Dentsu Digital Inc.'s Data & Technology Center (DTC) develops and provides various solutions to advance digital-era marketing. This is achieved by establishing a data platform environment and building upon the data analysis obtained there. At the core of this effort are the many data analysts employed by DTC.
Transformation SHOWCASE hosts roundtable discussions with data analysts active within the Dentsu Group. This article is the third installment. We spoke with Mr. Masahiro Fukuda, Ms. Shizuko Funaki, Mr. Makoto Nakajima, and Mr. Yuki Asada, who gained extensive experience as data analysts at other companies and now contribute to Dentsu DTC. In the latter part, we delved deeper into the qualities required of data analysts at Dentsu Inc. and the rewards of their work.
Data Analysts Also Need a Business Perspective
Q. Could you describe the ideal profile for a data analyst in the marketing domain Dentsu Inc. provides? What kind of person is suited for this role?
Asada: Fundamentally, it's someone who possesses the ability to understand general statistical analysis using programming languages and analytical tools like Python or R. Even if they are transitioning from a different industry, possessing these core data analyst skills allows them to acquire Dentsu Inc.'s specialized domain—data analysis based on marketing theory, known as "Marketing Science"—as they perform their duties at Dentsu Inc. However, merely acquiring the academic knowledge of Marketing Science alone is unlikely to enable them to perform their duties in a way that satisfies our clients. Data analysts bear accountability to clients, planners, and business producers, requiring the ability to explain concepts clearly enough for everyone to understand and accept. Merely stringing together academic terms is insufficient. An approach rooted solely in academic reasoning fails to communicate effectively or demonstrate genuine engagement. While this isn't unique to Dentsu Inc., this ability to translate concepts is essential, isn't it?
Dentsu Inc. Yuki Asada
Fukuda: Furthermore, figuring out how to leverage the results of data analysis for marketing initiatives requires working closely with planners, right? People who struggle with this kind of collaboration might find it difficult to progress smoothly in their work.
Funaki: Indeed, data analysts also need a perspective for grasping business challenges. Those who say, "I'm not good at communication, but I'm skilled at data analysis," might find it difficult. Conversely, possessing these skills means you can be entrusted with work regardless of experience. In fact, DTC has seen remarkable contributions from younger members.
Nakajima: I definitely sense momentum in the contributions of career hires, especially younger ones. Personally, though, I feel there's still room for growth as an "organization." Fundamentally, fields like data science and data analysis are relatively new within the advertising industry. Many companies are likely strengthening their talent in these areas to meet current market demands. Dentsu Inc. is no exception. I believe the key lies in our organizational integration—in how data analysts, possessing high individual skill sets, drive forward as one team with planners and business production teams to enhance their contribution to the business. Furthermore, to continuously provide this integrated capability as a reproducible and sustainable solution, I think the organization needs various initiatives: recruitment/development, standardization and formalization of work processes, and more. This brings us back to the question of how to enhance "organizational strength." To achieve this, I believe those of us in the data field who are in our forties have a significant role to play.
Dentsu Inc. Shin Nakajima
A rewarding job that shapes corporate data utilization strategies
Q. So, when do you feel a sense of accomplishment or enjoyment in your work? Please tell us the points that bring you joy.
Fukuda: There are two main points. One is the moment when a question arises while looking at data – "What does this mean?" – and the hypothesis formed from that question connects with the data during further investigation and analysis, leading to an "Aha!" moment.
The other is when presenting analysis results to client companies and receiving unexpected feedback from a fresh perspective. Discovering "Oh, that's another perspective!" is exciting. Explaining the analysis results from our viewpoint sometimes leads clients to re-explain their values or the thoughts behind their target audience. Beyond just submitting data and reporting analysis results academically, I find joy in discussing new interpretations and expressions with clients, exploring questions like "Could we also consider this perspective?"
Funaki: It's truly rewarding when we can deliver an output that satisfies the client. Synthesizing diverse opinions and ultimately producing an output that benefits the client brings a real sense of accomplishment.
Ms. Shizuko Funaki, Dentsu Inc.
Nakajima: When co-creating solutions or services with clients who hold proprietary data, the process involves their future vision for how they'll utilize that data. For instance, even if Dentsu Inc. proposes a solution, the scope of data usage is limited unless the client establishes privacy policies for handling the data and secures internal alignment and approval across departments. Within this context, I find it rewarding when the entire team, including the client, works together to move a large organization forward.
Asada: I have two points. First, I find joy when I can pursue and pinpoint the cause of an issue that arises. Having experience in system maintenance and operations from my previous job, I feel a sense of fulfillment when I can swiftly reach the root cause of an error in a system flow.
The second is when data analysis yields unexpectedly positive results beyond initial assumptions. For example, we had a project where we were asked to "run automotive product ads on social media and measure the personas of those who viewed them." Since it was a nostalgic product, I expected older people to click. But when we looked at the results, the group with the highest response was "young women who love makeup." They seemed to click the ad because they found it "retro-cute." As an analyst, I found it fascinating to see that this product could be perceived that way, and the client was also very pleased.
We provide end-to-end solutions, delivering outputs based on data analysis results
Q. Many companies specialize in IT consulting. Where do you see your uniqueness?
Fukuda: I believe our greatest uniqueness lies in our ability to create outputs based on data analysis results. Being able to conceptualize the output and actually execute the creative production is a value proposition unique to the Dentsu Group.
Dentsu Inc. Fukuda Masahiro
Funaki: I also believe our ability to handle creative work is our greatest value. Our capacity for better planning stems directly from our ability to handle a wide range of data.
Nakajima: At Dentsu Inc.'s DTC, I get the impression that many people work outward-facing despite being in the development department. As the Data & Technology Center, we have a clear direction on what solutions and services we provide to our clients. I think our uniqueness lies in consistently executing the fundamentals well.
Asada: Each individual has a very large scope of action. Of course, within the bounds of protecting personal information, I think it's an environment where you can fully explore what kind of data analysis is possible.
Q. Some people understand the importance of data marketing but aren't sure how to approach data specialists for consultation. How should they reach out?
Fukuda: Don't overthink it—a broad, general inquiry is perfectly fine. Just start by saying, "I'm facing a challenge." Through ongoing dialogue, we can clarify the issue and propose solutions. Please feel free to reach out anytime.
Data analysts deal with vast amounts of data daily, performing analysis and developing solutions. It was interesting to note that by combining academic analytical skills with a business perspective on utilizing data and analysis results, they can deliver high-value work that truly satisfies clients. For those interested in the role of a data analyst, we hope this article helps you visualize what the job entails.
The information published at this time is as follows.
At a domestic IT consulting firm, engaged in various phases of client projects including core system construction and operation, as well as ERP, CRM package, and service implementation. Subsequently, after working in customer success and corporate data collection/analysis for marketing utilization at a domestic venture company offering B2B marketing services, joined Dentsu Inc.
Currently, primarily leveraging experience in system construction/operation and data research/analysis, engaged in effect analysis of advertising and sales promotion measures utilizing major platform providers' Data Clean Rooms, as well as solution development.
After graduating from an American university, I have consistently worked in marketing and data analysis-related roles. Following a stint at Dentsu Digital Inc., my previous position was at a credit card company, where I was responsible for data analysis-focused tasks within the department overseeing marketing strategy. I joined Dentsu Inc. in 2023. I am responsible for proposal work across data clean rooms and global expansion.
With 14 years of experience in the digital advertising industry, I have worked across a wide range of fields including media planning, sales, and DMP planning and development. Subsequently, I joined Dentsu Digital Inc. in 2022. My responsibilities include solution planning and development, focusing on areas such as geo-solutions and data clean rooms.
Previously worked in the database division of a newspaper company, responsible for developing economic and financial data content.
Joined Dentsu Inc. in 2023. Primarily engaged in platform data analysis and development within the data cleanroom business, responsible for building data analysis environment designs and developing analytical solutions utilizing advanced data science cases, including MMM.
