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Evaluating CDPs: Distinguishing Back-End and Front-End Components for Use Cases

Written by AI Generated | 14 February 2023
Navigating the world of marketing technology can be overwhelming, as customer data platforms, data management platforms, marketing automation platforms and email service providers offer services that often overlap. In order to decide what you need, it is helpful to distinguish services by their back-end and front-end components. Back-end components include the technical infrastructure and processes used to collect, store, harmonise and manage customer data. This includes data integration, warehousing, governance and security features. The back-end component is responsible for ensuring customer data is accurate, complete and accessible, with the goal of merging disparate records from multiple sources to create a single customer view. The front-end component of a CDP can be divided into marketer-facing and customer-facing features. Marketer-facing features include data visualisation and reporting, whereas customer-facing features could include recommendation engines, paywall management, and custom content displays. It is important to consider which components are necessary for your use cases, and which need to be part of the CDP itself. To evaluate a CDP, consider a few use cases and how the back-end vs. front-end metric can help. For example, if you want to recommend articles based on which e-newsletters the customer receives or which products the customer subscribes to, you’ll need a back-end connection with the ESP and/or the fulfilment system, as well as the ability to merge the user’s online profile with that data. However, if you only want to make recommendations based on the user’s web behaviour, you don’t need the back-end function, and you may not even need a CDP. In the retail space, vendors often want to provide product recommendations, which can increase the value of each order. If the recommendations are based on the customer’s order history, the recommendation engine will need back-end data. However, if the recommendations are based on averages across all customers, specific information about the customer’s purchase history is irrelevant. Publishers who don’t rely exclusively on ad revenue to fund the creation of content may offer access to premium content for a fee. This requires the creation and maintenance of accounts to manage access to this content. If those accounts need to be coordinated with other accounts, such as a magazine subscription, the paywall management system will need to integrate with back-end data from the magazine fulfilment system. A/B or multivariate landing page tests can dramatically increase the success of an online store, online forms, and e-newsletter sign-up pages. Services that facilitate the creation and deployment of such tests usually do not distinguish between customers and non-customers, and this works for most situations. However, if your customers are significantly different than the average web visitor, back-end information on the audience might be crucial. Surveys can help you understand your customers, which can help you provide better service. Many CDPs can manage surveys, but dedicated survey platforms often have more features. If your surveys are enhanced by incorporating back-end customer data, or if you need to extend the survey process over time through progressive profiling, a CDP may be necessary. Creating a worksheet can help you evaluate potential CDP vendors. Start with use cases and think them through in terms of front-end and back-end functions, also considering 3rd-party alternatives. The more your use cases require back-end functions, the more you’re likely to need a CDP. Ultimately, the key is to figure out which solution fulfils the requirements of your use cases.

Originally reported by Martech: https://martech.org/how-to-create-a-cdp-worksheet-from-your-use-cases/
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