Artificial intelligence (AI) and machine learning are offering ecommerce practitioners many benefits, from chatbots to multichannel customer support to online store features like a virtual fitting room – all allowing capabilities to provide exceptional shopping experiences.
Therefore, to stay competitive in today’s market, you need to view AI and machine learning features as something you should invest in. But first, let’s take a look at why AI and machine learning are considered game-changers in ecommerce and what is the basic difference between them.
Current influence of AI and machine learning on ecommerce
The influence of AI and machine learning on ecommerce is expected to continue growing. According to different sources:
- Implementing AI and machine learning could save a retailer around $340 billion annually (according to 400 surveyed retail executives);
- 47% of online retailers say that they already have a defined AI implementation strategy;
- Overall retail spending on AI will reach $7.3 billion by 2022.
Indeed, investment in AI and machine learning can substantially boost sales and benefit brand exposure. However, the implementation of AI in ecommerce can also solve a $300 billion-dollar problem, which has to deal with ill-fitting clothes. With the help of machine learning and its predictive solutions that capture 3D body scans of consumers can solve this problem for you once and for all.
Ecommerce practitioners also expect AI and machine learning to bring them some other important benefits, including:
With all these convincing numbers, it’s hard to underestimate the influence of AI and machine learning on your ecommerce business.
However, if you’re just starting your digital journey, the implementation of AI and machine learning can bring a lot of questions. Even as basic as what’s the major difference between the two?
Delving into AI
Loosely translated, artificial intelligence presupposes introducing human intelligence to machines. This term is wide in scope, so it wouldn’t be correct to call it a solution, a program or a system.
It is a widespread misconception to call AI a system. Rather, AI is implemented in a system, it is a part of a system.
In general, AI is a part of computer science, aimed at analyzing how to train machines how to do things that humans currently do better.
Controlled and supervised by humans, AI can change the way how many aspects are approached in a particular industry. Feng Guoping, an investigator at MIT’s McGovern Institute says that, although AI once evoked great concerns, now its contribution to different industries, like healthcare, manufacturing and even retail, are hard to underestimate.
According to Mr. Guoping, whenever a machine copes with and solves an algorithm, this is recognized as intelligent behavior, hence, AI.
AI has three basic levels:
- Artificial narrow intelligence (ANI)– also called weak AI, is the technology that already exists. You’d be surprised to find out that such technologies like Alexa, Google Assistant, and Siri are all based on weak AI. Talking about ecommerce, weak AI is used in different payment systems and is incorporated into fraud detection programs. Why weak? ANI usually uses a database and cannot go beyond the tasks that are already assigned to them.
- Artificial general intelligence (AGI)– these AI-based systems are comparatively as intelligent as the human brain. The main difference of AGI is that it can improve itself, based on a particular database. There are no particular outstanding AGI inventions that influence ecommerce industry, as the technology itself is very difficult to implement.
- Artificial superintelligence (ASI)– this level of AI describes a technology that is more powerful than the human brain. ASI surpasses human intelligence, thus solving the algorithms that humans cannot solve. The technology doesn’t exist yet, but it is the AI level that raises questions and concerns.
So, to sum up:
- AI is a part of a system that makes a machine intelligent and capable of solving the tasks that humans are currently performing;
- It is a vague and changeable term that depends on technological advancements;
- The research on AI is still not sufficient enough to help us discover its full potential. However, ANI has already contributed to many industries, including ecommerce, for instance, helping make payment transactions safer.
Clarifying Machine Learning
Opposite to AI, machine learning is a more researched topic.
Simply put, machine learning is the ability of computers to collect information and “learn”. Machine learning enables machines to learn by themselves, with minimum intervention from humans. Machine learning trains computers to recognize algorithms and find solutions based on their knowledge.
The best example of machine learning is a chatbot. This technology is gaining momentum in almost all industries that have to deal with regular interactions with customers. “In real estate industry, for instance, machine learning-based chatbots help customers find a suitable apartment online based on their location, language, and search history,” says Martina Powers, a front-end developer at the international real estate company Flatfy.
Speaking about ecommerce, many companies use chatbots to communicate with customers, collect tickets (requests) and search the database to find a solution based on matching keywords.
H&M’s chatbot, for instance, can answer basic questions, and connect customers with an assistant if the request doesn’t match chatbot’s database:
This technology can save ecommerce businesses a lot of money, as it can substantially decrease the number of employed customer support representatives and reduce the number tickets (for instance, if a hundred of customers ask the same question during a certain period of time).
What’s the Difference?
These two technologies are often confused because companies often prefer one over another. For instance, you can use a chatbot to communicate with customers, but you don’t introduce any ANI technology.
Yet, there’s no difference between these two. Machine learning is not a separate technology but rather a part of the AI. As artificial intelligence is a broad term, and machine learning is a technology that shows how AI can be implemented.
Benefits to Ecommerce
Even though AI and machine learning are both to be studied more, there’s no doubt that both of them bring important changes to ecommerce. You can already see the results: intuitive search, enhanced interactions with customers and even bringing the solution to the problem of ill-fitting clothes. All this is possible thanks to AI and AI-powered machine learning systems.
What do you think the future influence of AI on ecommerce will be? Share your thoughts with us!