“AI is now also improving the online shopping experience for consumers as well as retailers like most other fields. But exactly how it is doing so, what is the speed of its growth and what are the challenges that we may face are the burning questions. Most retailers are already using AI into their ecommerce processes from virtual assistant chatbots to customized shopping experiences.”
“Some predict that bots are the new apps…Consumers are overwhelmed with apps, and they prefer to converse on the messenger apps they’re already on. If you think about it this is a natural progression, considering that messaging is the root of all mobile communication. 50% of U.S. mobile users haven’t downloaded an app in the last year, but billions of people are already using messaging apps.”
“One of the reasons the chatbot has so much potential for businesses is its ability to scale. In 2016, 1.6 billion people used mobile messaging apps. That number is expected to reach 2 billion people, or 80% of all smartphone users, in 2018.”
This is an infographic developed by ShivonZilis.com titled The Current State of Machine Intelligence 3.0. Also, be sure to read the associated post. Here are just a couple of my favorite quotes:
“We’ve had a few people tell us that the biggest predictor of whether a company will successfully adopt machine intelligence is whether they have a C-Suite executive with an advanced math degree. These executives understand it isn’t magic—it is just (hard) math.”
“Then, if you do understand how this technology can supercharge your organization, you realize it’s so valuable that you want to hoard it. Businesses are saying to machine intelligence companies, ‘forget you selling this technology to others, I’m going to buy the whole thing.'”
“The basic premise of Artificial Intelligence (A.I.) was originally that human intelligence is predictable enough that it can be simulated with computers. As such, A.I. is a broad field involving many areas of research. This includes computer vision, language recognition, decision-making.
In more recent years, A.I. has also acquired other challenges including machine learning/ deep learning, as well as robotics as a whole. In fact, if you were to ask the average person what they thought of when someone mentions “artificial intelligence,” it’s likely they would say “robots” — thanks to pop culture: TV shows, movies, comics, books and toys.”
One of the key challenges of building a business case for a nascent industry such as AI eCommerce is trying to find the data to support and justify your assumptions for lift of: conversion, AOV, revenue and more.
That, combined with a substantial amount of vendor research, has led to the development of this infographic that I’ve titled “Top 10 Data Points for AI eCommerce.”
Also, please take note of the source links. These are the vendors that have produced and published their case study data. If you’re interested, you’ll find even more data and material on each of their sites.