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Dentsu Inc.'s DMP Implementation Theory: Refining Marketing Through Data [Part 2]

Continuing from the first part, we focus on DMP implementation theory. In this second part, Satoshi Saeki from Dentsu Inc. Integrated Data Solution Center shares know-how on segment-specific strategies using DMP.

Close collaboration among personnel is essential for granular marketing

DMPs now enable segment-specific strategies, making near-one-to-one communication possible. As shown in the diagram, when we segment users and deliver appropriate creative appeals and landing page (LP) guidance to each segment, how does user behavior change?

Data scientists from the Integrated Data Solutions Center directed operations for each segment, from creative production to DSP (digital advertising automated bidding system) bidding, providing detailed operational instructions. This resulted in the following outcomes:

・Click-through rates (CTR) increased by 1.5 to 10 times compared to standard DSP delivery without data linkage (DMP).
・Post-click behavior also indicated high interest and effective landing page matching, with metrics like pages per visit and session duration showing strong results.

Thus, even considering the increased ad delivery costs due to data usage fees and smaller segment sizes, the results secured sufficient effectiveness. The key success factor for this campaign was having someone overseeing the entire DMP process.

This relates to point ③ mentioned in the previous section: since DMP involves various marketing processes, numerous stakeholders are involved. Close collaboration is essential with many responsible parties, such as the trading desk, search engine marketing (SEM) operators, and email marketing operators.

For example, imagine the trading desk operating the DSP and the segment designer had no communication whatsoever. Only the segment designer possesses insights into the target audience and their attributes. Conversely, the trading desk optimizes the portfolio of target segments, bids, frequency, and other factors based on performance metrics. However, optimizing without understanding the target audience often leads to strategies that simply favor segments showing immediate response. While such operations may yield short-term efficiency, they risk losing customers who should be nurtured for the future.

This principle applies not only to ad operations but also to communication design and creative development. Segmenting via a DMP fundamentally means defining the target audience. Aligning the overall marketing strategy with DMP-based segmentation is essential.

Toward a world of integrated marketing where all data connects

These initiatives—estimating and leveraging user attributes and insights—hold the potential to fundamentally transform digital marketing itself. This transformation lies in leveraging data from other media touchpoints for integrated planning.

For example, visualizing TV exposure allows us to discover effective media that can complement customers not reached by TV ads. Furthermore, analyzing over time enables us to identify targets likely to respond next, based on their exposure to TV commercials.

Furthermore, considering the potential for integrating diverse data—such as social data, cross-device data, and wearable data—the future of data marketing expands infinitely.

Dentsu Inc.'s Strategy and Initiatives for DMP

Dentsu Inc. has been fully committed to DMP since early 2013. We possess abundant resources across the three key areas supporting DMP service competitiveness: data sources, talent, and tool options.

Regarding data sources, DMP connects data from approximately 100 million browsers, primarily from panel data and Dentsu Inc. partner sites. We possess deep expertise in diverse tools, centered on Turn, which holds top market share in Europe and the US. We select tools that best match advertiser needs from a neutral perspective, free from vendor lock-in. Furthermore, having professionals across strategic planning, ad operations, CRM, and other domains is a unique strength of the Dentsu Group.

DMPs have proven effective not only in the acquisition-focused areas where digital advertising traditionally excels, but also in contributing to brand building and marketing strategy through enhanced customer understanding. Furthermore, the rise of rich media advertising has ushered in an era where digital advertising is effective not only for direct outcomes like clicks and reach, but also for brand awareness, favorability, and purchase intent. Considering the trend toward richer digital advertising enabled by DMP-driven customer understanding, the value of brand advertisers continuing with digital advertising is becoming increasingly visible.

At Dentsu Inc.'s Integrated Data Solutions Center, our experience has taught us that the "human" element is ultimately decisive. When tools become highly functional and data becomes open, the differentiator lies in the "people" who master these tools and data. Marketers handling DMPs require advanced decision-making and analytical skills. This is because one cannot fully utilize a DMP without understanding what data is collected within it and how it is processed. Data scientists who deeply understand marketing while also mastering machine learning and statistical analysis, and who can handle massive data volumes using tools like Hadoop, are indispensable. Our center actively recruits and systematically develops such talent. We are also cultivating talent unique to Dentsu Inc.: "data scientists who are also well-versed in mass advertising and creative production." This represents a distinct strength born from our longstanding focus on mass advertising. As the trend toward full-scale DMP utilization intensifies, we intend to continue exploring its potential.

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Author

Saiber Satoru

Saiber Satoru

Dentsu Digital Inc.

Joined Dentsu Inc. in 2007. Responsible for data analysis in digital marketing and ad technology support. Previously at Dentsu International Information Services, specialized in developing media optimization systems and CRM systems from scratch, with 7 years as a programmer & SE. Subsequently worked as a financial analyst at a foreign financial institution. Speaker at ad:tech tokyo 2012 and 2015; Director of the Data Scientist Association.

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