Consumers want to buy new products, and it's the company's job to make that job easier. In years past, that responsibility generally came in the form of simple advertisements: television, radio, newspaper, etc. These days, it's becoming more common for companies to present products to their customers in more nuanced and discrete ways.

Technology is a big participant in this revolution. With increasing software capabilities and more user-specific data sets, companies can now target their ideal customer almost down to the foot. While this may sound like another case of Big Brother knowing too much about your private life, it also has the dual effect of making your life easier, simpler, and faster, in getting the products you want without doing a ton of searching.

Companies want to know who each and every one of their customers are, so that they can better sell to them. They want to know who you are, what your interests are, what general geographic location you live in, how much education you have, etc. They use this data to better segment their marketing lists, so that they can deliver timely content to you when you need it.

A company that specializes in natural living may have customers that are interested in their resources on a natural lifestyle, while others are just looking for something specific like "Thrive Market coconut milk". As such, they'll be sent completely different emails tailor-made just for them. Complementary products or resources will normally be sent as well, all in an effort to give you more of what they believe you want in the first place.

In-depth algorithms throughout digital juggernauts like Amazon and eBay are constantly crawling through your shopping and browsing history trying to understand you as a buyer. They know which pages you've gone to, how long you've spent on each page, and even how far down on that page you've been. If you leave a review, that is logged away in their internal database as a particular construct just for you.

All of this means that the next time you log onto that particular website, they have a variety of offerings that they believe you might be interested in; no matter how random they may appear, each one is the result of a specific mathematical result. This appears as a sign saying "Customers Who Bought This Also Bought" or "Frequently Bought Together." When you see those flags, you're looking at a suggested buy from the company itself.

Everything you put on social media is used by that social media software to advertise to you. It's the payoff of sites like Facebook, Twitter, and Instagram being free in the first place: in order to make money, those sites aggregate your data and allow third-party advertisers to tap into it for marketing purposes. While privacy advocates have called for this type of data collection to stop, it's not going anywhere anytime soon, and that's largely because the information collected is voluntarily given anyway.

Advertisers rely on this bevy of data to pitch their various products to you. By knowing what pages you like, your interests, the ways you interact with various posts online, they can suggest products to you through targeted ads that they believe you may be interested in. Furthermore, they also know your buying history, average household income, and whether you respond better to desktop or mobile ads. They know exactly what to pitch to you, where to pitch, and the manner in which they present it to you.

100 years ago, all of this big data collection would have been a dream, but advertisers today have access to a whole host of tools and software solutions that can help them deliver the perfect product to you at the perfect time.