Not all your friends will like you if they really get to know you. Chances are, if they spent more time with you, they would treat you differently. They might start avoiding your calls and stop inviting you to parties. Or they might like you even more and stay lifelong friends.

The more time people spend with you, the more they know you. Obviously, there is an element of posturing - you are aware of their presence, so you act differently than what you would. But over a long enough time scale, the masks start to wear off and they get to see the real you. At which point either they think that they like you and want to spend more time around you or start finding excuses to avoid hanging out. More information allows them to estimate how much value you bring to their life and to make an informed decision. But they first have to invest time with you to get the information to make this assessment - a worthy investment to have a chance at making a new friend.

This model - investing in a relationship early on, collecting information, deciding as to whether or not the relationship is positive for you, and acting in accordance is uncannily similar to how modern consumer internet companies(MCICs) operate.

MCICs are not interested in friendship though. The relationship they want to build is the one in which they make the most money. Unlike human friendship, which can be quite complex to define and explain, this special kind of relationship generally has clear goals and metrics of success. One of which is maximizing the Customer lifetime value(CLV). The CLV is an estimate of how much money the company will be able to make from an individual customer over the course of their relationship. Customers with a high perceived CLV are good and others aren’t worth pursuing. But how can MCICs estimate CLVs of customers to make this decision? By collecting information, same as a potential friend would have to, to estimate your friend-worthiness.

Most people reading this interact more with their devices than they do with any single human being. Even interactions with friends are mediated by digital social media landlords. One could make the case that if you really want to know someone, instead of going out with them half a dozen times, spend an hour studying their activity on the internet. Chats, posts, emails, search history, what they buy, the works. That might paint a more accurate picture of the person than any information collected from human-human interactions.

And this is where MCICs get their edge. They can collect this digital information by letting a lot of customers use their products and services, sometimes for unsustainably low pricing, and learning from their activity(time and money spent on the platform, browsing patterns, likes, dislikes, etc.). They can also mine data that has been generated by these customers all over the internet(social media profiles etc.). Based on this information, they can estimate the CLV of their customers and discriminate accordingly. In a way, a few of these companies know you more than most of your friends.

If you were running a bakery, think about how you would treat your customers differently if you knew their income, address, and social media activity. People who live closer to the bakery, have a high disposable income, and follow a couple of dozen food pages on Instagram, would get a warm welcome to your bakery, regular complimentary muffins, and special offers on birthdays and anniversaries. These are the customers who have both the desire and the ability to patronize your business(high CLV!). You want to be in their good books.

People living far away(just happened to pop by the bakery in passing), having moderate levels of disposable income, might be treated with a little less warmth unless they order a 5-pound blueberry cheesecake on the spot. In fact, you might want to tell them that most of the stuff on the menu is not available except for the blueberry cheesecake. Because what’s the point of serving customers who will probably never come back to your bakery again.

Sounds practical but as a bakery owner, you never have access to this level of information about your customers. Let’s now take this whole setup into the digital realm, which is where we are headed as a civilization. You now run a digital bakery in the metaverse where people can log in to order food and the whole interaction happens digitally. Although it is your customers who open a window into your bakery through their ipads and phones, the window opens both ways. It allows you, through the use of some delicious cookies(pun!) and other sophisticated information collection mechanisms, to peek into your customer’s activity in the digital realm. Which pages they visit, which device they use, which apps are installed on their device(people with a lot of fitness apps might not be good potential bakery customers) etc. These pieces of information, while ostensibly innocuous, when put together and churned through a good model can produce the information we talked about earlier - income, address, likes/dislikes, affinity to buy muffins, etc. which would allow you to discriminate between a good and a not-so-good customer.

The digital realm also allows you to completely transform your bakery - rearrange your menu, change pricing, and offer other services, according to your assessment of how your customers are. Data and models(machines that translate data into information) allow you to discriminate among people. Instead of having to treat everyone equally, you can optimize your resources to cater to the few who deserve it and personalize your offerings to suit each customer.

This is happening already on a massive scale. MCICs benefit hugely from knowing us better. It is a huge competitive advantage to be able to collect the maximum amount of data about existing and potential customers, and have models that convert this data into information that you can use - income estimates, affinity to buy a certain class of products, political inclination, etc. Privacy and data ownership issues will somewhat impact the potency of such solutions in the short-medium term but in the long term, I feel we are moving to a place where these companies have a starkly clear picture of who we are and each product, service, and interaction is personalized.

As a corollary, each one of us will experience the digital world differently. The digital ream will be owned by these MCICs and will be tailored for each individual to increase their profits. At present, most of us still spend the majority of our time in the physical world, where we are subject to natural laws that are indifferent to our lifetime value or the goodness of our hearts. Even if companies what to treat us differently, in the physical world, there is only so much that they can do. If I walk into a luxury car showroom today, they will have to treat me the same way they would anyone else even though I would be unable to make a purchase.

With time, these MCICs will have enough data and expertise to be extremely discriminative in the way they treat customers. This will open a can of worms. Would it be okay for a telecom company to deny a connection to a low-income, low-CLV customer an internet connection? This might significantly impact that individual’s ability to increase his income and get better opportunities. Is it OK to charge higher prices for booking a cab for iPhone users(who are higher income on average) than others?[1] What level of discrimination is fair and where do you draw the line?

Companies that are able to collect and leverage customer data will have an advantage over their peers. It will allow them to be more efficient. Customers like us on the other hand will need to be increasingly aware that even if we scroll on our phones in the privacy of our physical homes, every click and scroll might potentially be used to profile and personalize(discriminate) the world for us, not always in a way that’s best for us.