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Over the past 10 years, there have been various technological advancements in the retail industry. One of the significant developments, for example, has been machine learning (ML). What is machine learning? Why does it matter in business? Is it the same thing as artificial intelligence (AI), or how does it differ? To help answer these questions and give you a general overview of machine learning in retail and its benefits, here is a look at the basics.
What Is Machine Learning?
Machine learning is all about giving computers the ability to learn from data, without having to be specially programmed. What this means is that as the machine observes and computes user behaviors, interactions, and decisions, it automatically knows how to use that information to update itself and improve systems. In retail, this can facilitate demand forecasting, price formation, fraud detection, personalized offers, logistics, and more.
How Does It Compare to Artificial Intelligence?
Machine learning is a kind of artificial intelligence. With AI, computers mimic human thinking and logic to carry out tasks, and ML is a specific way they do that.
What Are the Benefits?
For retailers, machine learning offers many advantages, particularly in the online sector. Do you want to stay ahead of your competition, increase sales, and lower costs? ML could be your solution. Here are a few examples of how it benefits retailers:
- Recommending products to customers: By tracking a customer’s interests, ML can skillfully create a recommender system of highly personalized offers for shoppers. This not only makes the consumer feel understood, but it also encourages more purchases.
- Pushing out targeted ads: Led by an in-depth understanding of customer behavior, ML knows when to send targeted ads — and to whom. It can find and target customers who are most likely to buy, using data from e-commerce platforms, social media, and more.
- Automating touchpoints: When a customer hasn’t purchased from a retailer for a while, ML can automatically send an email. When someone abandons a shopping cart, it can know to reach out. This frees up retail staff to focus on other, more creative projects for the good of the business.
- Predicting customer behavior: Another great benefit of ML is being able to intelligently anticipate how customers will behave in the future, based on their behaviors in the past. This enables more personalized marketing, building customer loyalty.
- Predicting inventory needs: The algorithms in ML can also help retailers know how much inventory to stock. This helps purchasing managers know what and when to buy for the best store profits.
If you’re interested in learning more about machine learning in the retail sector, including a breakdown of how it works, take a look at the accompanying resource. In it, you’ll find information on how machine learning is used in the retail world, more examples of benefits, and statistics relevant to how AI and ML are being used in retail today.
Bridgette Barry is director of marketing for Aptitive, a modern data and analytics consulting firm based in Chicago. From business strategy to technical development, Aptitive’s experienced data and analytics consulting team works with clients to develop tech-forward solutions that help them reach their business goals.