Just like Don Corleone in the epic Godfather movie, the folks at Washington-based e-commerce giant Amazon are about to make offers to their business partners, the company hopes they can’t refuse. That the firm, like Corleone, relies on ‘capos’ to enforce these offers, can be doubted, but they have a treasure the Mafia never possessed. Amazon’s immense knowledge about their business partners, generated from all sorts of data, takes the firm to a stage where it plans to rely a huge part of its channel domain on its recommendation system. But let me explain.
After establishing overnight delivery years ago and the introduction of the ‘drone delivery service’ last summer, the firm filed a patent in January with the bulky name ‘anticipatory shipping’. The idea behind it could revolutionize the e-commerce environment. According to techcrunch.com the system is the next ‘step towards cutting out human agency entirely from the e-commerce roundabout’ (1). When set up properly the automated collaborative filtering algorithm will learn from the behavior of registered consumers and anticipate what they could possibly be interested in, before the consumers themselves think about it. When matched with a specific product, Amazon plans to wrap the item and send it towards the potential customers before an order has been placed. This means slashing down shipping time by relying on clients’ historical buying patterns, preferences expressed via surveys, demographic data, but also browsing habits, wish-lists and even mouse movements (1). Essentially, the system entirely outsources the consumers’ shopping experience and direct communication with Amazon on basis of an online recommendation agent.
The patent states that packages are sent without ‘completely specifying the delivery address at the time of shipment’, and while the package is in transit the correct address will be labeled in a logistic hub or even in the delivery truck (1) (2). Amazon expects, that while the package is already on the way to a certain geographic area, a potential consumer in that area will place the order and is delighted, when the package arrives only a few minutes or hours later.
But what happens, if my sister, who is visiting, browsed through Amazon too much and triggered a shipping to my house? Does this delivery without prior consumer-company interaction decrease the trust in the company? Amazon’s answer to these faults is to quickly shift the package’s purpose from sales to advertising by disguising the anticipated item ‘as a promotional gift to be used to build goodwill’ (3).
The whole idea still seems a little futuristic to me, and I doubt that a recommended product for my sister will create any goodwill by me. However, it points in a direction for the future and tying on to prior class discussions, I am not only curious what tasks marketing professionals will work on in a couple of years, but I’m generally wondering how big data, information systems and automated machines in general will change or replace jobs in logistics, operations and supply chain management!
In this sense,
Hasta la vista, baby!