Imagine a luxury goods store at the airport and the crowds of people going back and forth. Some of them walk in; some don't. Most people are casually browsing, killing time waiting for a flight; some are potential buyers. Consultants' job is to welcome all the people coming, tell about the goods and walk through the promos. However, a good consultant can often distinguish a real buyer from a person who is just browsing. At the same time, a perfect consultant can also say what kind of good the person might be here for or even sell a product more expensive than the buyer was initially up to. It is a real-life example of customer segmentation and profiling.
As things went online, answering the question of how the ideal customer looks became much more complicated. As an opposite to older approaches where experts evaluate the population defining the demography and social parameters of the target audience, modern digital marketing consumes many more data points finding more sophisticated features that characterize people. Years ago, the characteristics of ideal clients might have sounded like age, gender, education and employment status, income level, and other basic information. Nowadays, we can connect alternative data sources such as social networks, geolocation, the power of cloud analytical products, and track the engagement history within our services. Netflix is a good example of tailoring content for specific audiences. For instance, they change the thumbnails for featured series based on local geographical preferences or recommend content based on similar types of actors, e.g., if you like Tom Hardy, would you like to watch some films with Logan Marshall-Green?