Customer Data Platform – Panacea for Data-Driven Customer Experience?

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In our projects, too, we see an increasing awareness of the importance of the customer experience as a key lever for customer acquisition and retention. A great customer experience means reaching the right person with relevant content at the right time and along the entire journey with a company’s brand, product, or service. However, the technical prerequisites for a consistent data-based approach to customer experience are still a major work in progress.

 

The Challenges

No wonder, then, when you consider where the customer potentially comes into contact with a company – open and closed areas of a website (e.g. homepage, login area), app, email (customer support, CRM, marketing), social, etc. – it becomes clear that most organizations still have a long way to go in order to reach the goal of a data-driven orchestrated customer experience.

 

The key challenges for companies are:

 

  1. to gain an overarching view of the customer

  2. to create an overall orchestrated customer experience with the help of this view

 

In addition to the organizational requirement that various specialist disciplines must overcome their silo thinking and work together in a goal-oriented manner for the benefit of the holistic customer experience, companies face major technical challenges in this context. The following basic skills are required to achieve the goal of a personalized customer experience across all channels:

 

  1. permanent collection of data from all touchpoints in one place

  2. linking the data belonging to a customer (profiling)

  3. segmentation (rule-based or using predictive analytics methods)

  4. providing the obtained information to executing systems, ideally in real-time

 

CRM, Data Warehouse, Data Lake, and Co. do not cover – neither individually nor in sum – the mentioned 4 aspects: Only data from specific touchpoints enter a CRM system, data from different pots can be stored in a data warehouse, but only in a structured form and thus inflexible. The flexible linking of even unstructured data and the associated formation of segments are indeed possible with a Data Lake, but the ability to activate acquired knowledge is also lacking here. This means that the knowledge gained from these systems cannot be used directly as a trigger for the corresponding action at the touchpoints.

 

The CDP Solution

This background provides fertile ground for the rise – not to say hype – of the so-called Customer Data Platforms (CDPs for short), which is now beginning in Germany as well. CDPs promise the solution for the described challenges of data-based customer experience design and control. The term was coined back in 2013 by David M. Raab, founder of the CDP Institute – an organization that aims to educate marketers about this technology class – and describes software solutions with the following characteristics:

 

  • They have an integrated, persistent data management to unify customer information across many different sources and channels.

  • They have a unified customer identifier that links all of a customer’s data, regardless of source

  • They are accessible to external applications and provide data for various marketing and analysis technologies

  • They are controlled by marketing

Since then, the market for this technology has exploded, and with the entry of major players such as Adobe (Adobe Experience Platform) and Salesforce at the latest, it is becoming clear that CDPs are not a temporary trend. At the same time, a differentiated view of the topic is advisable. Gartner sorts the technology into its hype cycle in the “Peak of Inflated Expectations” phase and reports that many marketers who have introduced a CDP only use it as CRM.

The now densely populated market has slowed its growth and at the same time, marketers are trying to understand how each vendor differs. Many vendors are now positioning themselves as CDPs, but not all of them deliver the capabilities marketers hope for. Attempts to differentiate often result in providers offering redundant technology.

Before companies jump on the bandwagon – following the shiny promises of the industry -, a precise definition of internal requirements is absolutely essential. This enables companies to choose the most suitable provider or to opt for a custom solution.

In both cases, it is important to avoid redundancies or gaps in the technology stack. Otherwise, companies run the risk of finding themselves in the position to have spent a lot of money and effort for introducing a new software solution without having made progress in regards to data-driven Customer Experience Management.

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