Bringing One to One Marketing to Digital

One to One marketing can be defined as personalizing the experience for every customer, based on what you already know about them or what you can infer.
Man Shopping Among Very Similar ClothingA top 10 global retailer pioneered one to one marketing, with a customer loyalty program they started more than half a century ago. But it wasn’t easy to translate that success into the digital world. Ultimately, they found Treasure Data and built a holistic customer data platform that brought behavior data, demographic data and offline data into a single, unified view of each customer.

The result? Personalized one to one marketing boosted customer LTV for loyalty program participants by 20%.

How they solved for mass personalization at scale

In 2012, the company had created a customer loyalty web site that made it possible to browse catalogs, order products, search for store locations and receive expert advice and product recommendations. The site helped them gather data on their users’ evolving preferences online, but that data only represented a tiny subset of their customers.
When the company audited their dozens of customer touchpoints, they realized they 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 a common customer ID. Their incumbent ETL processing 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 the company’s 1st party data and the 3rd party available through Data Management Platforms (DMPs) were combined, would they be able to deliver truly personalized, one to one customer experiences.

The Treasure Data Trifecta: Scalability, Flexibility, Integration

The company considered building their own in-house solution from scratch. They also considered using Adobe Marketing Cloud, a natural choice since their team was already using Adobe Analytics.
Instead of adding other Adobe products to their stack, they decided on Treasure Data. The decision was based on three advantages: Scalability, flexibility and a rich integration ecosystem.

  • Scalability: Treasure Data’s automatic scalability ensured they wouldn’t have to set up complex extensions later.
  • Flexibility: Treasure Data’s comprehensive, schema-flexible support for various data sources, and flexible storage meant they didn’t have to invest resources for upkeep.
  • Open integration system: Not only was Treasure Data 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 systems used by their data analysts. With a rich library of existing integrations and constant stream of new integrations, Treasure Data was also future-proof.

As the team began to deploy Treasure Data, they were pleasantly surprised by their increasing freedom from the need for engineering time, as well as the power and productivity that came with complete ownership of the entire data platform by Marketing.
With all customer data connected, current and easily accessible, they quickly moved onto the most important task: modeling. The team categorized the data into four types:

  • Demographic—“Who is the customer?”
  • Brand Loyalty—“How much does the customer like our brand?”
  • Channel—“What paths does the customer take to buy products?”
  • Interests—“What is the customer interested in?”

Synthesizing these four types of insights 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, their preferred marketing automation system.

From Marketing Automation to One to One Marketing

The new customer data platform built on Treasure Data has fundamentally changed how the company communicates with their customers.

“Previously, our customer communication was based on assumptions about customer behavior and designed for our convenience, not customers’ needs,” said their Head of Marketing Analytics. “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 interactions between brands and consumers become increasingly complex, Treasure Data is pioneering the shift from marketing automation to customer preference management via one to one marketing at scale.

Learn more about Treasure Data CDP solutions for marketing.