• Aditya Singh


Updated: Feb 2

Imagine a world where the Terminator was no longer a figment of our imagination. The ruthlessly perfect combination of Artificial Intelligence (AI) and Algorithms with a literal killer instinct demanding that we surrender our freedom to think and live independently.

Although the idea of a John Connor saving humanity may sound surreal, the combination of Artificial Intelligence and Algorithms is quite real. Fast-tracking its way into our lives without most of us even realising. Here’s an example to provide some context.

During the height of the Information Age - also referred to as the Golden Age of Humanity - advertising was done mostly through television and/or billboards, radio - otherwise also known as ATL Marketing (above-the-line). On the other hand, in the Digital Age advertising is not only done through the aforementioned but it’s further reinforced through mobile phones, tablets and computers - just about anything with a screen. Professionally, this is called BTL Marketing (below-the-line) otherwise seen as Google Ads etc.

The point to contemplate here is the tradition of force buying that is perverse in our daily lives today. Not much has changed since the Information Age, what has changed however, is the degree to which we succumb to advertising and this is force buying.


The term Four Horsemen was conceptualised by Scott Galloway, a professor of marketing at New York University Stern School of Business. These Four Horsemen according to Scott are Facebook, Google, Apple and Amazon. The presence of each of these companies in our lives is so well entrenched that they dominate our daily lives, decisions and choices. What makes these companies so unique and successful is their ability to satisfy human needs and desires.

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Consider this every day when you switch on your browser (most likely, Chrome) you will find a hundred odd suggestions awaiting you. Maybe some of those likely suggestions emerged as a result of things you had previously searched for on Google. Or more likely, you will find suggestions for products/services that you’d given some thought but never intended to buy at that very moment. An appropriate question here would be: how is it that Google knows this and why is it recommending things that you’re not likely to buy RIGHT NOW?

Search engines and e-commerce brands track the movement of customers through their site using a host of digital tools. Doing so allows the algorithms utilised by these companies to track consumer thoughts consistently and use the information to target highly accurate and visibly amazing suggestions or Ads. What’s imperative here to understand is the psychological process of force buying. Brand/product hammeringis a simple yet effective tactic by which brand names or specific products are nailed into the minds of the consumers, forcing them to buy products. Extrapolate the number of times you watch an Ad over one or two months, and it’s almost guaranteed that you will be forced to buy. Now, a rational consumer may say such a bold statement is speaking in hyperbole, however, look into yourself and try to articulate how many times Ads have driven your decisions or choices. Even if these Ads did not necessarily materialise into an actual sale but the idea still stuck to the mind. While going back to it when required. For a brand, the establishment of such an idea in a consumer may possibly lead to a sale in the near future.

But why does this happen? In a recent article on the Born Group website, Mackenzie Johnson answers this as she writes, “Google has become the replacement for a higher power. In this modern age Google becomes the first place a person turns to when a question is left unanswered. Apple adds to a person’s sex appeal. When someone has an Apple product they are perceived as wealthier, fashionable, and increasing sex appeal. Amazon has become a ‘temple of consumption’ as it provides us with a seemingly endless assortment of products. With over 1.2 billion daily visits to their site, Facebook has managed to gather nearly one-sixth of the world’s population in their digital space on a daily basis. By appealing to our daily human needs, these four companies have grown to dominate the business world and play an essential role in our daily lives.” [1]

In a subtle yet clear manner what she attempted to explain was that the human mind functions in such a way that it desires what it does not have, and humans will buy what they desire. If a big discount offer running on Amazon is met with a degree of approval from a friend, chances are, you will most likely hear of it too! It is to this action of humans that Amazon so brilliantly caters to when it comes to marketing. In the last fiscal year, Amazon spent $18.88 billion on marketing and according to the company, the marketing cost was primarily divided between targeted online adverts, TVC (television commercials) and related marketing spends. [2] When a company such as Amazon spends such an outrageous amount, it is to ensure that the entire process of brand hammering comes full circle. Through such enormous marketing spends, Amazon gathers information, (re)targeting potential and existing customers with visually spectacular Ads. In such a situation, the idea of not only buying (say) a new phone from Amazon is registered in our minds, but the fact that we may buy & own one becomes a reality.

Thus, it is no wonder that in 2018 Amazon accounted for 35% of all online spending in the UK and 52% in the States. [3]

However, all of this is about to change in the future!

Scott Galloway postulated the concept of Algorithmic Commerce or A-comm in a recent podcast and how it may come to transform the future. Believe it or not, the entire history of companies gathering information on people, their behavioral patterns, preferences and choices has been leading up to this new age of selling products.


When we think of algorithms, we tend to associate them with big tech or big data companies. The association is true - but what we don’t ask, is how they use it or more importantly, how they plan on using it in the future.

Search engine algorithms utilised by Google, Bing, Yahoo and more importantly, algorithms used by Amazon, Myntra, Flipkart and other e-commerce brands determine what you and I see in our search or suggestion results. In fact, no two users will ever see the same results page (unless they are using the same device with the same login credentials).

The main purpose behind each of these high functioning, highly accurate algorithms is to understand consumer searches based on behaviour, preferences, and any other condition that may help define a consumer’s nature. Whether they are highly volatile buyers or habitués of adult sites; the list of human nature is limitless. And so is the potential of these algorithms.

Since algorithms study consumer patterns by the second and deliver results, services or goods based on these search engines or e-commerce brands are more likely to suggest things that you had never thought of. Essentially, it’s all a game of predicting as accurately as possible what a consumer may buy in the future.

Now, when data such as this is thrown into the mix with AI, it creates a bowl of multiple situations that allow algorithms to identify our needs even before we do. This phenomenon of predicting consumer wants and delivering products/services is called A-comm or Algorithmic Commerce. In other words, A-comm is a zero-click order fulfilment system.


Artificial intelligence in A-comm, as mentioned above, not only helps in tracking the digital footprint of consumers. It also helps in analysing and predicting the choices they will likely make in the future. This ability to determine individual online trends is just one of the aspects in which A-comm will change the way we shop online.

A different approach would also be to apply this same logic when it comes to people searching for information. Which may, intentionally or unintentionally, reinforce any biases that they previously had. Why? Again, because prediction functions on past searches and patterns - at least as the first set of data. Through Machine Learning, this system may be able to then predict future desires of consumers and we may go so far as to say that it may very well shape consumer thoughts, desires and choices. Something that you may not particularly wish to buy ever may still find your way into your life. Because marketing under A-comm functions in such a way that it fulfils an innate problem; the limitless desires of humans and the fact that we will never be fully satisfied with what we have.

Hence, A-comm is not only a system by which we may purchase products, it’s a trade in information and ideas that may very likely impact our thoughts and decisions. Due to its ability to reinforce prior biases, it’s highly likely that such a possibility becomes a reality in the future.

For brands like Amazon or Myntra, “Algorithmic commerce can predict what consumers are going to do online, and this is an incredible resource for any brand to have access to, especially when it comes to improving inventory management, marketing, and logistics.” [4]

However, a rational consumer may still be smarter than the average Joe. A rational consumer may refuse to buy a product that a brand chose to sell to the consumer, even if the consumer did not wish for it previously. And that’s where the problem of logistical nightmares may harass brands. The cost to re-package and transport the rejected product back to the warehouse is high.

In fact, even without the support of a-comm, many online retailers of multiple brands such as Flipkart and Amazon among others witnessed a sharp decline in sales in 2018, due to a high return rate. [5] However, we must expect such large online multi-brand retailers to forego this short term loss by innovating on their systems and a-comm may well provide the solution over the years.


Access to such a system generally provides a competitive advantage to brands, but sometimes it may even provide ferociously unfair competitive advantage. Which means that the emergence of new brands would likely be impossible and big companies will have a monopoly. This barrier to the emergence of new and young brands is due to the bigdata tech companies accumulating and soliciting millions of their customers from hearing of new brands, to even knowing about them.

When you create a system that collects data on what people like, dislike, how much they are willing to pay for a certain quantity and what; making it impossible for small brands to compete. Unless, of course, these small brands are able to create an innovative product or service.


A strong data infrastructure is inherently important to brands or special interest groups: that even as most of us consider ourselves spontaneous, dubious or unpredictable, our digital footprints - and the data we generate as a consequence tell a different story.

Often, as consumers of any sort of content, we are highly driven by thoughts, biases and habits that such data can be easily converted into actionable insights. With the right analytical tools coupled with Machine Learning in AI, brands and special interest groups can easily evolve from offering people what they had searched for, to what they may most likely want to purchase or buy into. And that is why we’re either living or may be jumping into an era of the blind. Where we will no longer be able to define or choose what we want and need.

And for any major brand this will be a gold mine.


[1] Born Group: Developing Your Business Strategy for the Digital Age with Scott Galloway, Key Takeaways

[2] Statista: Annual Global Marketing Costs of Amazon from 2010 to 2019

[3] Wunderman Thompson Commerce Futures 2019 Report

[4] Wunderman Thompson Commerce: How Your Shopping Trends May Be Determined by Algorithmic Commerce

[5] Entrackr: Amazon Has Highest Product Return Rate in India Than Other Countries

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