How to boost your Customer Data Platform

What is Customer Data Platform?

A customer data platform, or Customer Data Platform (CDP), is a tool that brings together customer data from across the organization into a single system and displays each customer as a single profile, regardless of the source system of the data.
Customer identification is done through data consolidation, through which data from several different systems is collated, adjusted to customer profiles and collected on the same platform.

The differential value of customer data platforms is the automated alignment of data from various systems, and the matching of information from the customer's profile and behavior. All of this allows the platform to identify the same customer across all systems, and consolidate them with master data and transaction data.

Your customer's knowledge will exceed anything you're currently used to.

For example, imagine opportunities in terms of staff turnover prevention, comprehensive product development analyses, and better and faster customer service. Or, what about personalized communications and sales?

If the CDP can do all of that, then why do I need a data strategy?

A CDP can quickly become a place with a large amount of irrelevant information and a random record of customer behavior. Information that, at best, makes the system obscure, but at worst, can create poor customer experiences or illegal data recording.

That's why a data strategy is necessary.

What is a data strategy like?

If you want to get the most out of a customer data platform, you have to do some previous work that should lay the foundation for linking people's data. Without these rules, the system will quickly turn into confusing information and will be virtually useless.

We can do the exercise of seeing the set of rules as a constitution for data governance. Without a constitution, the data landscape will quickly turn into anarchy because there are no adequate institutions to secure government.

Description of data governance

For good data governance, some general rules must be identified on the way in which data is collected, rectified and entered into the platform. The set of rules must be in place before the first data is entered into the system.

It should be a simple set of rules, and it's critical that they are known to the employees who use the system.

To enhance knowledge of the set of rules, you can create a training session for those people in your organization who will occupy it. In some systems, you can insert small notes in the user interface in the different sections, so you can establish naming or formatting rules. You can also share them from a document management tool such as SharePoint. The most important thing is that you can easily change the rules in a centralized manner and thus keep the guidelines up to date and in order.

The set of data governance rules can be divided into 3 small sections that form the basis of good governance.

1. Data Tracking

Data tracking is a simple summary of:

• What data do you collect
• Who is responsible for the data collection process
• What source system is behind the collection
• Why data is being collected

2. Data validation

Data validation is a description of who owns the data unification process. Here it must also be described if the data is loaded in the CDP's own formats, or if the system is fed with raw data, which must then be aligned with the tools of the customer's data platform, such as Segment Protocols.

Data validation also contains rules for which unique master data, customer profiles (for example, email, phone number, credit card number, customer number) are established, and rules for when data must be written, overwritten or deleted in a given customer profile.

3. Data application

Data application refers to the management of functions in the CPD, or in the source systems. Administrators are the ones who define access to data and features at the user level. Role management ensures that changes go through the previous validation process and are approved by the right people.

Role management also includes the division of responsibilities for debugging tasks in the system. Because let's be completely honest. Even with the best management, obsolete data will need to be cleaned up. For the same reason, we recommend that you create a cleaning cycle and put those responsible in charge of the tasks.

Decide on each data entry

It is important to ensure that the platform collects only the data necessary to carry out your activities. Excessive data, as mentioned above, can cause confusion and in the worst case scenario can lead you to disagree with the law.

To avoid this, each data entry must be evaluated based on 3 questions:

1. Who needs this data?
2. What is this data for?
3. If we didn't collect this data, could we continue to run the business?

If you can't answer the first two questions, don't save the data. If you answer yes to question 3, don't save the data either.

Should historical data be migrated to the new platform?

It can be tempting to migrate all the historical data to get some volume on the customer data platform in a hasty way. But that's not necessarily a good idea.

It's important that you follow steps 1 and 2 mentioned above, and that you also follow the rules you've established for the system. Remember, a database with old data and a poor structure creates distrust among the organization's users and can ruin the implementation of the system, and therefore, the value of the investment will be harmed.

Know your organization's data silos

It is called a “data silo” when data is collected by different departments of the same company and is stored separately from that accumulated by other departments. It creates blind spots in your data and means you don't get a full view of your customers.

If you want to avoid data silos, or want to eliminate existing ones in your company, then collaboration between departments is required.

You must have a full understanding of what data is collected and what it is used for. To do this, you should start by figuring out what tools are used to collect customer data in your organization. From there, build on what information the tools collect.

You may find that data is locked inside a silo for legal reasons. Or perhaps, that the data is surrounded only by the lack of communication between departments.

But thankfully there's a solution for that! And, as we have been explaining to you, a CDC is a great opportunity to bring data to life throughout the organization.

A data strategy is a simple plan that will secure systems in the future

With a good and simple data strategy, the framework is created so that you have adequate data hygiene at all times.

We are sure that you will be on the right track.

Remember that to ensure that the customer data platform works properly and you take advantage of all its benefits, it's important to constantly be aware of the basic requirements within your organization:

• Gradually eliminate data silos by linking and storing data in a central location
• Increase data accuracy by minimizing redundant data and overlapping customer profiles
• Collect all customer data across the organization so that all parties only have to search in one place

All of this will allow your company to effectively bring customer data into play for analysis; product development; market research; customer service; upstream, cross and upsell; recovery campaigns and much more.

Now you know everything you need to implement a successful customer data strategy, and of course, also benefit from the properties of your CDP.

How can we help you?

If you need more information, do not hesitate to contact us.