5 Unexplored Benefits of Machine Learning in Retail

When we start examining how technology is changing life, education, and the business landscape as a whole, we might not be able to exhaust everything in a day. Technology is now a mode of life and there is no denying that. Among the top-notch technologies conquering every aspect of life, we have Machine Learning (ML) and Artificial Intelligence (AI).

Machine learning alone is a subset of artificial intelligence and deals with the use of data and algorithms to gain insights and draw predictions from the raw data input. Precisely, ML is a technology that allows systems to learn on their own i.e from experiences without being explicitly programmed.

The growth of data science has led many businesses and companies to leverage technologies like ML and AI. With such technologies in place, business processes are streamlined, and business owners are able to attain and digest big data and make more informed decisions. When computers are fed with data; whether from customers or business owners, they are able to learn and update their knowledge base continually.

Machine learning is revolutionizing eCommerce and retail as a whole by allowing retailers to stay ahead of the competition, forecast market changes, and provide better customer service. Applying machine learning to business workflow helps to achieve optimal efficiency, eliminates human error, and results in the better utilization of business data. When it comes to marketing, ML helps in the process of analyzing large data to gain insights into customer behavior, spending, and customer lifetime value. It also leads to better-targeted marketing campaigns.

The global market for machine learning was valued at USD 15.44 billion in 2021. More insights show that the ML market is expected to grow to USD 209.91 billion in 2029. Other findings indicate a 300% increase in investments in machine learning and AI technologies. 91.5% of the world’s companies besides Amazon, Alibaba, eBay, Netflix, and Walmart are already investing in machine learning, automation, and artificial intelligence.

Regardless of the industry, or type of business (online or brick-and-mortar), any retailer can leverage ML technology to improve marketing strategies, increase sales, or double ROI. However, it’s crucial to first understand how machine learning works to bring about optimal results. Now let’s explore more about the benefits of Machine Learning in retail.

5 Unexplained Benefits of Machine Learning in the Retail Sector

1. Personalized Product Recommendations

This is the age of personalization and the trend isn’t about to fade away. A report by McKinsey & Company shows that customers not only want personalization but demand it. The report also shows that companies that manage to connect with their customers generate faster revenue. To substantiate, 71% of customers expect personalization from their brands. Todd Yellin, Netflix’s vice president of product innovation, describes personalization as the process of creating the right connection between the viewer and the content. In addition, Netflix managed to save $1 billion due to its machine learning algorithm that personalizes content recommendations for its users.

Personalized product recommendation results in better customer experiences and consumers are left more satisfied than without it. Many brands and businesses are aware of how valuable every customer is. To enhance experiences, generate leads, and boost sales, companies leverage ML to understand customers’ behavior depending on purchase history or profile. The technology studies customers’ or shoppers’ data input or queries and then begins cultivating experiences based on the data input.

With time, the website automatically brings up related searches and similar products based on historical data or what other customers searched about. Retail companies use recommendation systems to help customers access the latest content and personalized offers they would benefit from. These efforts increase sales and improve buyer journeys.

2. Optimized Supply Chain Management

Market dynamics are forces that every business must deal with. However, with machine learning technology, businesses can have their supply chains optimized to eliminate or reduce disruptions and meet customer demands on time. Machine learning provides an avenue where large volumes of real-time data are centralized, accessed, and used to make decisions.

Retailers get to know how to better manage their inventory or look for other suppliers to achieve a balance between the stock in hand and the customer demand. Businesses can also stock up on goods or resources once they predict a shortage in the near future. Precisely, ML allows automated quality inspections and reduction in forecast errors due to its efficiency.

For example, an apparel store can leverage machine learning to study customer behavior, analyze its current stock, and plan for procurement. The retailer is able to learn about future customer behaviors and then stock more where necessary. ML impacts every point of supply chain management from procurement, and logistics, to stock availability.    

3. Forecasting Future Trends 

Modern markets are fast-paced and forecasting is key to predicting future market changes and why they will occur. With the advent of COVID-19, a drastic change in customer behavior, and supply chain disruptions, it has become more significant for retailers to rely on data to understand future market trends.

Market forecasting is the process of analyzing the current trends to predict future trends. Machine learning helps retailers to predict market patterns by assessing current customer behavior, purchasing power, and preferences among other forces. Machine learning has become crucial in forecasting future trends by providing authentic data to retailers.

Computer algorithms recognize people’s genders, ages, preferences, and purchasing power. It helps retailers to do away with guesswork, most especially when it comes to planning and decision making. They are able to make realistic predictions that have a far-reaching impact on business ROI and growth. Retailers are also able to create optimized and targeted marketing campaigns to increase customer lifetime value. All in all, trend forecasting helps retailers stock up on products that will be in demand or make better marketing decisions.

4. Greater Efficiency in Finance & Payments

The recent developments are paving the way to harness machine learning in financial management and payments. With the help of ML and AI, retailers can track customers’ purchase trends through various channels like CRM databases, user-generated content, and purchase history. As people prefer online payments, and order discounts, machine learning helps in price optimization and fraud detection.

Machine learning involves data analytics and it can help in studying customer and purchase behaviors. In case there are sudden changes, there is better predictability as algorithms can revise the data. Businesses can then set better Key Performance Indicators (KPIs) to impact the business tasks and their bottom line.

Utilizing machine learning in payments and financial management will require a retailer to first find an eligible team with professional and technical experience in several areas like data, computer science, and advanced analytics.

These should work hand in hand with the sales, marketing, and management teams. Machine learning currently caters to credit card transaction monitoring and this helps in the real-time authorization of transactions and elimination of errors in payments.

Besides, when recurring payments or invoice operations get automated, it will add to positive employee experience leading to greater workplace motivation. Employees can then focus on other imperative tasks without having to worry about monotonous and repetitive tasks.

5. Seamless Customer Experiences  

It is every business’s target to get more leads, and sales, and offer the best-in-class customer experiences. Before, retailers relied on human efforts to offer the best experiences to customers. However, with the advent of top-notch technologies like AI, ML, and data science, retailers can rely on facts to craft better experiences depending on customer habits and interests.

eCommerce and retail are all about experiences and with ML, retailers can optimize buyer journeys through personalized shopping experiences. Machine learning helps businesses gain insights into raw data such as customer purchasing habits and trends and are able to understand demographics, improve browsing experiences or invest in targeted marketing campaigns. Algorithms are more accurate in identifying what customers are more likely to buy more in the future and retailers are able to direct their marketing efforts to the right consumers and markets.

To encapsulate, Machine learning (ML) and Artificial Intelligence (AI), are fascinating technologies stirring up every aspect of life. From recommendation engines, and self-driving cars to seamless voice searches, ML and AI are revolutionary in every way. In retail, ML is undeniably an influential factor in understanding customer data, crafting marketing campaigns, and providing seamless CX. As a retailer, it’s essential to implement AI and ML technologies to optimize marketing efforts, business growth, and ROI.    

Author Bio:

“Doing what you love is the cornerstone of having abundance in your life.” Wayne Dyer’s thoughts are well suited to Kiara Miller. She has been working as a content marketing professional at ‘The Speakingnerd’. Her passion for writing is also visible in the innovative joys of material she provides to her readers.