XICA MARKETING SCIENCE LAB (hereinafter referred to as MS Lab) is a community that aims to explore "optimal decision-making" in marketing. A free event exclusively for members was held at the Tokyo venue on Thursday, November 2025, 10.

The event was divided into two parts: a "seminar" where cutting-edge information and success stories on data-driven marketing were shared, and a "lab" where practical knowledge was generated through two-way communication between the seminar speakers and participants. This article reports on some of the content of the seminar.

Speakers/panelist:

*Titles are as of the time of the event.

Mr. Masaharu Hayashi
CMO and Head of Marketing, Pizza Hut Japan Co., Ltd.

After graduating from Daito Bunka University, he joined Kentucky Fried Chicken Japan Ltd. in 2002.
He was assigned to the Pizza Hut division and has consistently worked in the sales field, from staff member to store manager, supervisor, franchise sales manager, and sales director.
In 2017, he was appointed COO and General Manager of Sales following the spin-off of Pizza Hut Japan Ltd. He led the operation development and POS system renewal as the project owner.
From 2024, he will oversee the marketing department as CMO.

Moderator

Yoshiaki Hirao
President and CEO of XICA Corporation

A graduate of Keio University, Faculty of Policy Management. Yoshiaki witnessed the banruptcy of his father's company, and this drove him to discover the potential of management support through statistical analysis in university. He founded XICA Co., Ltd. in February 2012. Based on his background in statistics and economics, he has provided extensive marketing consulting services to a number of major clients, and he has served as a product owner in the development of various products at XICA.

table of contents

Expanding delivery market and intensifying competition

Pizza Hut is a growing pizza chain with over 610 stores nationwide. In recent years, the pizza delivery market, including pizza, has continued to expand due to the establishment of telecommuting and the increase in dual-income households. However, competition has intensified due to the spread of food aggregators (services that allow customers to order from multiple restaurants from a single app) and the sale of low-priced pizzas at convenience stores and supermarkets. Furthermore, the industry has been hit hard by rising raw material and labor costs. Diversifying values ​​and touchpoints have made it difficult to change customer attitudes by simply focusing on traditional, uniform marketing.

In this challenging environment, Pizza Hut is aiming to achieve long-term profit growth by improving its brand power, and is focusing on optimizing not only the quantity (investment) of marketing, but also the quality (strategy).

As part of this effort, this seminar shared examples of optimizing both quantity and quality through data-driven marketing, maximizing the cost-effectiveness of marketing and increasing brand power through building ongoing relationships with customers.

Why Pizza Hut is focusing on data-driven marketing

The challenges that Pizza Hut faced in the tough market environment can be broadly divided into two categories.

The first issue was a lack of ROI visualization and evidence for optimal allocation of advertising investment. Although the company revamped its communications based on a new brand strategy in 2024, it lacked objective data to assess the results of its initial advertising initiatives.

The other issue was that there was a lack of evidence to support the validity of the strategy to strengthen the brand. There was also the issue of the lack of visible impact on the results of the new brand strategy.

So, first of all, to address the issue of "lack of evidence for visualization of ROI and optimal allocation of advertising investment,"MMM (Marketing Mix Modeling)We utilized the "ROAS" tool to visualize the ROAS of each advertising initiative and work to calculate optimal budget allocation.

Visualize ROAS for each advertising measure and optimize investment

MMM is a method of statistically analyzing and visualizing the extent to which various marketing initiatives, such as television commercials, digital advertising, sales activities, and promotions, contributed to results such as sales and conversions.

This time, an analytical model was created using the number of purchases as the outcome. It quantified not only the "direct effect" of each measure on the results, the "indirect effect" that spreads to other measures and KPIs, and the short- to medium-term "residual effect," but also the "long-term effect (brand accumulation effect)" that accumulates over the long term.

Data-driven strategy optimization

However, quantitative analysis alone was limited in its ability to clarify the reasons why the new strategic communication did not produce the expected results. Therefore, the next step was to analyze the quality of the communication.CMM (Consumer Mix Modeling)By utilizing this, we were able to identify the key drivers for increasing sales (brand elements that should be enhanced).

CMM is a method developed by XICA that statistically analyzes the brand selection mechanism based on consumer awareness data. It identifies investment levers that are effective in switching from each competitor to the company's own brand, and also calculates the "switching rate" (the probability of switching when the lever score increases by one point) that indicates how much that factor influences switching.

The analysis focused on two axes: the delivery market and the pizza delivery market, but here we present the results for the delivery market. In order to clarify the factors necessary for non-pizza delivery users to switch from competitors to Pizza Hut, the analysis was conducted using multiple structures, including consumer attributes, the 4Ps of marketing, and brand equity such as attitude change and brand image.

In this way, Pizza Hut's goal of "maximizing the cost-effectiveness of marketing and enhancing brand power through building ongoing relationships with customers" is steadily being realized through data-driven marketing.

Finally, to sum up the event, Hirao listed three elements to "increase market share in a highly competitive market like Pizza Hut's."

Hirao:"First, it's important to 'maximize the precision of marketing through data science.' Then, 'to increase precision, consider not only quantity but also quality,' while 'tackling both the quality and quantity aspects with data and intuition.' In other words, I believe it's important to use a mutually complementary approach: verifying data discovered through intuition with data science to increase reproducibility, while also using data science to further refine intuition and increase the precision of hypotheses. I hope that Pizza Hut's case study will serve as a reference for developing marketing strategies for companies competing in a similarly tough market environment."

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