The traditional data analytics in retail industry is experiencing a radical shift as it prepares to deliver more intuitive demand data of the consumers. The rise of online shopping may have a major impact on the retail stores but the brick-and-mortar sales aren’t going anywhere soon. According to Euromonitor International, it is projected that 83% of goods purchased globally in 2022 will still be bought in-store. But that said, retailers really need to come up with innovative technologies to offer new ways to lure customers to their stores. Fortunately, business intelligence and data analytics in retail industry can offer a wide range of useful applications that helps retailers to generate more sales.
By using business intelligence and data analytics in retail industry, retailers can transform traditional shopping to a whole new level. For a customer, the basic shopping experience hasn’t changed much. They walk into a store, search for the right product and make a purchase. However, this simple process can be vastly improved with the help of data analytics in retail industry. With valuable insights derived from business intelligence, retailers can provide unmatched levels of personalization, automation, and efficiency to the retail sector.
Retails can generate actionable insights from various sources of data such as point-of-sale stations, surveillance cameras, Websites, Apps, etc and helps to make predictions such as the impact of a marketing campaign, the level of demand for a new product or even identifying the new consumer trends.
Here are some of the ways that can accelerate business intelligence & data analytics in retail industry:
A consumer’s behavior inside the store says a lot about them. If retailers can study how consumers make decisions about what they need, want, and desire and how do they buy, they can drive more sales. By employing real-time data analytics and computer vision technologies to their surveillance infrastructure, retailers can capture and study customer behavior inside the stores. This will provide a wide variety of valuable insights, such as identifying store performances and understanding customer needs and engagement levels.
For example, the AI-powered data analytics system can detect customer’s emotions to see whether a consumer was satisfied with the in-store experience and if the consumer got what he/she wanted or whether if they were looking for more options, etc. The data analytics also allows retailers to optimize the current store layout, avoids overcrowding inside the store and streamline operations for higher engagement and revenue.
Use of data analytics in retail can ultimately lead to improving the customer’s shopping experience by significantly reducing the wait time, providing the best prices and buying options and also increases the ease of shopping.
⊕ Emotion detection to better understand the customers
⊕ Can monitor the in-store crowd movement
⊕ Enhanced security surveillance
⊕ Tracking customer affinity
⊕ Efficient facility management
An AI-powered real-time video analytics software such as Emotyx can harness intelligent insights from CCTV videos. Built using proprietary computer vision and AI algorithms, Emotyx video analytics can deliver actionable intelligence which helps to accelerate business growth. It can analyze customers’ emotions and their satisfaction level based on their on-premise activities which are very helpful to facilitate a better customer experience.
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Everyone loves personalized services, in fact, personalization leads to positive customer feedback. This, in turn, will lead to higher customer retention which means more sales. In a study, 65% of consumers said that personalization is the most important factor in their shopping experiences and 54% of consumers expect a personalized offer within a day of interacting with a brand. With Data analytics, retailers can better define and predict customer journeys to provide a unique and curated shopping experience to their customers. Here are some of the ways AI delivers a unique shopping experience.
AI conversational chatbots can handle thousands of queries simultaneously and offers a prompt and personalized attention to the consumer. They can suggest shopping recommendations and can resolve a customer’s problems very easily. Moreover, Chatbots can be part of the loyalty programs. It can send “exclusive” discount codes or limited time offers to the users. And when customers get personalized attention, they will engage deeply with the brand, paving way for more sales.
2. Digital Assistance to provide personalized consumer experiences
Customers in-store often need assistance in locating a product or getting information about a product. Such situations can be addressed with the help of AI-backed touch panel kiosks or even robots. They use technologies such as Natural Language Processing and Natural Language Understanding to answer customer’s questions. The questions can be anything. Such as details of the store’s layout, information regarding product location and other available in-store services. This way stores can reduce their manpower and running costs. Not only will it improve customer service levels but will attract more buyers to the store.
In 2016, Lowe the American retail company specializing in home improvement has launched a digital assistant robot called LoweBot to improve in-store customer service. Customers can ask a question to LoweBot regarding products through speech or via touch panels. LoweBot can help customers find an item they are searching for and provide other product information along with performing real-time inventory tracking.
3. Virtual Trial Rooms for Easy Decision Making
Shopping for apparel or clothes can be very frustrating and time-consuming since it involves trying out different options. However, AI-powered virtual trial rooms equipped with digital mirrors allows customers to try the clothes without having to change again and again. Shoppers can also mix and match various outfits, accessories, shoes, etc to finalize the final look. It is also very helpful to cosmetic companies and brands since they can show a customer how the makeup would appear on real skin without forcing customers to apply the product.
Mango and Vodafone together launched a digital dressing room that is powered by AI. The virtual dressing room allows the customers to scan the clothing inside the dressing room, and to contact the store staff directly to request other colors or sizes. The system can suggest other clothing to match chosen by the customer. Meanwhile, MAC Cosmetics has launched ‘ModiFace’ an AR technology that allows customers to virtually try different makeup looks in real-time.
Good marketing is when it doesn’t feel like it. And marketing is said to be a success when customers feel as though they’ve been helped. With the use of Business intelligence and data analytics technologies such as predictive analytics, advertisements are more customized to each user than ever before. With valuable insights from business intelligence, retailers can create marketing campaigns based on their interests, region, preferences, and purchasing habits. This technique leads to higher conversion rates and improves customer loyalty and customer retention.
⊕ Improved personalization
⊕ Ability to be proactive in every sales opportunity
⊕ Betting understanding of leads behavior
⊕ Ability to scale and curate Ad campaign
Smart Inventory Management System
Implementing data analytics in retail inventory management can vastly improve and streamline the business. Smart Inventory management systems use machine learning as well as computer vision to help automate various inventory management processes. It helps retailers to keep up with supply and demand by maximizing stock levels and preventing stock depletion. It enables retailers to better anticipate, predict and manage products while providing an increasing ROI. Data analytics helps to manage inventory quickly and efficiently.
⊕ Automated inventory monitoring
⊕ Enhancing demand forecasting accuracy
⊕ Reducing forecasting errors
⊕ Enhancing supply chain management productivity
The big challenge retailers face is shrinkage. Retail shrinkage is the loss of inventory due to employee theft, shoplifting, administrative error and damage in transit or store. AI can be used to address retail shrinkage. By applying AI-powered video analytics to existing CCTV infrastructure, the system can monitor people’s behavioral aspects such as how people walk, their hand movements and facial expressions, and even their clothing choices. In other words, it can be trained to detect suspicious activity in the store. If the system spots behavior it deems suspicious such as being restless or sneaking to putting items into bags or pockets, it can alert staff members so they can swoop in to prevent the theft. The system can also identify checkout scanning errors and failures. By applying advanced video and data analytics to existing video and data streams, retailers can curb loss by identifying the products that go without scanning at checkout.
A rapidly evolving competitive environment and the ever-changing behavior of customers are driving the industry to a new phase of technological innovation, with business intelligence and data analytics at its core. Retailers must keep up with customer expectations to remain in business and implementing data analytics can help a long way. It increases operational agility, improves the quality and speed of decision making, and enhance the customer experience. Early adopters are already getting competitive advantages.
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In the battle for market share and to stay competitive, harnessing the power of business intelligence is simply not an option. The companies that fail to adapt and leverage its benefits will fall into oblivion.