The Added Value of a CDP (Part 3)
A Deeper Analysis of the Benefits of a Customer Data Platform
By Peter Gergen, Solution Architect CX
A Customer Data Platform (CDP) offers companies a wide range of benefits when it comes to using and managing their customer information. It enables extensive insights into customer behavior, personalized customer journeys, improved data quality and data integrity, automated marketing processes, and real-time interaction over a variety of channels. A CDP optimizes marketing strategies, improves customer satisfaction, and increases sales.
Data Analytics, Customer Segmentation, and Audience-Building
In the final post in this series of three, I will be examining the key differences between conventional data management and using a CDP with regard to data analytics, segmentation, and audience-building, to emphasize the value added by a CDP.
From Raw Data to Meaningful Information
A Customer Data Platform (CDP) initially guarantees precise harmonization and normalization of raw data from different source systems. This data does not deliver its full potential or become truly valuable until it is linked with historical data. Clever combination of information, particularly from the customer’s transaction and activity data, creates meaningful indicators. This comprehensive data analysis makes it possible for companies to gain valuable insights and make informed decisions based upon them.
Here are a few examples (based on the SAP Customer Data Platform):
- Activity indicators in the CDP provide summarized information about the customer’s contact data, master data, and activities. Two examples: For purchase orders, an attribute can be created in the customer profile that summarizes the number of online orders placed in the last 12 months – provided that they exceed a specific order value and only involve a specific product category. For service tickets, an attribute can be created for a business partner that summarizes the number of service tickets that were opened by the customer’s contact person or IoT system, but only for a specific product class. Indicators of this type are updated in the CDP automatically and in real time as soon as an activity by the respective customer is recorded.
- The customer data platform also uses cross-activity indicators to calculate complex summaries of attributes. For example, whether a customer has opened at least one service ticket and left negative feedback on the website in the last 10 days – and made a complaint about at least one product. Based on this information, the CDP calculates a score that reflects the customer’s “pulse”.
- And lastly: In the customer data platform (CDP), a predictive indicator based on customer comparisons can calculate predictions of different events. One example of this is the likelihood that a customer will abandon the company in the foreseeable future based on their shopping habits, feedback scores, and other attributes (the churn risk). Likewise, the customer lifetime value, or CLV, can be determined for the near future. This determination takes numerous factors into account, to make precise predictions as to how important the customer is to the company now and in the future in economic terms.
Indicators represent the fundamental building blocks for enabling deeper analytics of the data in the customer data platform (CDP). They serve to form the parameters whose thresholds are relevant for creating customer categories (segments) or triggering workflows and therefore have a major impact on the development of the customer experience. By basing its activities on these indicators, the CDP can initiate complex processes targeted at optimizing customer care and interaction.
Effective Audience Identification
Based on the raw data and indicators, the CDP can define threshold for forming segments and trigger points for individual customer flows, as well as audience activities. What does that mean? Let me explain briefly:
- Customer flows: In my first post on the benefits of a CDP, we looked at an example in which an air traveler missed their connecting flight and the company proactively suggested compensatory measures. Targeted activities like this are part of the customer flow and are usually executed quickly. To shape these activities effectively, companies need to prepare corresponding use cases in their customer data platform. These use cases are then triggered automatically as soon as the customer reaches certain trigger points. In turn, these trigger points are created through customer-specific activities and events. As a result, the customer responds to the customer’s behavior and needs proactively, to guarantee an optimal customer experience.
- Audience measures: These are periodic, company-internal activities that focus on target groups with shared characteristics (audiences) and that are initiated by the company. For example, trade show visitors who show particular interest in specific products and then visit the website for more information about these products can be identified as audiences, for which custom-tailored marketing activities can be defined. These audiences are recorded, and the corresponding measures are planned and implemented, by the customer data platform in connection with the marketing system, with everything executed according to the requirements of the company’s marketing team.
The CDP makes it possible to execute situation-specific immediate actions for individual customers in real time, particularly when the customer’s individual situation demands exceptional service. At the same time, the audiences defined by the CDP simplify targeted marketing activities that focus on the interests of the respective audience.
You might remember the example of a completely misguided customer experience, in which a customer expected help from the company for an expensive repair, but was instead notified of a price increase by their contact person. This unfortunate encounter also caused the customer to search for ways to terminate the contract.
A customer data platform could have done a lot to proactively prevent a situation like this: potential problems with the product might have been identified in advance, through IoT tickets, before the company opened a service ticket. This would have triggered targeted, proactive, CDP-driven actions. The service and support inquiries would have made it possible to assign the affected customer to a specific audience that demands greater attention from its contact persons. As soon as a certain indicator in the customer data platform reached a threshold indicating customer dissatisfaction, the CDP could have notified the responsible contact person via the CRM system, who in turn could have called the customer – to find an amicable solution to the problem together.
More about SAP CDP:
- The Added Value of a CDP (Part 1) – Central Data Store
- The Added Value of a CDP (Part 2) – Customer-Centric Focus
- The Added Value of a CDP (Part 3) – Data Analytics, Customer Segmentation, and Audience-Building
- Unleashing Customer Insights: SAP CDP for Insurance Companies
- Unleashing Customer Insights: SAP CDP for Retail