Shiseido, a global cosmetics brand, has been practicing one-to-one marketing long before it became an obsession of digital marketers. Their customer loyalty program, launched in 1937, has been at the center of their customer communication and branding strategy
for 80 years.
One of the recent additions to their customer loyalty initiatives is Watashi Plus, the digital marketing platform designed to create premium customer value by connecting Shiseido’s enduring brand and evolving services. Inside Watashi Plus, Shiseido customers can browse catalogs, order products, search for store locations and receive expert advice and product recommendations. Launched in 2012, Watashi Plus was the first step in bridging the gap between brick-and-mortar stores and online visitors. “At the core of effective marketing is understanding each customer’s evolving preferences,” says Kenji Yoshimoto, the lead analyst on the Direct Marketing team. “By analyzing the historical data of each customer and correlating the analysis with the current behavior, we can accurately assess each customer’s preference.”
Knowing that the preferences expressed on Watashi Plus accounted for a tiny subset of customers’ preferences, Yoshimoto’s team set out to build a much more holistic customer data platform to bring customer behavior data, demographic data and offline data into a single, unified view of each customer.
Choosing Treasure Data
Shiseido’s Direct Marketing team faced two challenges: unifying their data silos and the need to enrich their Watashi Plus data.
When Yoshimoto’s team audited their dozens of customer touchpoints, they realized that Shiseido had inadvertently created many data silos: disparate sources of customer data disconnected from one another. They needed a way to bring all these data sources together and join them against the common customer ID. Their incumbent ETL process into a data warehouse was not able to keep up with the dynamic nature of marketing data.
If centralizing their own, “first party” data was the first challenge, the second challenge was bringing in 3rd party data. Only when Shiseido’s 1st party data and the 3rd party available through Data Management Platforms (DMPs) were combined, they would be able to deliver truly personalized, one-to-one customer experiences.
After evaluating multiple solutions ranging from building in-house solutions from scratch to working with a large marketing cloud vendor, Shiseido decided to build their customer data platform using Treasure Data. Their decision came down to three factors: Scalability, flexibility and a rich integration ecosystem.
- Scalability: Treasure Data’s proven scale gave them the confidence that their platform will be future-proof.
- Flexibility: Shiseido must handle a wide variety of data types, and Treasure Data’s comprehensive support for various data sources and flexible storage engine meant they didn’t have to invest resources for upkeep.
- Rich integration system: Not only Treasure Data was already integrated with a public DMP as well as their intended marketing automation system, it had native integrations with Tableau and Python, the two main analytic systems used by their data analysts.
Implementing Treasure Data
As they began to deploy Treasure Data, they realized the fourth benefit: a minimal need for engineering time and complete ownership of the entire data platform by the marketing team.
With all customer data connected, current and easily accessible, Yoshimoto’s team moved onto the most important task: modeling. The team categorized the data into four types:
By synthesizing these four types of insights, Shiseido has enabled data-driven customer communication. Because Treasure Data integrates natively with Tableau, the preferred platform for exploratory data analysis and dashboarding, the team was able to iterate on their customer segments and detect patterns in customer behavior. The key final step was integrating Treasure Data with Salesforce Marketing Cloud, Shiseido’s marketing automation system and LINE, a popular messaging app that Shiseido uses for direct response marketing.
With Treasure Data: From Marketing Automationto Customer Preference Management
“The new customer data platform built on Treasure Data is fundamentally changing how we communicate with our customers,” said Yoshimoto. “Previously, our customer communication was based on assumptions about customer behavior and designed for our convenience, not customers’ needs. Blasting emails to everyone who tried samples or bought a particular product won’t lead to customer delight. Detecting a mood swing in each customer and changing the tone of push notifications does.”
As the interaction between brands and consumers become increasingly complex, Shiseido’s Direct Marketing team is pioneering the shift from marketing automation to customer preference management.