How are Businesses Using Customer 360 Views?

Editor’s Note: This post was originally published in March 2024. We’ve updated the content to reflect the latest information and best practices so you can stay up to date with the most relevant insights on the topic.

For B2B and B2C businesses, Customer 360 is the holy grail for marketing, sales, and support teams. Done well, Customer 360 enables businesses to deliver personalized experiences, uncover hidden revenue opportunities, and deliver world-class customer support. However, when Customer 360 initiatives are implemented poorly, organizations may experience customer dissatisfaction, stagnant revenue growth, and customer attrition. 

Implementing a Customer 360 use case isn’t easy. A slew of challenges including siloed data, poor data quality, and legacy master data management (MDM) solutions that can’t scale make attaining Customer 360 views difficult to achieve. 

That’s why businesses need a new approach. To overcome the historical barriers to achieving Customer 360, businesses must explore innovative strategies that deliver the golden records needed to deliver the kinds of experiences their customers expect. 

How Does Customer 360 Fit Into Existing Business Strategies?

Customer 360 views provide businesses with golden records—single, authoritative, accurate versions of customer data across multiple data sources and datasets. The benefits of having these customer golden records are immense: better, more personalized experiences; increased customer satisfaction; reduced churn; and greater lifetime customer value. 

Customer 360 views make it easier for businesses to make better decisions. Not only can organizations feel confident that they have a holistic view that encompasses all relevant information and touchpoints related to the customer, but they can also rest assured that their decisions are based on trustworthy golden records that contain the best version of their customer data. 

In addition, when golden records are connected via enterprise knowledge graphs, their value increases even more. Enterprise knowledge graphs are a critical platform capability of AI-native MDM, providing a connected, contextualized view of an organization’s data that highlights the relationships among and between key customer entities. Identifying these cross-entity relationships enables organizations to reveal meaningful—and often obscured—connections that surface valuable, actionable insights. 

Here are a few examples of how Customer 360 views benefit various parts of the organization. 

• When marketing departments have Customer 360 views, they have a better understanding of customer activities and preferences, enabling them to target and personalize their marketing campaigns with relevant offers aligned to customer needs. 
• Sales teams use Customer 360 views to spot untapped revenue opportunities that were previously obscured because data about buying patterns and behaviors were dispersed across a myriad of systems and departments throughout the organization.
• Customer 360 views provide customer support teams with a unique understanding of the customer, including insight into their interactions, preferences, and purchase history. As a result, these teams can deliver the personalized support customers expect, leading to greater levels of customer satisfaction and higher retention rates.

In all of these examples, customer golden records—connected through enterprise knowledge graphs—provide a clearer picture and deeper insight into customer attributes, relationships, actions, and behaviors that enhances marketing, sales, and service across the business. 

Examples of Customer 360 Use Cases in Action

While achieving a true Customer 360 view may seem like an insurmountable task, there are organizations that have successfully implemented Customer 360 use cases. Using Tamr, Toyota Motors Europe and a global life sciences company delivered the customer golden records their organizations needed to achieve business goals. Here’s how they did it. 

Customer 360 at Toyota Motors Europe (TME)

Toyota Motors Europe (TME) had an objective to grow their business across Europe. However, with 30 national marketing and sales companies (NMSCs) operating across 50 countries, growing the business was no small undertaking. They launched an initiative to put the customer closer to the center of their activities—but because each NMSC used their own systems and integration approaches, gaining a consolidated view of customers proved challenging. Not only did their customer data vary in quality, but it was also trapped in data silos, making it nearly impossible for TME to innovate, collaborate, and scale their European business. 

To tackle this challenge, TME partnered with Tamr. Using Tamr’s unique combination of AI and human intelligence, TME was able to eliminate data silos and improve the accuracy and consistency of their data in a cost-effective way. Using Tamr, TME was able to clean and standardize their data, easily add new sources, and track changes and improvements to the data over time. And, using the collaborative capabilities within Tamr, TME employed human intelligence to capture input and validate results, helping to improve the trust and accuracy in the data. 

As a result of using Tamr, TME not only gained a unified view of their customers, but they also reduced duplicate customer records by 40%. They improved overall sales and marketing efficiency and effectiveness as well, enabling them to deliver the exceptional experiences their customers expect. 

“Toyota is intensely focused on innovation and customer satisfaction. We want to deeply understand our customers and provide them with the best products and services we have to offer in a very innovative way. We saw a more integrated approach to unifying customer data as a core component of this.”

‍Matt Stevens, General Manager, Toyota Motors Europe

Customer 360 at a Global Life Sciences Company

A leading, global life sciences company knew data was the key to growth. But first, they needed to overcome major operational challenges. With customer data fragmented across more than 15 operating companies—each running separate CRM, marketing automation, and service systems—their ability to identify upsell and cross-sell opportunities was severely limited. Further, poor data quality and incomplete records slowed the adoption of AI initiatives, while redundant enrichment and compliance processes increased costs and risk.

To solve this challenge, the life sciences company modernized their data architecture with Snowflake, Salesforce Data Cloud, and Tamr’s AI-native MDM solution. Using Tamr, the company mastered customer and contact records across 17 internal and external sources, deduplicated 10M+ contact records, and improved data quality from 65% to 85%. Once the company had single, trusted Customer 360 views, they published the data back into Snowflake for use across the organization. 

In just six months, the company transformed their customer data—increasing transparency and delivering clean, consistent Customer 360 views across the enterprise. As a result, these trusted customer views power downstream use cases including:

• Next best action for sales
• Marketing personalization
• Cross-sell and upsell
• Customer journey analytics

“With Tamr, once the data is connected, records are mastered in a day or less—fast, automated, and accurate. Having a trusted golden record is a huge unlock. For the first time, we can confidently say, ‘Here’s who we’re working with—and here’s how to better serve them.’”

‍Data & AI Executive, Global Life Sciences Company

A New Approach to Address Customer 360 Use Cases

Toyota Motors Europe and the global life sciences company prove that businesses can overcome the challenges associated with the creation of Customer 360 views and realize immense business value. But doing so requires organizations to take a different approach than they have in the past. 

Relying on traditional, rules-based MDM solutions is no longer sufficient. Traditional MDM solutions were built for static data. That means when the data changes, the rules must change, too. And in today’s world where data is dynamic and ever-evolving, traditional MDM simply can’t scale. 

In contrast, Tamr’s AI-native approach combines advanced AI/ML models, agentic data curation, and select business rules—making it easier and faster to discover, enrich, and maintain the trustworthy customer golden records that organizations need to deliver personalized experiences and accelerate business growth. 

Tamr enables businesses to:

• Achieve great results out of the box: By combining embedded similarity with human feedback, Tamr helps organizations achieve highly accurate match rates across internal and external data sources, improving data quality and reliability.
• Tailor interactions to the consumer: AI ensures that customer interactions are informed and relevant by creating a personalized, single view of each customer and validating it, where necessary, with human insight.
• Increase effectiveness: Machine-generated feedback helps AI-native solutions learn and improve over time, ensuring that the system keeps pace as business needs and data landscapes evolve.

Tamr: Delivering Trusted, Customer 360 Views

By eliminating fragmented, siloed data, Tamr delivers the trustworthy data foundation needed to fuel analytics, operations, and AI initiatives. This foundation transforms the customer lifecycle by sharpening personalization, reducing attrition, and forging stronger customer relationships.