The potential of artificial intelligence and machine learning for retailers

Artificial Intelligence

Artificial Intelligence and Machine Learning can be a boon to retailers

From science fiction movies to the future of retail, technology is making its way into all areas of our lives and also in the world of online consumption thanks to its power to optimize all processes with the application of artificial intelligence in retail.

Online sales companies are increasingly interested in innovating by creating new strategies and technologies that are capable of optimizing Internet sales and improving the shopping experience for consumers.

The biggest challenge they face is knowing the users, pleasing them, and meeting their demands according to the logistics processes that are offered.

This is where artificial intelligence appears in retail. Each purchase involves a large amount of data that is wonderfully usable in the basic principle of AI, Big Data, and Machine Learning. The more this data is filled in, the more information AI will know about users, knowing what they think and what they do on the internet.

For this reason, there are already several companies that have arranged their resources to include AI in their systems to streamline data management, and in reality, the better the data is used, the better the service in retail will be.

 

The benefits of artificial intelligence in retail

The management of large volumes of data, and the use of Artificial Intelligence processes are changing the world of online sales. Among many of the benefits that artificial intelligence represents, the following stand out:

 

Demand predictions for supplied stocks

Demand predictions are one of the best aids that artificial intelligence represents in retail on the sales side. This enormous ability to analyze the volumes of data provided by consumers allows companies to have an inventory supplied with sufficient quantities of goods and services, which users are more willing to buy to prevent the desired product from disappearing very quickly.

 

Cost impact reduction on products

By making the necessary purchases in a single moment, and supplying the stock on a planned basis based on consumer demand, companies can reduce their operating costs such as transportation, which are reflected in better costs to the consumer.

 

Offer suggestions

On the other hand, Machine Learning can make segmented purchase suggestions to buyers, according to users with similar profiles and the trends identified in many of them. These suggested offers based on possible tastes lower the cost per click, and as a result, the cost of advertising, which could also be reduced in the final cost of the product for the consumer. But these positive results are something that can be seen more often in e-commerce.

 

Three examples that illustrate the potential of AI and machine learning for retailers

The retail sector is experiencing significant growth and while it is now becoming almost impossible to separate “growth” and “data analysis”, retailers readily admit the opportunity represented by big data but also admit the need to develop this “Data culture” to fully exploit its potential.

Whether for the analysis of consumer behavior, competitive intelligence, or the personalization and targeting of communications, big data has many uses and benefits. However, it requires the adoption of new tools.

Transforming data into real usable information and thus developing customer knowledge, offers, and ultimately income is more than ever a priority for companies. AI and machine learning are the most suitable technologies to achieve this. It is no longer a question of simply collecting the data but of understanding and analyzing it to use it in an efficient and relevant way. Advanced analytics and data science are two approaches that are now known to retailers. Here are three real-life cases to understand how these technologies can help retailers realize the full potential of data.

 

Increase loyalty with new services

Data makes it possible to optimize customer knowledge and access the holy grail of sales and marketing services: loyalty. By having the tools to intelligently process data, retailers will be able to categorize transactions, analyze how consumers feel about a product or service, and create accurate models to increase sales.

Supermarkets have understood this and are deploying data science tools allowing them to develop their own application with new differentiating services such as the location of a product in-store, the possibility of checking a predefined shopping list, or alerts on ongoing promotions on the customer’s favorite products. The goal is clear: to simplify the customer experience to build loyalty and stand out from the competition.

 

Push personalization up to the exclusive offer

Personalization has been widely discussed in recent years to become the standard approach that many retailers have taken. The average consumer is used to receiving offers that correspond to them and their expectations have evolved as a result. Today, the expectation is high on exclusive offers. To answer this, retailers will have to go beyond ultra-personalization, for example using artificial intelligence algorithms that feed on mass data to publish relevant recommendations in near real-time.

This trend is already very present among e-merchants whose preferred communication channel remains email. Brands can thus use these algorithms to create unique and dynamic emailing campaigns whose content adapts in real-time to its recipient. From a single shipment, each consumer can receive a unique offer, designed from the analysis of their data.

 

Boost the in-store experience thanks to online technologies

Despite the rise of online technologies, many consumers continue to prefer human contact. The pure-players of the web have understood this well with the recent openings of points of sale by Amazon. However, the dynamism and attractiveness of these physical stores remain essential.

The opportunities created by intelligent data processing and the power of data science are endless. The automation of processes thanks to machine learning or the creation of artificial intelligence algorithms are two analytical tools that will allow retailers who so wish to create a differentiating customer experience.

To carry out these projects in the field, “Marks & Spencer” has created its own “data academy” to allow its employees to discover analytics and to confront these new uses. Team training is indeed essential in the transformation process towards optimal use of data.

 

Conclusion

Businesses understand the importance of integrating technologies into their business processes. That is why many have included AI in their systems to streamline data management. Mining and transforming data into real usable information and thus developing customer knowledge is a priority for companies.

A top AI development agency such as Hyperlink InfoSystem can help you with a top solution to integrate into your retail business.