This brings us to the end of this chapter. We had a lot to cover here, and it is natural to get overwhelmed by the amount of information we shared in this chapter. All of this will make sense when we proceed with the later chapters.
Let us summarize what we learned in this chapter.
We understood the concept of CDP. According to the definition, “A Customer Data Platform is packaged software that creates a persistent, unified customer database that is accessible to other systems”. A relatively newer concept in CDP is to leave out the database part. So, a CDP can refer to a software package that helps you connect your different sources of data (input) to your chosen destination.
One of the top challenges to great customer experience delivery is related to collecting, managing, and storing customer data. CDPs solve the challenge of collecting customer data from different sources and storing it in one place to create a unified customer profile.
We learned that a persistent Id is an identifier that can provide a single view of an individual across numerous devices, including desktop, mobile web, and in-app, without duplication.
Customer data can be divided into three types depending on the data origin: first-party, second-party, and third-party. Customer data can be classified into three types based on the nature of the data collected: identity data, descriptive data, behavioral data, and qualitative data.
Identity resolution is the process of uniquely identifying the user who is using different channels to interact with the brand. It is the ability to persistently recognize a unique entity across all digital and physical channels to build a rich profile to personalize the customer journey. Identity resolution is done using identity stitching.
There are mainly three types of CDP: MarTech Suites, engagement-oriented CDP, and data management-oriented CDP. The list of events that should be tracked is called the tracking plan. Events include any actions the user takes- like submit form, account created, and add to cart. The CDPs available today in the market suffer from some challenges, mainly the inability to scale, and difficulty getting data in real-time, among other challenges.
In the next chapter, we are going to discuss the main topic of this book: Salesforce Data Cloud. We will understand how Data Cloud solves common challenges that plague the modern CDP and how to best utilize it. Are you excited? If you have come this far in the book, we are sure you are!
If you can answer the following questions and explain them to someone who has not read the book, consider yourself knowledgeable enough to proceed to the next chapter:
- Explain what a CDP is and how it works?
- What business challenges do companies face while managing customer experience delivery?
- How does a CDP solve challenges faced by companies dealing with customer data?
- At a high level, how does a CDP work? What is the typical workflow for a CDP?
- What is a persistent ID?
- What are the different data types CDPs need to handle?
- What is identity resolution, and how is it done?
- What do you mean by a Tracking plan?
- What are events, event properties, and user properties?
- What are the challenges that the current generation of CDPs faces?
If you wish to read more about SalesForce than what we could cover here, please go to the following links or resources: