Every B2B company knows that their customers are a valuable asset. And data about these customers is equally as valuable. But when that data is incorrect, incomplete, or outdated, it becomes difficult to derive value from it. Too often, customer data spans multiple systems, departments, and data silos, making it difficult to integrate into a holistic, 360-degree view of the customer. And without that holistic view, the individuals in the company who are responsible for identifying and driving upsell/cross-sell opportunities, delivering world-class customer experiences, and identifying potential risk exposures will struggle to succeed.
Data Products: An Antidote to Dirty, Disconnected Data
Overcoming the challenges presented by dirty, disconnected data is an age-old problem. But today, companies are shifting their strategies to focus on data products. And they’re delivering great results.
Data products are easy-to-use sets of high-quality, trustworthy, and accessible data that people across an organization can use to solve business challenges. When your organization employs a data product strategy, it signals to everyone in the company that data is an important asset. A data product strategy manages data as a product, and often employs a data product manager, just like traditional product management employs a product manager.
Organized by business entities and governed by domain, data products are the best version of your data, purpose-built for use in both analytical and operational use cases. Good data products have seven characteristics:
Curated with feedback from end users
Managed by real-time operations through machine interfaces
Aligned to domain-specific, universal schema
Mastered through machine learning-based matching models
Validated and cleaned based on global standards
Enriched with external data sources
Version-controlled for monitoring and provenance
These seven characteristics roll up to four key pillars that highlight the greater value of data products:
Discoverable and interoperable using intuitive user and machine interfaces that support real-time operations
Comprehensive and consistent by aligning to a domain-specific, universal schema and enriching data with reference data sources
Clean, accurate, and reliable with validation and cleaning based on global standards and version control for monitoring and provenance
Curated and continuously-updated using pre-built, machine learning-based matching models and curated with feedback from end users
B2B Customer Mastering: A Data Product Template from Tamr
Data products help B2B companies deliver the clean, curated, continuously-updated data needed to improve customer experiences, drive upsell/cross-sell opportunities, and identify potential risk exposures. And Tamr’s B2B Customer Mastering data product template is no exception.
Designed with B2B companies in mind, this data product template checks all the boxes when it comes to the characteristics of a good data product. Tamr designed B2B Customer Mastering to be consumption-ready, which means that we started with end-user needs and worked back to the data – not the other way around, which happens with most data-led initiatives.
Designed with machine learning at the core, our B2B Customer Mastering data product template streamlines operations by using machine learning to automate the matching and modeling of data, allowing data stewards to spend less time cleaning dirty data and more time providing feedback on the model results. Data enrichment incorporates the critical, external data needed to build out incomplete records. As a result, organizations have a more complete and holistic picture of their customers across systems and departments, allowing them to personalize the customer experience and target them with additional solutions that make sense for their business.
It’s Time to Shift Your Strategy
Implementing a data product strategy is simple when you have the right tools and technologies. Tamr is the data product platform for organizations looking to increase the value of their data by treating it as a product. Our turn-key data product templates combine machine learning, optimized for scale and accuracy, with a low code/no code environment and integrated data enrichment to streamline operations. See a demo of how our data products work at tamr.com/demo.