Thu, 04 Mar 2021

Data Science in Retail

27 Jan 2021, 04:33 GMT+10

Whether retail happens in a commercial or online space, one thing is the same. Companies always put the customer at the center of their activities. Retailers are more and more often choosing modern solutions based on data science in retail. The goal is to shorten the communication path between the customer and the brand. Data science in retail helps in optimizing prices, product recommendations, and inventory. If you want to know more about the use of data science in retail and how it affects sellers and buyers-read on.

Along with banking, financial services, and insurance, retail is one of the industries that most often uses various data science solutions. A significant number of industry analysts suggest that in 2021 more than three-quarters of companies plan to implement solutions based on artificial intelligence in the retail industry. No wonder; data science technologies help retailers improve their marketing strategy, optimize processes, and increase financial results. Data science in retail plays a vital role in developing and automating many sales processes. Let's take a look at some of them:

Examples of using Data Science in Retail

Today, retailers are increasingly seeing the potential of data science and are looking for ways to get more information about their customers. This data allows the development of numerous areas of activity in the retail industry.


Knowing what additional products customers buy with their elementary purchases helps retailers improve merchandising and increase sales. Customers usually buy products in groups. Thanks to AI, retailers can not only understand but also predict customer behavior. That, in turn, enables them to provide customers with appropriately tailored purchase recommendations. The way the referral engine works is simple. Based on the purchasing history, products added to the cart, or even social media likes, the algorithm automatically generates recommendations for other products. Recommendations are a powerful tool. Analysts indicate that 35% of all Amazon sales were attained through the use of the referral engine!


Nowadays, thanks to modern technologies, consumers in the blink of an eye get directions to their destination or suggested films to watch based on their previous choices. The same AI-based technologies can help improve your customer service. Companies can provide better customer service by implementing chatbots or sending personalized emails with information about the latest products and promotions. Such activities, frequently combined with tailored offers, build positive shopping experiences for customers.


If you are a seller and you don't have social media profiles, you lose a lot. By resigning from social media presence, you lose the ability to use big data to grow sales and improve customer experiences. Also, social media is an extremely helpful tool when it comes to predicting future trends and spotting the new bestsellers. The social media data allows you to find out which products are attractive to your potential customers. Thanks to this approach, you will find out which of them you should promote.


Probably every retailer strives to optimize their prices. The best price is always a chance for high profit. Choosing the best price depends on such factors as competition, market position, production costs, distribution costs, and many others. Data science lets you take advantage of ML (machine learning) to obtain all the necessary information to select the best price for a given product and enhance your entire pricing strategy.


Information on customer outflow, frequently known as customer churn, is one of the most desirable data in any type of business. Companies are very interested is curbing customer churn, chiefly because the price of acquiring a new client is usually much higher than keeping the current one. Machine learning comes to the rescue with the most effective way to predict your customer churn rate. The developed algorithms can learn patterns from individual data and predict individual dropout rates. This way, you can measure how many customers might depart your store in the coming months! Read more about that solution here:

Data science is the retail industry's answer to marketing 4.0

All the aforementioned examples of the innovative use of data science in retail allow sellers to offer the highest quality of service and increase retail sales. For large companies such as Amazon and IKEA, data science has become an indispensable part of their daily business operations. Increasingly, however, both small and medium-sized entrepreneurs use the opportunities offered by data science and AI to increase brand awareness, better manage risk, or build loyalty and commitment among customers.


However, possessing data is not enough to achieve the intended results. You still need to know how to use it. Technology evolves and has more to offer in the retail world. To take advantage of all the possibilities, it is worth finding the right data science partner. In other words, look for a partner who has knowledge and experience in implementing AI and ML in the retail industry. If you need help validating an idea, verifying a concept, or implementing artificial intelligence in your company, talk to experts and find out how to grow your business through data science and artificial intelligence.

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