A robust customer data platform will enable your business to have a competitive edge. It empowers your data teams to make data an in-house differentiator as well as a core competency. However, building a customer data platform can pose as a big technical challenge. The following are the common obstacles you will come across when building your own customer data platform. After all, knowing will put you in a better place to get it done right.
You would have a crystal ball in predicting the challenges and opportunities will come across in the future in an ideal world. In reality, it is nearly impossible to consider and brainstorm all questions and data points. Additionally, spending your precious time on the world of “what ifs” will end up at decision paralysis. The problem emancipates when you have not integrated all key sources leading to rise in data gaps. Teams will often stop relying on the data and start making decisions based on what they think is right which often leads towards the wrong path.
Absence of standards
Clear standards are key in life and business. Disparate datasets with different schemas can be difficult to join. Data varies on where they originate from. For instance, data from your email service provider are stored in different schema from the data from experimentation tools or web. The data arrives at your warehouse with different timestamps and it is up to you to connect the data sources as well as present accurate and up-to-date insights.
Fragile ETL pipelines
A significant time is spent on integrating, cleaning and maintaining ETL pipelines by data teams to come up with a holistic user view. Incorporating all your data can derive up costs consuming a lot of your data resources resulting in reduction of the amount of time required to delivering insights, taking action, as well as developing predictive models.
Complex identity resolution
Data teams use a lot of significant internal resources and spend a lot of tie implementing complex identity resolution and reconcile pre-conversion, anonymous behavior, browsing behavior with email behavior with an authenticated behavior. It is because of these reasons that organizations are shying away from identity management vendors inclining towards building in—house solutions instead.
You can still leverage the power of customer data as a service
Despite the above challenges, you can still get customer data service that simplifies the process bringing clean, complete customer data into your business’ source of truth. If you get customer data as a service from a top marketing analytics company, data teams can cleanse fully and normalize the data based on a user-centric schema, model and verify data, and remove the daunting as well as error-prone parts of managing data pipeline/ETL processes to leave you to focus on more valuable data science.
Deciding on whether to build or buy a CDP
There is no doubt that a CDP can help to eliminate data discrepancies, improve customer analytics and segmentation, as well as support personalization. But, it can be difficult to decide whether to get a CDP or build one. The three key factors you need to consider before making the decision are: the available resources, track record of technology development as well as CDP time-to-market requirements and finally, your level to which organization seeks competitive edges through a CDP.