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The Benefits of AI Analytics
for Retail Businesses

The Benefits of AI Analytics for Retail Businesses

Data analytics is indispensable for any organization that wants to grow a competitive and successful business. That is particularly true for retail businesses that face increased competition and pressure in this day and age. With in-store analytics of consumer behavior, retailers gain the opportunity to use actionable insights to improve store performance and boost the productivity of their business. However, to reap the optimum value from gathered data, it is instrumental to harness the power of AI. It can be effectively utilized to improve store operations, streamline marketing and loss prevention strategies and enhance the customer satisfaction index. Let’s explore what opportunities AI analytics gives stores to maximize their performance and drive sales.

Over the years data analytics has been an important tool for retailers to optimize business processes, build marketing strategies and satisfy customers’ demands. These days, as the retail business environment has become highly competitive, the need for advanced retail analytics software is rapidly growing. According to a report by Research and Markets, the global retail analytics market is expected to increase with a 19.4% CAGR and will be valued at $10.4 billion by the end of 2023.

In the battle for customers’ loyalty, brick-and-mortar retailers increasingly adopt next-gen technologies to improve their customers’ experience. Compared with legacy applications and data sources, new technologies such as AI win the competition. AI-powered solutions for retailers can perform the same tasks as human analytics do but much faster and effectively. Due to the automation and the ability to process large volumes of data, intelligent software makes retail analyses more efficient and robust. Besides, AI learns from data patterns, which allows providing advanced analytics at a higher level of accuracy.

In essence, in-store analytics implies the process of collecting and analyzing retail data related to sales, inventory, customers, etc. to get meaningful insights into the store performance to help retail managers to optimize it, discover current trends and customer needs and make better marketing and operational decisions.

Retailers benefit from AI analytics in different ways. Discover a few of them below.

Store performance optimization

The first priority for any retailer is to satisfy customers’ needs which is hard to do as shoppers are getting more and more demanding these days. They expect to get the product they like the moment they need it and do not accept any out-of-stock scenarios or product substitutions. Thus, the key to optimizing store performance lies in better understanding customer needs so as to create the most preferred shopping environment for them and improve their shopping experience.

This is where AI analytics comes in handy. Analyzing data collected on almost everything – from foot traffic and customer count to time dwell and basket size – AI equips store managers with the insights required to make better, more informed decisions about the inventory. For example, it helps to handle their supply chains properly, keep stocks to the optimal level and avoid out-of-stock scenarios. With smart insights, stores can better prepare for seasonal peaks and low demand periods and determine which products to order and in what quantity. Retailers also use AI analytics to improve store design to guide footfall to desired areas and products or increase the street capture rate from people who pass the store. At the same time, AI automates and streamlines operational processes, which results in stronger performance outcomes and has a positive impact on the bottom line.

Retail security

Increased store-team performance

The conversion rate is intrinsically linked with staff efficiency. Customers expect shop assistants to be available at the right time and provide good and fast service. It is observed that store associates’ performance is likely to go down when they have to serve more than seven customers at a time. That negatively affects customers satisfaction and the conversion rate drops significantly.

To understand whether employees handle their responsibilities properly it’s critical to assess in-store foot traffic, determine where customers linger, what time the foot traffic is at the highest, and optimize store-team performance accordingly.

AI analytics steps in to assist retailers with this. By analyzing customers’ behavior in the store AI provides heat maps for foot traffic which help with staffing decisions. Those are used to adjust store layouts and staff shifts according to the number of shoppers at different times of the day and increase the number of employees at peak times to make sure that the right number is present to handle the level of traffic.

Stores can also implement AI-powered chatbots to help human assistants with customer service, for example, provide real agents with insights about customers to resolve issues faster or assist customers with in-store shopping. Integrated with the store’s inventory, which includes in-store location data for each product, the chatbot can say whether the product is in stock and which aisle to check. That gives customers a self-service option and improves service experiences.

Streamlined Marketing

In-store analytics software is just the right tool to measure and streamline marketing attribution. With smart software, it is easier to understand trends, measure the number of visits, determine new and repeat visitors and assess the effectiveness of advertisement methods. Based on these insights retailers improve their marketing programmes and advertising campaigns, make decisions on ad placements or locations to produce better advertising effects on hit rate and average purchases. Studying historical patterns of consumer behavior and needs, retailers can adjust marketing promotions all year round and make them more relevant and personalized to their customers. Real-time analytics gives an extra advantage to retailers as it allows them to react to poor performance live and make appropriate changes in their strategies.

Enhanced customer experience

In a retail business where customer experience rules, retailers are acknowledging the call for more effective personalization. In this regard AI analytics is the right solution for stores that gear towards meeting customer needs and enhancing their shopping experience.

AI analytics can generate insights based on demographic traits such as location, gender, age, as well as customers’ interests, habits and values. With all these consumer-related data, it is easier for retailers to identify their buyer personas and provide a curated merchandising experience, for example, creating relevant offers or personalized product recommendations based on the insights from a customer’s previous visits.

They can also make sure that customers’ desired products are always available as if a retailer abruptly discontinues a beloved product that might end up in loss of that product’s customers.

Final Takeaway

Retailer businesses are now rethinking how they can meet the growing demands of consumers and deliver improved customer experience. With AI-driven software, they gain the chance to stay one step ahead of the competition. Insights gained from AI analytics enable them to maximize store performance, identify inefficiencies, optimize stock and streamline marketing activity. Due to real-time data analytics, retailers make faster and better decisions to determine how to better manage in-store capacity, personalize customer experience to gain customers’ loyalty and boost their bottom line.

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