Upgrade Your CDP Software for B2B with a Customer Intelligence Platform
To remain competitive, large corporates need to upgrade their CDP software to harness the full potential of B2B data and exceed changing customer expectations in an increasingly digital world.
Consumers, accustomed to the likes of Netflix and Amazon, expect seamless experiences across channels and geographies, demand service anytime, anywhere, and instant fulfillment. However, in a B2B context, large corporates – from banks and insurance firms to communication service providers – often struggle to meet these expectations as they are hindered by legacy technology and siloed data – which results in a lack of true understanding of their customers.
Customer Data Platforms (CDPs) have surfaced in recent years as a popular solution to help organizations overcome these challenges. CDPs allow you to connect customer data across multiple sources to drive more relevant and timely engagement across channels.
But despite the early success that CDPs have seen in the B2C space, B2B client engagement is more complex and requires a broader range of capabilities than is available from the typical CDP.
A new approach is needed to extract value from an abundance of available data and make sense of complex interactions that can span multiple individuals, entities, business lines, and countries. Using new technologies, you can now intelligently connect and process huge volumes of data to understand complex B2B relationships and make better data-driven decisions.
Enter the Customer Intelligence Platform.
What is a Customer Intelligence Platform?
Customer Intelligence Platforms (CIPs) are similar in many ways to CDPs but encompass several additional capabilities to deliver value in a B2B context. For example, the ability to connect broader datasets, handle complex relationship information and deploy advanced analytical models.
The following table compares the typical capabilities:
|Customer Data Platform||Customer Intelligence Platform|
|Segment||Retail||Retail, Business, Corporate|
|In-scope data||Marketing, Digital, CRM||Any firm-wide and external data including: Marketing, Digital, CRM, product holdings & utilization, transactions, contracts, counterparties, performance and income, third party, news|
|Identity/Entity Resolution||Identity resolution – typically deterministic matching based on digital footprint e.g. email address, cookies, IP address, customer ID||Entity Resolution – deterministic and probabilistic matching across a broad range of attribute combinations from internal and external sources|
|Analytics||Simple calculations and rules-based segmentation capability||Store and process complex relationships (e.g. corporate structures and supply chain networks). Develop and deploy machine learning models|
Comparing the B2B value generated from CDPs and CIPs
Why are these additional capabilities critical in B2B?
There is increased availability of useful data – but it is more difficult to connect multiple internal and external sources
There is a growing amount of external information available for companies – from reported financial information to mentions in the media, and awarded government contracts to emergency funding applications. Organizations also typically hold a more varied set of internal data for their business and corporate customers due to the relative complexity of product and service offerings.The combination of this internal and external information can provide a holistic understanding of your B2B customers and inform timely and highly relevant engagement.
To do so, you need to be able to stitch together data from a variety of sources to resolve identities – and to move beyond deterministic matching using customer IDs, emails and IP addresses. This requires entity resolution on a huge scale. Firstly, you need to get the data from all of these sources into a single platform. Given the broad range of data, a flexible approach to data ingest is required to avoid costly data transformation programs.
Entity Resolution then allows you to connect billions of data points to create an accurate single view of data This then enables you to enhance decision-making across the customer lifecycle, optimize the customer experience, and unlock unexpected opportunities.
In B2B, it is critical for organizations to move beyond a narrow focus on marketing and channel information. By taking advantage of this broader set of data to create a holistic view of your clients, you can uncover valuable new insights and drive contextual client engagement.
Relationships are the key to unlocking a true understanding of business and corporate customers
Networks and relationships are fundamental in B2B. Businesses are a network of entities, directors, shareholders, and contacts – often with complex legal structures. And every business interacts with others as part of a wider ecosystem of buyers, suppliers, investors, and other parties.To make matters even more complicated, organizations often hold different views of corporate clients internally to serve different purposes.
For example, sales will have their own view of a corporate structure, which adds further challenges when trying to connect data and build a holistic view of relationships and engagement with clients and contacts. An ability to make sense of these complex relationships is vital to truly understand your customers and drive meaningful engagement. When looking for a CIP, ensure it has the capability to model and analyze these networks. A greater understanding of your B2B customer relationships, connections, and behaviors will help you to discover new business and reduce customer attrition.
Bespoke analytics are required to uncover the most valuable insights
The B2B segment typically requires a bespoke approach to analysis. The huge variety of client profiles, behaviors, internal customer data structures and complexity of product and service offerings means that a one-size-fits-all approach does not work and prebuilt models are ineffective.
A simple rules-based segmentation approach (often adopted in retail) is not suitable; sophisticated analysis is required to provide the insights necessary for proactive and relevant engagement. For example, that which considers engagement across corporate structures, variations in behavior due to business seasonality and complex trading relationships.
A CIP provides a connected view of customers as a basis for this analysis, and a framework for the development of specific models based on the use case at hand. These can range from simple rules-based models to more complex algorithms developed using machine learning to create bespoke customer segmentation or predictive insights.
For example, in a banking context, it is possible to predict a customer’s need for lending before they are even aware of it themselves based on analysis of market trends, the behaviors of companies in their trading ecosystem, and changes in the circumstance of the customer themselves. This allows you to drive proactive and meaningful engagement across digital and face-to-face channels to support your customers and build loyalty and trust.
Start your move to a Customer Intelligence Platform
A CIP should be deployed as a horizontal layer to connect data across multiple applications, channels, functions, and business lines. APIs allow seamless integration with existing tools, both to ingest data into the platform and to return enriched information – allowing you to get the most out of your organization’s existing technology stack and ensure alignment across departments.
For example, a CIP can sit as a layer beneath your CRM system to provide a robust single customer view and timely prompts for account managers based on the analysis of a broad range of internal and external data – not just that stored within the CRM system.
The following steps will ensure a quick time to value and sustained long-term commercial benefits:
Identify key areas of focus
Set a strategic vision for the solution
Prove commercial value with a simple first step
Expand in both depth and breadth
Monitor and optimize your Customer Intelligence Platform