Henry Bell
Henry Bell 30 September 2021

Machine Learning in Retail: Should You Implement it?

Many retail businesses are now starting to use AI and machine learning to keep up with the constant changes in consumer behaviors. Using the same strategy in your business might allow you to get good results as well.

Customer data is an essential component of a successful business. Properly analyzing and utilizing said data is the biggest factor in the growth of a business. With the ever-growing sources of customer data nowadays, machine learning has become critical to the development of new strategies in the Retail industry.

According to a report from IBM, more than 70% of retail and consumer product businesses are now depending on machine learning services to analyze client purchasing behaviors in order to optimize the supply chain and personalize offers for their customers.

While predictive analytics relies on people to identify statistical trends in data, machine learning is a type of artificial intelligence (AI) that uses computer algorithms to identify data trends. Computers can then generate predictions on their own based on such trends, effectively "learning" without being trained for a specific purpose.

Why Integrate Machine Learning into a Retail Business?

Machine learning can assist businesses in optimizing prices, collecting consumer data, and streamlining logistical operations. The capability of machine learning to simplify the retail business saves costs and strengthens consumer connections.

But aside from that, here are more benefits in integrating machine learning into a retail business:

Churn Rate Forecasting

Predicting churn rate is critical for businesses. When a firm loses a client, it loses both the prospective earnings and the money invested in attracting consumers.

If you continue to lose clients due to churn, you will never reach a break-even threshold. The expense of acquiring new customers will be really costly.

Fortunately, machine learning can assist you in tracking events that are likely to result in client loss. The data from the AI will help you come up with appropriate actions to retain consumers in a proactive manner, as opposed to the standard reactive approach.

Market Analysis

Businesses must forecast demand for their services in order to provide consumers with a fully tailored experience.

Machine Learning in retail can perform such predictions and assist firms in keeping track of their inventory in order to manage stock levels. Furthermore, they can determine demand changes and adjust their pricing appropriately.

Automating Basic Processes

Machine learning can evaluate the internal data of a retail business significantly faster and more efficiently than any person could. For example, you can allow the AI to check and analyze your human resource data.

The data produced by the AI can help you accomplish the following:

●     Make your employees more adaptable

●     Free workers from mundane chores

●     Effectively plan the employee work schedule

Not only that, you can even apply it to cases where you need to physically verify the status of a product. Costco is using the technology to check the freshness of their produce aisles, of all things. They managed to significantly reduce the amount of food wasted and increased the freshness and sustainability of their products on display.

Fraud Detection

Businesses may develop a self-learning system with the aid of machine learning. Furthermore, AI can better improve the system's efficiency in detecting fraud.

Machine learning systems will help in the prevention of fraudulent actions and track the usage of coupons and discounts by recording user behavior of a given IP address.

Protected and Quick Routing

Retailers may employ machine learning algorithms to discover faster and better routes and deliver items to customers much more promptly.

Businesses may utilize the same concept to use various algorithms that will determine the intentions and desires of the user to give them personalized experiences.

More Genuine Personalized Offers

Personalization is currently on the rise because today's customers aren't willing to be part of a subscribers list that gets flooded with generic email messages.

Machine learning may assist retailers in adapting to this trend by monitoring user behavior and incorporating critical information about prior transactions.

Machine learning-powered analytics can sift through users' Google search history, comments, and likes on social networking sites to make the best product or service recommendations.

An example of this is H&M’s attempt to restore sales in their retail stores by customizing the offers and products shown to customers, according to this WSJ article. While the company refused to disclose how much, they reported that their earnings and sales grew in one of their Stockholm stores.

Make Use of Predictive Analytics

Predictive analytics has shown to be a valuable tool for retail business owners.

Predictive analysis may help retailers identify key industrial events, upcoming patterns, and how customers would react to such happenings.

Businesses may use Machine Learning and Artificial Intelligence to analyze a vast amount of historical, current, and alleged data to make predictive analytics successful.

A key example of this is Amazon’s implementation in their staff-less Amazon Go retail stores. The Company installed cameras in their stores that track users to determine what items are in demand, what is returned, and multiple other characteristics. This helps not only determine the best options for customers but also alter the pricing policy.

Price Optimization

Large data sets analyzed via machine learning systems allow store owners to foresee how the industry will evolve. By doing a thorough examination of consumer data, retail businesses can set the price that most customers will be willing to pay for a certain product.

Retailers can then modify the pricing based on these results in order to maximize market advantage and profit. Apotek Hjärtat, the Swedish chain of private pharmacies, is using machine learning to track the offers of their competitors while adapting their own pricing in response to the customer’s shopping behavior.

Things to Consider Before using Machine Learning

Machine learning and AI applications are not always the best solutions to the problems of most retail businesses.

Aside from the complexity of these technologies, they are also expensive to integrate into business operations. That is why it's best to address these issues before using machine learning or artificial intelligence solutions.

Can Machine Learning Solve Your Problems?

Keep in mind that AI and machine learning are tools. In certain situations, they are the best tool for the job. But unfortunately, they lack the ability to change a firm on their own.

So, before you decide on using machine learning, identify your problems first and see if ML and AI could be the right solutions.

Is Machine Learning Integration Necessary?

Before deciding whether to pursue AI or ML solutions, it's critical to evaluate whether the tools you presently have are enough. While new technology may be the most appealing solution to a problem, it is not always the most practical.

Only a handful of issues lend themselves well to AI and ML solutions. Aside from that, the most recent technology is rarely the most time- or cost-effective.

Do You Have the Resources for Machine Learning Integration?

Let's assume you've identified an issue that ML or AI can address and concluded that these tools are the best approach to tackle it. The next step is to assess whether you have the infrastructure to deploy AI or ML. In other words, do you have AI / ML software developers on staff that can create the solution you want or adapt an existing solution to meet your needs?

Because of the great demand for these professionals, they are difficult to find right now. They are also highly costly as a result of the high demand.

Integrating machine learning into your business without the necessary infrastructure or funds could lead to numerous problems like financial instability.

Final Words

Many retail businesses are now starting to use AI and machine learning to keep up with the constant changes in consumer behaviors. Using the same strategy in your business might allow you to get good results as well.

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