See the incredible ways retailers are using artificial intelligence to enhance your Black Friday and Cyber Monday experiences.
Discounts on Black Friday and Cyber Monday have become an annual ritual for many of us. At least everyone knows what’s happening on these days: there are products with incredible discounts in online and offline stores. Nothing new, you say? There is still one important change—artificial Intelligence (AI) has come into play.
This is primarily about big data machine learning, which has dramatically changed the rules of the game in the online battlefield between retailers seeking to use all available technological advantages in order to grab the largest possible piece of the retail pie.
Companies using AI in retail can get rid of the need to make hasty decisions. Because AI helps predict what consumers want to buy before they even buy it, AI has often been at the forefront of these discounts in recent years, thanks to machine learning being an incredibly powerful tool marketers can use to maximize consumer savings.
In retail, this technology has two main applications: demand forecasting and service personalization.
Traditionally, retailers have used Black Friday as a means to move stock that hasn’t sold in over a year—and at a discounted price. Thanks to the huge increase in the amount of data we generate and which retailers can collect and analyze, today they can predict where we will spend our money with more accuracy than ever before.
This means that pricing, inventory, and distribution can be managed more efficiently. At the same time, global retailers such as Amazon and Alibaba can locate distribution centers in accordance with regional shopping habits. This overall savings in transport leads to an overall reduction in operating costs and, ultimately, to a reduction in costs for the consumer.
In fact, today’s sophisticated learning machines are built around artificial neural networks designed to mimic the learning process of the human brain. After all, it is the most capable information processor known to exist and is capable of finding much more subtle signals and relationships. AI seeks to expand a classification-based learning system honed by perfect memory, lightning speed, and error-free computer logic.
The reason efficient classification is so important to the process is that it allows computers to learn the basic relationships between different but similar “objects”—be they products or people.
An offline store owner can manage their business by making estimates as customers come to a small store, one by one. But what if 100,000 of them show up in their online store every hour? That’s when the speed and ability to replicate machine learning systems come in very handy.
Retailing in the online age has long been driven by recommendation engines, which were originally deployed by Amazon and are now being used by nearly everyone who sells online. Initially limited to predicting what a customer might buy next by analyzing their past buying habits, data from a wide variety of third-party sources is now often added to the selling proposition.
These “You might also like…” suggestions are based not only on your previous purchases, but also on what the seller knows about your age, location, preferences, lifestyle, and family life.
Recommendation engines return the money spent on their development by offering the right product to the right customer at the right time—for example, on Black Friday, when, according to Adthena research, online store traffic increases by 220% compared to the average day.
These days, most retailers’ advertising budget is spent on online pay-per-click advertising on sites like Google and Facebook. The reason Tesco or Walmart spend so much on these channels is because of the sophisticated machine learning algorithms developed by both companies, as well as by many other startups.
PPC spending skyrockets around Black Friday and Cyber Monday as retailers increase the amount they are willing to pay per click as they know visitors are more likely to spend money than on any other day of the year.
Looking to the Future
The future of retail automation is incredibly exciting and promising and is likely to be powered by AI automation platforms and AI Apps. These platforms will enable retailers of all sizes to streamline their operations and improve the customer experience through AI-driven automation, personalized offerings, captivating products, and insight into upcoming consumer needs.
Undoubtedly, technologists will continue to invent ways to measure and predict our behavior more accurately. They will also use increasingly sophisticated tools to set prices at levels that are attractive to us as individuals and advertise in places where we are likely to see them.
First the advent of the internet, then big data, and now artificial intelligence have all contributed to transforming what we now call “shopping” into something that would be almost unrecognizable to those who lived just 10 or 20 years ago. This pace of change doesn’t seem to be slowing down, so buyers in the next 10 years will likely find things have changed just as much once again.
Muhammad Abbas is an enthusiastic dreamer and a workaholic to achieve that. He is a passionate writer, Cricketer, researcher, and Team Leader. He has contributed to many reputed blogs and is constantly on the lookout to reach authoritative blogs around.