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Advantages and demands of customer data optimization

By Peter Gergen, Solution Architect CX

As a company, you have a wide range of interactions with your customers: through your website, newsletter, or personal meetings at trade shows. Your customers buy products, place orders, make complaints, open support tickets, express criticism, pay invoices (or don’t), and provide valuable feedback about your service. Each further interaction increases the connections between you and your customers. But don’t you think it’s time to recognize each customer’s unique needs and address them to increase their individual satisfaction?

To create an outstanding customer experience (CX), companies must successfully integrate valuable customer data from different data silos. By merging, standardizing, consolidating, and formatting this data for personalized customer interactions, you can get a 360° view of the customer. This end-to-end approach to data aggregation is essential to achieving the goal of creating custom-tailored, top-class customer experiences.

Increase customer satisfaction with an optimized customer experience: A satisfied customer experiences a seamless, personalized interaction – an example of a conversion from unknown user to a loyal repeat customer

The organic growth and diverse landscape of systems that store customer data – including CRM systems, support systems, marketing platforms, data warehouses, and ERP systems – results in fragmentation of customer information. Each of these systems contains customer data that is more or less complete and free of errors. To get an end-to-end picture of the customer, however, it is essential to consolidate this data in a single, comprehensive customer profile.

This doesn’t only involve contact data and master data (personally identifiable information or PII), but also activity data (transaction data) that includes all customer interactions: Purchases, orders, feedback, click behavior on the website, and much more. Merging this information creates an end-to-end customer profile that enables deep insights into a customer’s behavior and preferences.

A Customer Data Platform (CDP) is the solution to this challenge. The CDP is connected to the different source systems that are responsible for the described customer information. It enables this data to be integrated in a single, end-to-end customer profile. Using the PII and activity data, the CDP classifies customers, creates segments, and groups customers with similar needs and demands into “audiences”.

Segmentation in a CDP divides customer information into groups, with the aim of creating targeted marketing campaigns and personalized content

These audiences are target groups that are defined based on criteria like demographics and interests, to enable custom-tailored messaging and special offers.

The CDP doesn’t only serve as a central data store for customer information, however; it also uses its findings to forward them to the specific, connected target systems. Three examples:

  • The lead entry tool forwards contacts with trade show visitors to the CDP. In turn, the CDP sends the marketing system precise information about a specific audience of trade show visitors, who are either potential customers or existing customers who have shown interest in a specific product. Based on these findings, individually defined incentives are developed to further promote and strengthen these customers’ connections to the company.

  • A support system sends information to the CDP about a support ticket that a specific customer has opened. In this process, the CDP identifies that an important customer is involved, who is not receptive to marketing information at the current time. Based upon this, the CDP notifies the marketing system to suspend all marketing activities for this customer for a defined period of time.

  • Loyalty programs, websites, and shopping portals give retailers the opportunity to collect a wealth of customer information, such as shopping habits, product preferences, financial leeway, and social preferences. The CDP uses this information to calculate specific indicators, which in turn make it possible to categorize customers, segment them, and divide them into homogenous audiences with similar profile classes. They then serve as the foundation for creating custom-tailored specials, to offer individual added value to customers.

As such, the CDP acts as an intelligent agent that controls the flow of information between the different systems and ensures that the right activities are carried out at the right time for every customer.

The transition to implementing a CDP requires awareness of the changes that will be needed to internal company workflows and the willingness to tackle them. It may be necessary to rethink established data structures and introduce new methods for organizing data. Processes will need to be adjusted to enable the standardized data flow and integration of the CDP. Employees will need to be trained how to use the CDP, to leverage the platform’s full potential.

Implementation of a CDP requires integration in the company’s existing IT landscape. This entails structural and process-related changes to create a central data source that reflects the 360° view of a customer profile.

The aspect of data protection also requires serious consideration. The GDPR (General Data Privacy Regulation) states that all processing of customer information must be strictly tied to specific purposes. This requires clear policies and measures to ensure that the company is legally compliant in its use of this information.

The road to implementing a CDP can pose a challenge, but the potential rewards in terms of customer satisfaction and business growth are significant. A clear understanding of the necessary changes and careful planning can help companies successfully manage the transition and seize the opportunities that a CDP offers.

In the following posts, I will go into the benefits of a CDP in more detail, as well as examine the technical requirements of its implementation and operation.