Proposal capabilities that exceed client expectations. Supported by the in-house systems department.

One of Nextedge Dentsu Inc.'s strengths in pursuing results in the digital performance marketing domain is its in-house systems department. We spoke with architect Shota Izumi and operations manager Kazunori Hirose about how the systems department supports the operations team and the technologies Nextedge Dentsu Inc. possesses.

*Nexedge Dentsu Inc. became "Dentsu Digital Inc." on July 1, 2016.

Automating manual tasks makes advertising operations more efficient and precise

──First, please tell us about your respective roles.

Izumi: I belong to the Technology Group within the Solution Development Department, which uses technology to solve problems. My responsibilities broadly fall into three areas: developing internal business management systems, supporting and coordinating when clients implement existing advertising management tools, and building solutions from scratch to address client challenges.

All these efforts aim to automate labor-intensive tasks, improve accuracy, and drive operational improvements.

Hirose: My work spans multiple departments. One is the client advertising operations department. Since advertising requirements vary by client, I propose tool implementations optimized for each, negotiating with clients while collaborating with our technical team. The other involves R&D-like tasks: researching new overseas DSPs and ad delivery systems, investigating their feasibility for domestic use, and testing their application.

While these may seem like different roles, I believe they share a common purpose: supporting clients' advertising efficiency by assisting with operations and system development, or adopting new systems when available.

──What do you see as the value of having a dedicated systems department within Nextedge Dentsu Inc.?

Izumi: Nextedge Dentsu Inc.'s core mission is to enhance the precision of performance-based advertising and maximize its effectiveness. A fundamental prerequisite for this approach is a thorough understanding and knowledge of delivery platforms, led by Google AdWords. Beyond that, to flexibly address each client's unique marketing challenges, refine operational cycles, and accelerate the PDCA process, leveraging technology becomes necessary in many cases.

Of course, with a solid grasp of the distribution platform's characteristics, manual work and consultant knowledge alone might suffice to achieve passable, necessary results for ad optimization. However, adding technology to that mix allows us to accelerate the PDCA cycle and achieve more efficient, in-depth ad delivery. That is the raison d'être of our systems department.

Proactively identifying issues before clients recognize them and proposing solutions to resolve them

──From the operations department's perspective, what benefits does having a technology department provide?

Hirose: When a project requires a technological solution, outsourcing to an external SIer is possible, but it incurs communication costs for coordination. In today's fast-moving market cycles, I firmly believe in-house development is the most efficient way to propose and resolve issues swiftly.

In my role, I often receive technology-related requests from clients. Having an in-house systems department means I can contact them immediately when requirements arise, which is reassuring.

Furthermore, even if a client doesn't recognize an issue, if we identify it, we collaborate with the systems department to make new proposals. Currently, our structure focuses on deeply engaging with one client rather than handling many, so we strive to provide more in-depth solutions.

By digging deeper, we uncover connections between the client's sales and their ad campaigns, or fundamental issues with their site structure. This allows us to make "proactive proposals" – suggesting solutions before the client even asks, and moving them to the next phase. This is only possible because of our organic connection with the Technology Group.

──What kinds of issues might clients be unaware of?

Hirose: When clients want to maximize sales, if we can't accurately measure how effective their ads are, it becomes unclear where to invest next. Some clients place orders based on historical metrics, but we sometimes start by questioning whether those metrics are fundamentally relevant.

For example, sometimes we see sales growth without understanding the cause. This happens because the established metrics aren't correlated with sales, making it impossible to pinpoint the driver. However, other values not being measured might actually be correlated. This indicates the KPIs being evaluated are misaligned, meaning the evaluation metrics themselves need to change.

If we determine that different metrics should be measured, we propose this to the client for approval. Sometimes, this requires changing the system environment for ad measurement. This is necessary to correctly set metrics so we can measure which initiatives contribute to sales and assess the return on investment.

We collaborate with the technical department for system environment changes, but being able to consult immediately with just a phone call or sometimes chat when needed is a huge advantage.

Automated management of vast advertising delivery data impossible by manual effort

──Why does it happen that metrics aren't correlated?

Hirose: Previously, with a client I managed, we launched a large-scale advertising campaign to increase awareness. The following month, they reported, "New member registrations and web-based applications have significantly increased compared to the previous month and the same month last year. However, we can't identify the source." The inability to trace the path was due to issues with their existing system. In this case, we aimed to discover conversion-driving initiatives and make sound investments by changing the system to enable comprehensive tracking of user journeys.

For clients facing such issues, the environment for utilizing analytics tools is often not properly set up. Therefore, we sometimes also handle the implementation of analytics tools like Google Analytics in parallel.

──Could you elaborate on specific ways technology enhances operational efficiency and improvement?

Hirose: For e-commerce clients, it's common to process product information for use in ad delivery. However, clients operating large-scale e-commerce sites often have over 100,000 products, each with various details like size, color, and price. This volume is simply unmanageable for editing in a standard environment. Furthermore, since these are products, sold items disappear, and new products are added daily.

Manually processing this massive, daily-updated data is impossible, making technology indispensable. Therefore, we built a system within the client's company, creating a scheme where product data is processed daily and uploaded to the server.

For e-commerce clients, search ad keywords number in the millions and the required keywords change daily. Crawling product data also enables automatic actions like stopping ad delivery for out-of-stock items. We built a system capable of executing these intricate, high-quality settings with precision every day—tasks impossible by manual effort.

We also have a case study where conversion rates increased fourfold by optimizing ad delivery volume based on purchase intent.

──Could you share some specific examples?

Hirose: Consumer purchase intent varies by day of the week, time of day, and device. While the method for deriving purchase intent differs based on the client's metrics, it's typically derived from conversion rates resulting from ad delivery or profit margins. Running ads when purchase intent is highest maximizes effectiveness.

For instance, purchase intent from PCs increases during evening hours at home, while during lunchtime, PC usage drops and smartphone usage rises. We adjust ad delivery volume based on purchase intent data correlated with user lifestyles.

Regarding advertising, while Google AdWords allowed setting ad delivery volume based on purchase intent, Yahoo! Promotion Ads did not. After testing with Google yielded excellent results, we wanted to implement this for Yahoo! Promotion Ads too. We enabled integration with the Yahoo! Promotion Ads API via our proprietary internal system, nxdb.

Adjusting ad delivery volume based on purchasing intent resulted in a 31% increase in ad effectiveness. For mobile alone, we've seen cases where effectiveness increased approximately fourfold. Generally, PCs tend to have higher sales volume and purchase prices, so ads are typically delivered optimized for PCs. However, simply adjusting mobile delivery volume based on purchasing intent yielded this significant effect.

Purchase intent is also influenced by weather. We've integrated with external weather data APIs to dynamically adjust ad delivery volumes. This system is versatile and can adapt metrics to meet client expectations.

──A fourfold improvement in conversions is an impressive result. In the second part, we'll delve deeper into nxdb.