That Overcomes Uncertainty [MarkeZine Day 2026 Spring Event Report]

In this "Adapt & Advance" era, where all conventional wisdom is being rewritten, it is extremely difficult to continue adapting solely based on past successes and "rules of thumb." How is Marugame Seimen, which continues to grow amidst these challenges, adapting to this uncertain market and taking on new challenges?

The key, they say, lies in the marketer's sharp "hypotheses" and the improved win rate that support them through "data science."

On March 3, 2026, at "MarkeZine Day 2026 Spring," an event covering the current state of marketing held in Tokyo, Toru Manabe, General Manager of the Experience Design Department at Marugame Seimen's Marketing Division, and Motonobu Takagi, General Manager of the Data Science & Analysis Department at XICA's Consulting Division, took the stage to discuss "Marugame Seimen's approach to maximizing the 'winning rate' through the use of data science," which they are working on together.

This report will introduce the contents of the sessions held on the day.

*Titles are as of the time of the event.

Why you need "data science"

Marugame Seimen's slogan is "Fill this planet with the joy of food." For a company that makes its udon noodles from scratch in every store, emphasizing handmade and freshly prepared food, efficiency is not the top priority. Instead, it's about creating "KANDO" (emotion/inspiration) that touches the hearts of its customers. But why did the company introduce data science into this subjective realm of "KANDO"?

The reason lies in their strong commitment to sustainable growth."While you might win once, to 'keep winning,' reproducibility is crucial, and that's where data science comes in."That's what Mr. Manabe said.

While pursuing "KANDO," we maximize the "winning percentage" through data.Balancing sensibility and data scienceThis is the source of the company's strength. As a symbolic example, Takagi, who leads XICA's data science and analysis team, introduced Marugame Seimen's data-driven approach to marketing.

Initiatives supporting Marugame Seimen's "inspirational management"

What is particularly noteworthy about Marugame Seimen's approach is its management strategy of "emotional management," which aims to create memorable experiences.Customer Experience (CX)In addition to creating,Employee intrinsic motivation (EX),Creating inspiring experiences for the community (Social Good)It embodies the "win-win-win" principle, which integrates all of these elements. And these elements have come to fruition.A brand that creates truly unique and unforgettable experiences.This structure is built upon, leading to prosperity (success).

Marugame Seimen's approach to data science management involves improving reproducibility through structural analysis of this "creation of emotional impact" cycle. Below, we will introduce the "strategic management model" and the "happiness and emotional impact model verification."

■ Strategic Management Models — "MMM" and "CMM (KSF Analysis)"

The initiatives of both companies are"MMM (Marketing Mix Modeling)Analysis connecting policies and results using "[ ]"It all started with a project to visualize how each initiative contributed to sales and to assess its return on investment.

continue,"CMM (Consumer Mix Modeling)This allows us to identify Key Success Factors (KSFs).This study utilized survey data to statistically analyze brand awareness, which influences performance indicators (in Marugame Seimen's case, "frequency of visits"). What became clear was that the biggest factor influencing frequency of visits is "intention to visit," and that this is supported by the element of "the udon is delicious." Digging deeper, it was discovered that "high quality" is important as a component of that deliciousness, and at its core, the key is the unique value of "being able to eat with peace of mind" and "having a quality that sets it apart from other restaurants."

Regarding these results, Mr. Manabe reflected as follows:

"As a noodle factory, it's perhaps natural that we're supported by the image of having delicious udon noodles. However, among the various policies we could consider, we believe that pursuing this to the fullest extent is the right thing to do."The significance of data backing."I feel it's a big deal (Mr. Manabe)."

By developing branding and product promotions that precisely address these key drivers, these activities will eachVisualize the extent to which key drivers are being affected using MMM.By structuring it as shown in the diagram below, we ensure reproducibility for "continuing to win."

■ Happiness Emotion Model

Furthermore, the company stated that "employee happiness is the source of creating customer satisfaction,"Verification of the "Happiness-Emotion Model," which structures "Happiness → Emotion → Prosperity"We also do this.

The key to success lies in the structural modeling of the relationship between "employee happiness" and "customer satisfaction," which in many companies tend to remain mere ideals, and "business results." By objectively demonstrating with data how the state of "mind," which has previously been difficult to quantify, connects to business impact, they are enabling investment decisions based on scientific evidence rather than remaining mere ideals.

Even more astonishing is the speed at which they built a data collection platform for all stores in less than a year from conception. Not only did they prove that employee experience (EX) contributes to customer experience (CX) and ultimately leads to results, but they also thoroughly focused on reproducibility, such as calculating the increase in sales for the next year from the current scores.

Takagi, who is working alongside them as a partner, described the remarkable aspects of this initiative as follows:

"Even in areas where data science can penetrate to such an extent that it's surprising,Having a firm hypothesis and the ability to collect all the necessary data."That's what I strongly believe. It's that sincere approach that allows them to translate data, as a weapon, into concrete results (Takagi)."

▶For details of the initiative,This releaseto check more details.

What is a "decision-making mechanism" that increases the win rate?

While Marugame Seimen incorporates data science into every aspect of its business to unravel its structure, its true essence lies not in the analysis itself, but in its "decision-making mechanism." We will summarize the key points for maximizing the chances of success even in uncertain environments, based on Mr. Manabe's words.

In response to Takagi's question, "Given the various data and challenges, how do you prioritize your initiatives?", Manabe said:"The magnitude of the business impact"With that in mind,"Whether or not they will take action (make a move)"They emphasize that this is their top priority. A common example of failure in data utilization is the case where "we've analyzed the data, but we don't know what to do next," but to prevent this, the company says,Before starting the analysis, clearly articulate your "decision-making criteria."They are thorough in what they do.

Mr. Manabe emphasizes the following:

"For example, when the number '10' comes up, different hypotheses will lead to different interpretations. That's why,Clearly articulate your hypothesis, share your interpretation, and involve all stakeholders."This is essential. If a solid hypothesis and interpretation are shared, it becomes a powerful 'weapon' to move the organization, regardless of whether the analytical method is sophisticated or not (Manabe)."

In business, waiting for a "100% correct answer" can be too late, but if you have a plan like this, where you decide "if this number comes out, we'll act in this way"...A scenario (hypothetical course of action) was agreed upon with the stakeholders.Doing so creates an overwhelming sense of speed in decision-making.

Finally, to conclude the session, Takagi described the current market environment as one in which "a large amount of data can be collected, but uncertainty is actually increasing." He then concluded by outlining the role of data science in navigating an uncertain future.

"We need to take a step forward, identify potential solutions, and ensure that we can take the best course of action according to the scenario, regardless of the outcome.Data science as a predictive tool"We hope you will utilize it in this way. When the 'instinct' of a marketer's keen hypotheses and the 'science' of data science come together, the chances of business success will be maximized (Takagi)."