Data comes in all shapes and sizes. It is structured and unstructured. It contains letters (characters) and numbers (numeric) and can be strung together in sequences, series, strings. One element that gives data an asset value is how these various types and sources of data are combined and used in concert to help data consumers make better sense of things. We call this the 4Ps. We use the 4Ps to address current and future capability of data use and consumption.
Below is how we define the 4Ps of Big Data:
At Crunch Data we focus on: Information, Analytics and Decision Support capabilities. Data is at the foundation of this “stack”. In another blog I will go into detail about the stack. We find it critical to discuss the 4Ps in the context of the stack because data will inform the questions you ask in business analysis, will help determine what tools to select based on your information or analytics capabilities and will serve as a guide for how you structure or adjust your Information Management strategy.
Some examples of how to use the 4Ps:
- Use the 4Ps model to document known data sources current in use or planned for use
- Leverage for data gap analysis
- Identify potential suppliers for supplemental sources
- Use as discussion point for Information Management strategy and planning
But how do I apply the 4Ps to a function like Marketing?
Well… why not conduct a data mapping exercise to understand how to map the data 4Ps to the Marketing 4Ps. We have color coded the source of information and illustrating how it ties into to specific marketing fundamentals. Also note: we have documented the volume, velocity and variety of data that may pass through into marketing performance management systems or systems of record for use in analysis.
So why is all this important?
Understanding how you can apply the 4Ps to your current or planned analytics effort will put you in a better position to possess and acquire the right kinds of data; Data that can be used to make money or save money. Data that can be accessed and understood. Data that is trust worthy and that can withstand market and/or organizational scrutiny.
Platforms and Data Types Used for Marketing Performance Management (Not exhaustive)