A Guest Blog Post by Ravindra Savaram
When we think about artificial intelligence(AI), the first thing that comes to our mind is a self-driving vehicle or a Terminator-like robot. Both robots and AI are not exactly one and the same. Though often utilized together with bots, artificial intelligence particularly refers to the stimulation of human intelligence processes by machines. AI powers many technologies that we utilize on a daily basis.
Whether AI is something that you have been monitoring for a while or it’s something that you have just come across, it is undeniable that AI is beginning to influence many industries. One place where it is really changing things is e-commerce. From creating personal buying assistants to personalizing the shopping experience, artificial intelligence is something that retailers cannot ignore.
Many areas of e-commerce are ripe for innovation driven by artificial intelligence. Every enhancement to logistics efficiency, recommendations, pricing, or marketing provides retailers an edge over the competition. Retail creates and consumes large volumes of data from various channels. In fact, there is so much data that it’s not possible for a human being to analyze it. These are the ideal conditions for machine learning.
For various data analysis methods, machine learning is the overarching name. In these methods, the computers get insights in data without actually being told where to look for the insights. When exposed a large amount of data, machine learning algorithms can extract patterns and utilize them to generate predictions or insights about the future conditions.
When you upload a cat picture to cat Google Photos, it knows that the object in the picture is a cat. The code that identifies the cat is not written by a human but it is developed as a result of exposing the algorithm to a large number of cat photos(also, the photos of things that are not a cat).
The same principle explained above can be put to use in many e-commerce areas. For instance, the retailers have become really good at recommending products that are related, but the people who do online shopping knows that the recommendation engines get it wrong very frequently. The recommendation engines are quite limited as they can have access to only a small set of data and the ways they can reason about that data are restricted. Machine learning helps merchants find much better ways of modeling the behavior of users so they can make close to exact recommendations about what a customer is interested in buying. With machine learning, the AI can make predictions based on past data. The predictions include what customers will buy next, their typical price threshold, their preferred device and channel, and so on.
Today, the online retail industry is constantly presenting new challenges to COOs and CMOs when it comes to pricing. There is a fierce competition among the e-commerce brands of all sizes and guises. Even for an online merchant for a 1000 product list, somewhat tweaking in manual price can become a task that is almost impossible to accomplish. The environment is changing constantly – rival prices, logistics, currency conversions, and delivery rates are just a small sample of numbers or circumstances prone to change continuously.
The tweaking of prices in real time can be accomplished with artificial intelligence depending on multiple data sets including stock levels, resource capacity, internal operations, customer demand and behavior, and market conditions.
High-level of Assistance
The personal shopping assistants were a luxury of the rich or famous once upon a time. Artificial Intelligence has shaken up this scenario and in the process, revolutionized e-commerce. This conversational and intelligent technology has extended to customer service as well. The chatbots and personal digital shopping assistants can suggest the best available products to new visitors in a manner similar to humans, recommend new deals to your returning customers, answer the queries of a customer and provide suggestions, and alert customers when products they may prefer to purchase come into stock or change in price.
By merging intelligent neural networks with massive data sets, the applications of artificial intelligence will help e-commerce companies to build unparalleled competitiveness in the market. The impact of Personalized Merchandising supported by artificial intelligence on the e-commerce industry will continue to rise in the coming years. They not only optimize or automate current processes but also help retailers to avoid common pitfalls of manual approaches, giving customers an enriched experience to maximize profits.