Being able to make data-driven decisions is undoubtedly one of the top priorities for any organization that prioritizes marketing and customer experience. Thanks to the rapidly increasing number of touch points, brands are getting data streams from wide variety of sources. We receive data from numerous points such as web interfaces, mobile applications, call center interactions, store shopping, and marketing communications and try to create meaning from them.


Is it possible to get rid of the noise created by all this data stream, to turn this noise into a symphony?


In existing marketing architectures, sophisticated needs arise during complex systems’ conversations with each other. The difficulty of building the bridge between brick & mortar and e-commerce experience and the difficulties we face in unification of data make it almost impossible to use the data exactly as desired. (The unprepared environments and infrastructural inefficiencies to use data certainly play a role in this.)

Solutions to ‘handle’ the situation complicate things even more, costing both time and resources. Weeks and months pass as IT teams try to plan how to get through; projects of business teams sometimes oscillate in the void of space and are shelved without finding any solid ground for discussion. Are we able to calculate the opportunity cost of all these, for our institutions and the monetary equivalent of the inefficiency it creates?

No matter how serious the losses are, the answer is obvious most of the time: No, we’re not.

(According to Gartner’s research, the cost of low-quality data is around 15M USD annually on average per each company in US.)

Adding to all these problems, trying to comply with regulations and the use of 3rd party cookies being disabled in near future, we find ourselves in a very complex situation with regards to regulating our relationship with data.




Customer data is vital to a company’s future. They are the key to understanding your customers’ characteristics and purchasing preferences. This is where CDP comes into play.

It is a very important component that enables you to get real and maximized value from the data you have. CDP takes customer data from multiple sources and makes this data available for all systems that provide insight and interaction to your corporation.

As each touch point means creation of a new data silo, CDPs also plays a very important role in the consolidation of these silos.


We can summarize the concept of CDP, as a real-time technology that collects and combines data from all web / mobile platforms, applications, stores, call centers, and IoTs in a manageable manner, and makes them usable by other technologies and tools.



CDP is not an alternative but a complementary to your marketing investment


Contrary to popular belief, CDP is not an alternative investment to other components in your marketing stack. On the contrary, it offers great value in terms of being complementary to your other investments and ensuring their healthy and effective operability.

Creating a centralized data hub has never been more important than it is today. In this context, CDP ensures the unification of the data while enabling the ability to extract meaning from it by providing it a holistic identity.

While CDP provides a unified view of the customer journey at the data layer, it also generates long-term values for each department that are responsible for corresponding touch points throughout the journey.


Where Does A CDP Add Value?


In summary CDP,

• Maximizes interactions and conversions by creating a unique view of the customer

• Allows us to put the customer at the center (this time, finally!)

• In this way, it affects marketing efficiency and customer experience from top to bottom (in a good way)

• With the unique customer view it creates, it enables the teams and departments within the company to work with greater engagement with each other and as a result, with improved efficiency

• Maximizes the efficiency of your MarTech investments

• It allows you to consolidate the data silos and saves you from the ‘siloing’ problem

• Increases operational efficiency and agility

• Allows you to perform real-time data activation

• Enabling us to combine 1st and 3rd party data, it gives them a unique and holistic view

• Increases the quality of Target Audiences many times over and ensures that they are manageable from a single perspective




As one of the most important points underlined by the doctrine of Modern Marketing, it is really a big challenge collecting (and owning) the data of anonymous users, independent from advertising players and, platforms they provide.

In the past 6-7 years, DMPs have brought a very effective solution to this problem. CDPs also contain this functionality in their context and from this perspective, they contain the values offered by DMP.

DMPs also had a very important value proposition, such as transforming the anonymous data they collect, convert them into target audiences and, activating these target audiences in advertising channels, which we can say that this functionality can also be provided by many CDPs.

As for the most obvious difference between them and a scenario that is supported by DMPs but cannot be realized by CDPs, we can bring up the leveraging the use of 2nd party data. DMP platforms, as they went mainstream in time, provided a very effective ground for collaborations between brands using the technology.

Thanks to these aspects, brands started using each other’s data as for the “2nd Party Data collaboration” projects and they were able to use them in a very safe, privacy-first environment and in a cost-effective way.

We observe that this very useful but not vital feature is not provided by CDPs at first glance. However, we can say that as the number of brands using it increases over time, it can be easily covered.

Another important difference between a DMP and a CDP is that DMPs have many integrations with advertising platforms for years and their ID Graphs are recognized by the ad environment for so long. This also brings an important advantage to DMPs, although it is still unclear how this advantage would be fulfilled in the upcoming cookie apocalypse.




If you are on your way to becoming a truly data-driven company, we can easily say that you have no other choice but starting your learning curve on CDP context. Regardless of the industry your corporation is in, it is necessary to calculate the cost of not making timely initiations for these investments.

Which one is more expensive, to make an investment or not to make an investment in this direction? How about evaluating this together?

Today, it is the vision and labor of qualified people that still produce value. We expect too much from AI and ML technologies, show some reluctance to put real labor on the work needed in marketing management. The muscle strength brought by ML and AI will become very important components of CDPs in the future, but today, while we’re thriving to extract meaning from consumer data, we still get the greatest support from the creativity and labor offered by the human mind.

Today, as of starting of the new decade, CDPs have become the biggest supporters of the human mind in this manner, with their ability to regulate the flow of complex data in the best possible way.

They combine these complex flows and enable the use of these data in unique ways, and the aspects that enable data usage scenarios that have not been realized until today.

With these aspects, it would not be difficult to say that they quickly reached a unique and irreplaceable position in Modern Marketing architectures.

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