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What You Need to Know About B2B CDPs, Data Ops & Data Mesh Architecture (Part 2)

Abhi Yadav, Co-Founder & CTO, Zylotech

Missed ‘Part 1’ of “What You Need to Know About B2B CDP’s, Data Ops, & Data Mesh Architecture? Catch up here!


DataOps: An Operational Approach to Data and Analytics

In general, data operations (DataOps) is a methodology for developing analytics using the best practices of agile software development and DevOps (software development and IT operations). Like data mesh, DataOps involves developing data products and enabling teams to get the best value from data. 

Organizations that implement DataOps aim to achieve several things, including:

  • Improve how teams manage data and develop data products.
  • Allow business users to tap into and manage data with an easy-to-use user interface (UI). 
  • Streamline and speed up data consumption within the organization to better support data-driven projects, such as marketing campaigns, machine learning, and application development.

Marketing ops and sales ops teams are DataOps power users, but they often end up overworked, having to work on endless spreadsheets due to the lack of a DataOps implementation. For organizations to successfully implement DataOps, teams must focus on how data is consumed across the organization as opposed to how data is created. So we have a use case driven culture.

DataOps not only allows teams to pull insights from data but also use data to trigger action. The B2B buyer’s journey has evolved into an almost entirely digital experience, closely mirroring the customer journey of a B2C business. As your B2B leads or B2C customers move through the purchasing journey, your DataOps team should be able to take actions such as:

  • Trigger customized sales and marketing emails.
  • Engage all accounts using targeted digital ads.
  • Automatically serve customers personalized web pages.
  • Engage customers in relevant conversations via chatbot or live chat.
  • Personalize lead nurturing across multiple channels.

You have many approaches and frameworks to choose from to implement DataOps. Your choices depend on the skills of your engineering/LOB teams and the needs of your DataOps teams. For example, you could choose to: 

  • Implement data intelligence or customer data platforms (CDPs) that provide codeless DataOps.
  • Create a data warehouse or data lake with building block platforms (DIY) like Snowflake or Segment & Apache Spark and lot more to build out and make it useful or operational.
  • Implement martech or salestech solutions that require some specialized training but no coding, but limiting to limited data & lightweight data operations.

You may have noticed we list CDPs as a possible option for your DataOps implementation. When we say CDPs, we mean modern CDPs as opposed to the traditional CDPs most organizations have been using for years and will fall in DIY options.

B2B Customer Data Platform: Making Customer/ICP Data Accessible

The CDP Institute defines a customer data platform as, “packaged software that creates a persistent, unified customer database that is accessible to other systems.”

A marketing and business-friendly CDP makes customer data accessible to marketing, sales, and customer experience teams without the need to depend on the IT department. CDPs are not data warehouses or master data management systems (MDMs). Most CDPs are DIY— they bring your data into one place and make it accessible with a self-service UI, and some will even unify that data.

In the past, CDPs were used primarily by B2C organizations, but today, you can find both B2C and B2B CDPs. B2B buyers expect the same fast and personalized digital experiences they get as customers of B2C brands. A B2B CDP can gather customer data from multiple sources including email, CRM, company website, and social media websites like LinkedIn.  

While many CDPs have evolved to serve B2C and B2B businesses, only modern B2B CDPs combine data mesh and DataOps at this time. However, there is a missing piece – a modern CDP to ensure trusted data governance across a connected sales, marketing & customer tech stack, as well as the same distributed version of truth across each connected system. To automate this governance process it must be powered by a trusted B2B ID graph (Industry’s first) that enables persistent ID Management –  The unification & resolution of people, location, and companies that are constantly in a state of change. This is a huge differentiation with Zylotech.

You Need All Three

Nearly every company has ongoing data projects and data management tools. You need a platform that allows you to utilize the new data mesh architecture, and the latest DevOps trends, while still leveraging your existing data projects. Traditional CDPs i.e mostly B2C lack the capabilities & philosophy that line of business (LOB), revenue teams, and marketing teams need to achieve these goals.

At Zylotech, we’ve developed a scalable CDP with trusted data governance and an advanced data mesh architecture to fully automate data processes and operations. Our CDP provides codeless DataOps for MO and RevOps teams, which means they can combine domain specific use cases and DataOps without having to know how to code. So only CDP with Data Automation & Self Service Orchestration combination. With our B2B CDP, one can leverage all their existing data projects, data silos and build a scalable yet automated central data augmentation across people, companies & activities, but also offer a self-service data operations approach to your marketing, sales & customer ops team while offering a codeless environment for outcome focussed Revenue teams. Interested in learning more about Zylotech? Contact a solutions expert here!

Looking for more information on B2B Customer Data Platforms? Download our B2B CDP Basics ebook here!

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