How next-gen data management enables a 360-degree view of B2B customers

Unified customer profiles enable real-time insights to support the hyper-personalized experiences customers expect.

In brief

• Break down silos by integrating digital marketing data with offline sales data to gain deeper insights on consumer preferences.
• Utilize analytics capabilities to segment customer data and drive better experiences.
• Leverage journey orchestration to enable real-time decision-making, alerts and messaging.

Rising consumer demands and rapidly evolving technology are forcing business-to-business (B2B) organizations to rethink the end-to-end customer journey. Buying frequency, products purchased, key contacts, roles and decision-making is all vital information when developing marketing plans and processes to create ideal customer experiences that drive engagement, sales, and loyalty. Having the right platform and approach in place can help B2B organizations unlock these customer insights and much more.

A rapidly evolving status quo

B2B organizations have sought a 360-degree view of their customers for years to understand what truly motivates them. But between functional silos and fragmented data systems, few are able to see the whole picture. Often, each company domain — including the customer relationship management platform, sales analytics tools and marketing analytics tools — maintains its own version of customer data. But without a unified view, organizations struggle to perform robust customer analysis and use the resulting insights to inform the customer experience across channels. Even with the artificial intelligence (AI) and analytics capabilities needed to segment customer data and recommend engaging experiences, most B2B companies lack the specific capacity needed to unify individual customer profiles with real-time insights on customers’ cross-channel engagements to support the hyper-personalized experiences customers expect today. Moreover, because their data lives in disparate systems across the enterprise, organizations are often behind the curve in understanding what data is available and how to access it.

Tools like the Adobe Enterprise Platform (AEP) unify customer data across the organization (e.g., marketing activities, sales engagements, acquisition opportunities) to gain real-time insights about customer behavior, feeding a personalization loop that can constantly inform and improve customer experiences. With AI and machine learning capabilities, organizations can better anticipate, design and activate hyper-personalized experiences.

EY teams understand first-hand the key challenges marketers face in gaining the complete customer view that today’s market requires, and that’s why we have teamed with Adobe to evaluate a B2B-focused approach utilizing AEP — with our organization serving as the first test case. We recognized an opportunity to leverage the platform to help us to form a clearer, more unified picture of EY clients’ needs and preferences. Team members worked closely with the Adobe product management team to identify B2B use cases and account segmentation improvements on the project road map.​

The EY data management assessment journey

We embarked on a journey to evaluate AEP because we recognized the need for global B2B organizations to better unify their data across functions, systems and geographies. Unifying data in this way helps them streamline regulatory compliance activities across multiple jurisdictions, activate quick decision-making, execute leading data strategies, and provide exceptional goods or services. However, it also requires a carefully crafted data management approach, and below are a few use cases we tested from our recent implementation of the AEP platform.

Create actionable, real-time customer profiles and segments

Our analysis showed that AEP utilizes unified customer profiles that include information such as customer attributes and milestones. The platform then uses those profiles to create datasets from several sources and loads them into more than a dozen schema for high-velocity processing. We also confirmed that it has the ability to join data from disparate sources to create a holistic, real-time view of interactions between the sales and marketing functions.

Enrich and analyze multichannel data to derive customer journey insights

By integrating digital marketing data with offline sales data derived from a customer relationship management tool, AEP helps enable marketing-influenced sales reporting, multi-source audience overlap analysis, marketing fallout reporting and customer experience pathing flow analysis. We leveraged the platform’s query services and customer journey analytics feature to create an integrated sales and marketing dashboard that allows us to confirm that follow-up for qualified contacts is taking place consistently and in a timely manner.​ We also investigated how the platform connects machine learning and artificial intelligence to marketing and sales use cases. This effort enabled us to analyze data and compute and store predictive propensity scores onto individual profiles and accounts for marketing and sales activation. ​

Orchestrate and deliver consistent and personalized experiences in real-time

This phase of our analysis involved the platform’s journey orchestration features, which help enable experience personalization and real-time decision-making. After evaluating data segments in real time, AEP shares those audiences in a variety of ways, including batch delivery, streaming to other applications and one-on-one event-based orchestration. The journey orchestration workflow then streams real-time messages to external systems so alerts and messages can be displayed.

Establish account-level support for insights, hierarchy, inheritance, and governance

We explored the platform’s customization and integration features, which can be used with other tools to surface account interactions across systems. AEP’s query services and customer journey analytics create integrated sales and marketing dashboards to measure lead progress through funnel functionality. This supports account-based marketing efforts by elevating key considerations to account teams via API access or streaming segments, which can be activated for marketing via out-of-the-box connectors. ​

Key takeaways and success criteria

By leveraging AEP for a unified view of customer data, we confirmed its ability to centralize segmentation; activate marketing segments across internal and external systems; and improve customer experience, marketers’ experience, and marketing services. Working closely with Adobe, we created a 360-degree view of client interactions that supports growth strategies and drives a more efficient regulatory compliance process. The EY Consulting team implemented AEP to drive a next-generation client data platform that will enable EY teams to engage with customers and prospects in ways that are relevant to them. This type of customer and prospect engagement, including all relevant communications, can be tailored using insights from previous interactions with a client and/or the client’s response to marketing initiatives. 

Unifying data across complex, disparate systems is a challenge for most organizations. However, AEP enables them to bring together data from multiple sources to gain a single view of their audiences so that the organization can interact with them in a more personalized, relevant manner based on their preferences. For example, EY teams now have visibility into the status of each client or prospect, on both an individual and an account level, and can nurture them through the B2B sales cycle in the most appropriate way.