Today, analyzing and utilizing data is essential for business growth. However, it's common to see cases where acquired data isn't fully leveraged for business purposes. Many companies likely face concerns like, "We have the data, but we're not using it effectively," or "We're building a CDP (Customer Data Platform: a system for collecting, integrating, and managing customer data), but we don't know how to use it effectively."
Therefore, this time we interviewed Ryota Konishi from the Data Strategy Division, Business Transformation (BX) Department at Dentsu Digital Inc., which promotes business consulting through data utilization. Mr. Konishi hosts company-specific seminars called "AI Workshops," supporting the formulation of data-driven visions and improving sales effectiveness through AI and machine learning.
Many people intuitively understand that "business evolves when data is the starting point," yet struggle to visualize the concrete path forward. In Part 1, we asked Mr. Konishi about the characteristics of his team and data-driven strategy formulation.
Designing the Ideal Business Model Based on Data
Q. What role do you play in Dentsu Digital Inc. BX Division Data Strategy Department?
Konishi: I provide comprehensive support on how to effectively utilize data, including AI and machine learning, to benefit our clients' operations.
I'm particularly deeply involved in our company-specific seminars, the "AI Workshops." We listen to clients' concerns like "We're struggling with this" or "We want to learn about this," then conduct customized workshops to address their specific needs.
I also help formulate data utilization strategies. This includes advising on "how to effectively utilize data" and "how collected data can drive revenue growth," as well as performing data aggregation and analysis.
Dentsu Digital Inc. | Ryota Konishi
Q. When we talk about data, it encompasses various types like surveys and user membership information. What exactly do you mean by "data"?
Konishi: To start from a slightly higher level, data is "fact." Generally, when people think of data, they often imagine numerical values. However, beyond numbers, there are various types of data like text data and audio data. Personally, I consider "data" to be the objective capture of what customers or users have expressed.
For example, when gathering user feedback through interviews, it's difficult to speak with many people at once. Even if you could, it would likely be only a few to several dozen people. But if you accumulate hundreds, thousands, or tens of thousands of facts as data, you can discern various insights from it. You begin to understand what is happening now, and by analyzing that, you can see what will happen in the future. I believe that is what data is.
Q. Please tell us about your data-driven consulting. What solutions do you provide in response to corporate inquiries?
Konishi: What we value most is the vision of what we want to achieve through the business. We call this the "To Be." We first clarify what initiatives we want to implement and what kind of customer experience we want to provide by implementing them. Then, we consider what is needed to realize that.
The starting point here is the "data," or "facts," I mentioned earlier. What facts will we base our strategy and initiatives on? What data analysis and IT environments are needed to implement these initiatives? We design the ideal business state starting from the data. While the actual data analysis can be done without deep knowledge of machine learning tools, determining what to input and how to utilize the resulting outputs requires human expertise. That's the core focus of our Data Strategy Division.
Proposing the necessary data to realize your vision
Q. I imagine many companies are interested in AI and machine learning but still unsure how to utilize it. What kinds of inquiries does your team receive most frequently?
Konishi: Currently, about 50% of our work involves data analysis tasks like "aggregating data to extract insights." About 30% is modeling work using AI/machine learning. The remaining 20% is consulting support we call "Data Utilization Strategy Development," which introduces a data utilization perspective into our clients' operations.
Beyond that, we aim to increase the proportion of data utilization strategy formulation. This process begins by clarifying GOAL setting for clients—translating their abstract wishes into concrete visions like "Using data will lead to this future." We then create a roadmap covering everything from establishing the required IT environment and designing data analysis tasks to implementation.We want to take on the role of helping clients envision their future based on the data they've gathered, or gathering the necessary data to realize that vision. While other companies may also offer "vision creation" services, our department's approach combines qualitative initial hypothesis setting—drawn from our unique Dentsu Group perspective on the future of the client's industry and customer experience design—with the worldview enabled by quantitative analysis, including AI and machine learning. We believe this integrated approach sets us apart.
Q. To realize the formulated vision, it seems clients might sometimes need new data beyond what they already possess. In such cases, do you also propose acquiring the necessary data?
Konishi: Yes, we do. For example, suppose we receive a request like, "We want to analyze user data to strengthen our CRM (Customer Relationship Management)." In such cases, we start by refining the goal setting—clarifying what the client fundamentally wants to achieve with CRM. This process reveals the necessary data, allowing us to identify what needs to be gathered and provide a list.
The crucial part comes next. While we can suggest, "Gathering this type of data would be beneficial," actually acquiring the data is the client's responsibility. Therefore, based on the purpose, we present options like, "Generally, this is how you collect such data," "Let's gather this data through a survey," or "Designing it this way could make the data richer." We then collaborate to determine the optimal approach.
We also propose processing data clients already possess. We call this creating "composite variables." Even existing data can reveal new insights when combined with other elements.
How to collect new data and how to leverage existing data. We propose ideas addressing these two points early on in our consultations.
Q. What is the dividing line between success and failure in projects that utilize data?
Konishi: Many clients believe that "collecting data will somehow solve everything," but data alone is meaningless. What matters is the purpose for using the data. To achieve this, it's crucial to create a "menu" outlining the vision you want to realize and the specific data required to achieve it.
Discovering AI application themes suited to each company through "AI Workshops"
Q. From what we've discussed, I understand that vision-making and the effective use of data to realize that vision are crucial. How does AI and machine learning fit into this?
Konishi: We conduct our "AI Workshop" because we want clients to first understand the possibilities that AI and machine learning can unlock. When they see use cases like "This technology enables us to achieve this," it changes how they envision their own future. From there, we propose tailored solutions: "Let's envision this future. Here's how we'll build the pipeline to get there."
Q. Regarding the theme "AI Study Sessions," it's true that many similar events are held. Could you tell us about the characteristics, strengths, and highly valued aspects of your "AI Workshop"?
Konishi: Our "AI Workshop" is conducted exclusively for each individual company. The key feature we emphasize is customization. We don't just want participants to learn about AI and machine learning use cases. That sense of urgency about needing to utilize data effectively is something every modern marketer likely feels. In response, we want the case studies to serve as a catalyst for the realization: "Ah, this is what we should be doing." To achieve this, we conduct preliminary interviews to understand the specific challenges each company faces and then tailor the case studies accordingly.
Next, we hold a free-talk session where clients freely discuss their business challenges, leading to proposals. Our "AI Workshop" is characterized not just by attending a seminar, but by using free-talk to identify business challenges specific to their company and generate new value.
When people hear "data utilization," they often think of analyzing and using existing data. But it's more than that. Formulating a vision based on data and creating the environment to realize it are also crucial. Supporting this comprehensively is the role of a data strategist. As the first step in this data utilization journey, Mr. Konishi's team hosts the "AI Workshop." In the second part, we'll delve deeper into the details of the "AI Workshop" and its use cases.
I began my career as a CRM/budget planning specialist at a comprehensive e-commerce company, gaining experience in designing member programs for points sites and developing/implementing LTV maximization strategies through user profiling on auction sites. After supporting corporate data utilization initiatives, I assumed my current role. My strength lies in experience at both operating companies and service providers, and my motto is to drive data utilization tailored to each client's specific situation.
