Q&A: How Oracle drives more revenue from its B2B customer data

March 8, 2024 | 8 minute read
Atif Zubair
Product Marketing Manager, Oracle
Text Size 100%:

As one of the world’s largest technology companies, Oracle offers a living test case for many of the trends shaping B2B marketing and sales today. One example: Uniting marketing and sales as a revenue operations construct, which Oracle has put into practice. Or the shift from product-focused sales to a subscription-based business model—a shift at the heart of Oracle’s global cloud business.

Oracle’s Bence Gazdag, vice president, global marketing technology, recently discussed how Oracle uses customer data to navigate these major strategy shifts. Below are excerpts from that conversation between Gazdag (BG) and Atif Zubair (AZ), product marketing manager at Oracle:

 

AZ: Could you share insights on the current trajectory of the B2B market and on the challenges faced by B2B marketers?

BG: A few trends and challenges we’re observing involve the unification of marketing and sales into a revenue operations construct. We’ve implemented this at Oracle already. It demands transformation and support from both the data and technology side. The B2B data is very complex, and as a B2B marketer, you need to be able to manage those complexities, the intricate hierarchies, the evergreen data sources, and how to create intelligence that can power AI.

Another trend that we’re seeing, and we’re also navigating, is the shift from a product-focused business to a subscription-based model. At the same time, the value of third-party data is diminishing compared to years ago where you could purchase lists or buy your targets a lot easier. Now it’s less valuable and less accurate. So, the real gold is our first-party data that we have at our company, but the key is realizing its value, bringing it to a centralized place for alignment and segmentation, creating intelligence, and using it for activation and decision-making.

 

AZ: How does the integration of the customer data platform Unity with Oracle Eloqua contribute to overcoming these challenges?

BG: Eloqua is a fantastic tool for B2B marketing and driving amazing engagement and running sophisticated nurture programs. However, with complex and imperfect B2B account and taxonomy data, you need to manage that complexity, and that’s where Unity and the CDPs come in.

When we focus on bringing together all enterprise B2B customer data—dealing with account hierarchies, buying groups, product, and industry taxonomies—we aim to centralize all our first-party data in a single place, emphasizing both quality and quantity. These data sources span everything in the corporation, including sales, finance, support, subscriptions, web, and marketing data. This approach allows us to gain deeper account insights. Once the data is centralized and standardized, we can start making it actionable and create real-time customer intelligence, which we can activate across various channels, including Eloqua, advertising, social, etc.

This process also helps our journey with AI and machine learning, as a solid data foundation is needed for training and building the machine learning models to optimize and predict campaigns and sales activities. It’s essentially a robust data engine that allows you to activate through many channels, not just Eloqua, which serves as the email and web activation platform.

Dig deeper on Oracle Unity CDP Integration

 

AZ: What are the key B2B use cases you prioritized to address with Unity and Eloqua, and what level of success have you achieved?

BG: I could say that we were very successful in performing advanced segmentation with all the account data, lead scoring, opportunity scoring; really having a 360-degree customer and account view and delivering a consistent multichannel experience. To give you a good example, we’ve been focusing on cross-sell and upsell. During Oracle CloudWorld, which is one of the largest technology events with over 10,000 attendees, we wanted to ensure a speedy and relevant follow-up experience. So, we used Unity for that. We set up a complex segmentation business logic in Unity that looked at attendees, session attendance, and company details such as subscriptions and product ownership, so a variety of data sources came together to form a basis of that segmentation. It all happened really fast—on the same day the event closed, we had all the data and the segmentation ready in Unity to send to our sales system for follow-up. This level of segmentation in such a short time was something we hadn’t been able to achieve before. That’s a very recent example.

 

AZ: You say within a day you were able to get this information into Unity and do the segmentation. How long did it take to do the same task in the past?

BG: It could take weeks. There was a lot of manual work, like determining which account belongs to what territory, identifying their ownership and subscriptions, considering multiple sessions they attended and how they relate to specific products they own, deciding who should own the first follow-up and establishing the prioritization of preference for the follow-up. So, all of that logic, we built into Unity, and it was ready by the time Oracle CloudWorld happened. We executed that segmentation logic in close to real time and it’s going to be even better in this upcoming year. Very exciting.

 

AZ: Are you planning to expand on those use cases in the future?

BG: Absolutely, this is just the beginning. We’re learning and bringing in a lot of product usage and telemetry data to truly understand our customers’ behavior and interactions. We’re also starting to deploy various AI models. For example, large language models to help describe the complex set of activities for our sales organization, in business English, all in a few sentences. This way, they can understand everything they need to know about a customer or a lead instead of trying to dig through pages and screens of information or metrics. AI can turn this massive amount of information into an easily consumable format that becomes a part of our system and processes. 

 

AZ: What were some outcomes you achieved and where did Oracle Unity CDP come into play?

BG: The main benefit is being able to achieve precise segmentation because we now have access to all that information about our accounts that we were not able to get before. This includes account hierarchies, making sense of those account hierarchies, and getting a 360-degree view of the customer by combining internal and external data sources. We also brought sales into the fold, integrating sales account planning and lead planning into a single source of truth, which is Unity. Some of this was done before, but it was manual, taking around 10 days to pull this information together. Now we can do it in a matter of minutes. So, our time to decision and our time to market has decreased tremendously. We’re just discovering what’s possible once you introduce optimization and automation to many other processes. It’s going to be very exciting. 

 

AZ: What has recently emerged as significant is the role that AI plays in CX. What’s your perspective on AI in CX and how have you used various AI models in Unity to enhance your customers’ experience?

BG: The key to understanding is, first, you must have data in one place—a usable, high-performant, secure place where you can start building and training your models and use various AI tools for various initiatives. Without that, AI will just be a point solution. So, this was a sort of a heavy lift where Unity brings significant value, and we have achieved that.

Now we’re in the process of rolling out AI/ML tools or models. Some examples I’ve mentioned previously include using LLM models to summarize complex activities into digestible business form. We’re rolling out an LLM model for title normalization and title mapping because all this data is large and complex, and titles are a key building block of buying units. There is also opportunity scoring, or what you might call buying group engagement optimization or buying group scoring, where we’re looking at a vast amount of data that these models are good at consuming.

Those are some of the machine learning models that we’re working on, and we have been seeing good results. I can’t wait to do more with them. There is a whole set of ML models that come out of the box with Unity, such as next best offer, next best contact, and lead or opportunity scoring. But you can also bring your own model into Unity, and this combination is very robust. It’s a great platform to have the AI/ML models around your corporate data. 

Explore Oracle Unity CDP AI/ML capabilities

 

AZ: How has this powerful duo of Unity and Eloqua provided you with a competitive edge?

BG: That’s a great question because Unity and Eloqua are part of the same CX suite and tightly integrated. Because of that, you can now utilize real B2B account schema, capabilities, and all the account data from across the corporation for microtargeting, or precise targeting.

Previously, in order to achieve this, we would have to integrate with an external vendor, or database, and then go through the process of joining it all. It wasn’t a seamless experience; we were still hopping between systems, making it difficult to achieve a quick turnaround. And now, within minutes, we’re ready to make the decision and ready to execute. Our ability to respond to customer needs and changing trend or go-to-market campaigns has been reduced to days, and sometimes even faster than that. This close integration between Unity and Eloqua has made it possible.

Forrester Total Economic ImpactTM of Oracle Unity CDP

 

AZ: What are your recommendations regarding first-party data insights? Is it limited to just the front office, or does it extend to the back office, such as ERP? 

BG: It’s absolutely both. It’s not just your front office and CRM data, such as leads, opportunities, and sales interactions. You also need ERP data—your orders, quotes, subscriptions, support data, customer satisfaction data, etc. How are they adopting our products in the cloud business? Are they using our products successfully? Can we do something to help them become even more successful?

With those data points, we can identify which customers have certain products, and where they are in their journey of using and adopting them. This way, we could help them by showing, for example, other customers who were where they are now and how they succeeded. These stories really resonate with the customers. 

 

AZ: What important insights and best practices would you recommend for individuals going through a similar process?

BG: I recommend taking a crawl, walk, run approach. First, identify a specific business need or area, prove that things work, determine the ROI, and iron out your internal processes. While a technology upgrade is the easy part, the real challenge lies in business transformation and adoption. You need to ensure that you have your business transformation strategies perfected with a smaller group before onboarding the rest of the teams and processes.

It’s also very important to focus on comprehensive data ensure your data sources are integrated into Unity, cleaned up, and mastered. Without trustworthy data, your efforts might not yield the dividends you expect. So, these are some key recommendations: prioritize business transformation and comprehensive data management.

 

AZ: Our final question. What's next? What excites you about our CDP?

BG: What’s really exciting is that now that we’ve done the heavy lifting, and entered the age of AI, we’re ready to unleash our robots on our CDP and witness the amazing things they can do. We’ve been talking about this for a while, and now it's becoming a reality. I am very excited to embark on this journey. 

 

Additional resources

Learn more about Oracle Unity CDP

See Oracle Unity in action

See why Oracle was named as standalone leader in the 2023 Forrester WaveTM: B2B CDPs report

 

Atif Zubair

Product Marketing Manager, Oracle


Previous Post

Debunking the Top 5 Myths About Customer Data Platforms (CDPs)

Atif Zubair | 4 min read

Next Post


Q&A: How a CDP helps Oracle use its customer data more effectively

Sarah Gaade | 6 min read