Machine Learning Applications in Retail: Use-Cases for Marketing, In-Store Management, and Business Processes
Observing and analyzing changes in consumer behavior, habits, and preferences year after year is a fascinating exercise in scientific research. Of course, marketing and the art of selling are changing as a result of shifting customer values and technological advancements. In the twenty-first century, retail and marketing have almost entirely shifted to the digital realm. Furthermore, machine learning and artificial intelligence technologies are continuing to revolutionize this industry at an unprecedented pace. In this article, we’ve decided to compile a list of the most promising applications of artificial intelligence and machine learning for retail and e-commerce in 2020 and beyond.
What Are Machine Learning and Artificial Intelligence in Retail?
In the retail and e-commerce industries, artificial intelligence and machine learning refer to a collection of data-driven technologies that are capable of performing lightning-fast data analysis and making pattern-driven predictions. Perhaps this is all there is to know about machine learning and artificial intelligence in retail, as all of their additional features stem from these two fundamental capabilities. Following that, we’ll go over some retail machine learning applications, and everything will become clear to you.
What Applications Does Machine Learning Have in E-commerce and Retail?
As stated in the Exchange Solutions White Paper, “machine learning is powering an increasing number of technologies that touch every point of the supply chain for retailers.”
E-commerce and retail are two terms that are used interchangeably.
Perhaps the most specific industry in which artificial intelligence and machine learning can be applied the most broadly is e-commerce, where applications range from attracting customers to forecasting supply and demand to predicting supply and demand forecasting. Furthermore, it is possible to use artificial intelligence and machine learning solutions to make online and offline transactions more secure. In all likelihood, such solutions will be used on both sides – on the part of both retailers and banks / financial institutions. For example, a solution developed by the SPD Group to secure online transactions and prevent fraudulent attempts works in exactly this way, as shown in the following example.
What Are the Advantages of Artificial Intelligence in the Retail Industry?
Fraud must be avoided at all costs.
In almost all business processes, machine learning and artificial intelligence can be used to improve productivity and efficiency, such as manufacturing, logistics, and human resource management.
Artificial intelligence makes it possible to personalize the user experience most fully. The key to modern sales success is maximum compliance with user expectations and foresight into future requirements. The introduction of artificial intelligence can indeed be a costly investment, but the ability to develop more competent marketing strategies makes it possible to recover investments and earn additional profits. Because of their ability to work with real-time data, analyze patterns, and detect anomalies, artificial intelligence and machine learning can protect your company from fraud, improve your reputation, and save you money.
Use Cases for Machine Learning in Retail – Several Examples That Are Appropriate for Your Company, Too
Here are some examples of common machine learning applications for e-commerce and retail that you may be familiar with.
Artificial Intelligence in Retail Marketing
We have already stated that the introduction of AI and machine learning has the potential to increase sales. The majority of the time, this is made possible by taking a more strategic approach to marketing activities. Here’s how it works in practice.
SEO powered by artificial intelligence
Before this, SEO strategies were a major source of frustration for professionals and business owners. Today, with the aid of specialized software, it is possible to make your SEO promotion more thoughtful while also lowering the overall cost.
Examples include applications that allow you to create a semantic core for a website while taking into consideration the specifics of your business, the primary types of content, and your SEO objectives.
Using the Crayon and Bright Edge apps, you can quickly find the best ideas for your next blog posts and other materials by quickly analyzing trending topics, user preferences, and even the activities of competitors.
The Market Brew enables you to take advantage of the most advanced predictive capabilities of artificial intelligence to quickly determine whether a specific change in your content will be effective for search engine promotion or not.
Personalization of the content
The ability to create personalized content is already commonplace. When users interact with brands, they want to see a personalized approach and customized content at every stage of the interaction. It is also expected that shortly, the websites themselves will become fully personalized, showing the user only the products that, in the opinion of AI, are most likely to suit him, as well as taking into account the purchasing power of each individual and optimizing the price on that basis.
Recommendation Engine
Amazon was able to increase revenue by 35% as a result of the recommendation engine. This is the most basic application of artificial intelligence and machine learning in retail. The title itself conveys the essence of the company’s work. The algorithm analyses user behavior on the site and in the surrounding area and makes assumptions about similar or complementary products that may be of interest to a specific client in the future.
Search Engine Optimization for Voice and Visual Search
It is expected that voice search will account for half of all search queries by 2020. To appear in the Google snippet for certain searches, retailers must slightly improve their approaches to search engine optimization (SEO). When people use voice search, they are most likely to ask natural language questions such as “where can I buy a Gucci dress near me.”
An app that is powered by artificial intelligence When you use Answer the Public, you can conduct research into the questions that people may have while looking for your products. Visual search is also made possible in retail thanks to the use of artificial intelligence and machine learning technologies. Here is an infographic that demonstrates some of the solutions you can use to improve your visual search while also driving other marketing initiatives.
A store that sells goods to the public
In a retail setting, artificial intelligence is being used.
You can improve your physical selling point in the following ways by utilizing artificial intelligence.
Assistance from Robots
Currently, shop assistant robots are available for purchase. Simple Robotics, for example, has developed a robot to assist customers in grocery stores to deal with the challenges of a pandemic. His job is to assist people in retrieving items from higher shelves to reduce the number of contacts and touches. Under normal circumstances, assistant robots can work to improve the customer experience and speed up the shopping process, as well as reduce the number of human consultants who perform routine tasks in the process.
Recognition of Expressions and Moods
A customer entering the store can be identified immediately thanks to the use of face recognition technology, which is installed at the entrance. Using technologies for recognizing emotions and intentions, the machine learning algorithm can make educated guesses about what kind of product you should be offering a specific buyer at any given moment.
The layout of Shop Windows Based on Data
Through the analysis of sales data on the most popular products (as well as data on products that customers are unable to locate quickly on store shelves), you can optimize your shelves and shop windows to save customers time while increasing sales.
Artificial Intelligence in the Retail Industry and Its Business Processes
Artificial intelligence and machine learning can also be used to improve the efficiency of critical business processes.
Predicting issues and developing smarter strategies are important tasks.
The most straightforward example is the ability to predict fluctuations in demand and optimize pricing. Smart algorithms are capable of detecting anomalies that are not visible to the naked eye, preventing fluctuations from occurring, and protecting your company from unforeseen events.
Improve the efficiency of the delivery chain
This feature will be particularly beneficial to grocery retailers. Very frequently, goods arrive in the store half-rotten as a result of delivery delays, which can occur as a result of traffic jams, bad weather, or a strike. Artificial intelligence allows for the prediction of potential delays and the streamlining of the delivery process to reduce food waste and carbon footprint.
Churns can be predicted and reduced.
An analysis of purchasing behavior using AI and machine learning can provide you with inconspicuous clues as to whether or not a particular buyer intends to discontinue purchasing your products. In this situation, you can devise an emergency and personalized response strategy that will allow you to keep the client on board.
Manage Your Employees in a More Effective Way
It is also possible to develop more intelligent strategies for human resource management. For example, by identifying the times and days when the store’s peak traffic occurs, it is possible to increase the number of sellers on the floor and, conversely, to decrease the number of sellers on the floor without negatively impacting the customer experience during the “quiet” periods.
Conclusion
Modern e-commerce trends emphasize the fact that it is no longer possible to exist without the use of artificial intelligence and machine learning. Customers have already grown accustomed to it and expect even more amazing experiences in the future, such as having their desire satisfied even before they are aware that they have it. Modern technologies, of course, are capable of even greater things, provided that they are properly integrated into business processes and that the goals and objectives of artificial intelligence for retail are set correctly as well.
