To say that Amazon is confident about how well the company understands its customers would be an understatement. For years they’ve successfully recommended products that they think are of interest to their shoppers. Now, they have the technology in place to go a step further.

 

The company does not plan on sending toothpaste to a customer who they feel is nearly out of his favorite brand. However, they are going to use guesses and estimations to determine where to ship products based on the anticipation of demand. The new technology was discovered by The Verge in 2014 and could have a few interesting applications.

 

Predictions Help Amazon Increase Shipping Efficiency

 

The first thing that this technology does is increases shipping efficiency. Amazon became the world’s most famous e-commerce site and application because they have a ton of stock and ship quickly. Any improvement they can make in that area give them a competitive advantage.

 

Companies are relying more heavily on “Big Data” every day and Amazon is leading the way. Developing a whole new “insight-driven supply chain” will transform the retail and e-commerce landscapes forever. Since companies smell a chance to use AI to expand their profits, they will jump at the opportunity. Amazon is merely leading the way as they continue to attempt to pressure their competitors.

 

When Amazon improves its supply chain, its customers benefit in the form of lower prices. Customers have shown a willingness to try new programs when they perceive that they will save money. Recommendations and anticipating order behavior is one way that Amazon will continue to drive down costs.

 

Possible Uses May Get a Bit Too “Pushy”

 

Few would argue with a company using data to their advantage to lower costs. However, people may not be so keen on any “forced” product shipping that happens because Amazon anticipated your need. That has never been done before in business and could run into a high degree of resistance.

 

AI continues to spark debates because it’s a whole new way of doing business.

 

As machine learning programs become more ubiquitous, it would be easy to see them over-reaching into people’s daily lives. The most obvious example would be if Amazon did send you toothpaste when they thought you were running out. Perhaps they weren’t aware that you already bought some on discount on your way home from work. Would any customer want to go through the trouble of returning the package from Amazon that they didn’t order in the first place?

 

Is the World Ready for Product-Picking Robots?

 

Such questions will need answers before new recommendation engines like this see wide-scale deployment. Amazon is a patient company which reinvests in their technology. They will most likely bring new recommendation tech online incrementally. As users respond to the program, they will probably continue to roll it out to more and more people. Naturally, while they’re doing this, their competitors will have to keep up and offer alternatives.

 

The average user enjoys cogent recommendations in the proper context. There’s little doubt that suggesting a battery pack that’s not in the box as an add-on to a sale of a camera is a timesaver that everyone appreciates. However, when boxes and boxes of stuff show up at people’s door without them having ordered it, there could be an issue! The key will be just how valuable the recommendations are and if they improve people’s lives. Companies only get as big as Amazon when they’ve proven themselves to the average consumer.

 

Consistently good recommendations will help increase the usage of this particular technology. If the AI also helps lower prices, the chances are high that the customer will want anticipatory shipments. After all, smaller costs are the prime reason that Amazon has become as dominant as they have in recent years. There’s no end in sight for this trend, and as this patent shows, Amazon is not resting on its laurels.