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Future of Retail Analytics (Top 10 Trends) Below are significant retail analytic trends that businesses are using to achieve a competitive advantage in the market. 1. Create more hyper-personalized experiences for a one-to-one market The ability to track consumer interactions at such a fine level allows management to obtain a far deeper insight into key shopper’s wants and expectations. This means that shops may now provide the unifying experiences that customers expect while communicating distinct offers to highly refined segments. As a result, providing hyper-personalized retail experiences to your customers can increase total sales by increasing loyalty and share-of-wallet. If you would like to apply the same to your business, your firm should think of having a single data and analytics platform in order to develop and expand this level of personalization. 2. Spending and demand can be predicted Retail analytics trends are leveraging advanced analytics, which use computers and machine learning to predict trends detected in customer data. These complex computational models inform businesses how much of a certain product or service customers will wish to purchase during a specified time period. Demand forecasting is being used by business owners to bring their most profitable consumers back into the store through timely notifications and good offers on related products. As a result, businesses can ensure that shipments are timed to get the products their customers desire on the shelves while also optimizing their supply chain. Retail leaders are applying predictive data analytics to determine each customer’s lifetime value in order to increase retention. 3. Develop automated, dynamic pricing models To remain competitive, retailers frequently need to maintain a percentage of their prices very low. These low-cost items, known as doorbusters, and key value items (KVIs), are frequently the top sellers and traffic generators that establish a retailer’s price image. As a result, while KVIs can account for up to 80% of revenue, they only account for half of a retail company’s profit. To compensate for the low margin on KVIs, merchants raise the cost of their higher-margin items and strategically put them alongside doorbusters and KVIs in creative ways to encourage buyers to add higher-margin products to their carts. Retailers can stay in business and grow by optimizing product prices to increase profit margins. With this in mind, dynamic pricing algorithms, in particular, have proven to be game changers for merchants. Dynamic pricing models will offer price suggestions automatically, allowing management to make better informed and timely decisions that benefit the company’s bottom line. To be genuinely effective, we strongly recommend collaborating with a data analytics consulting firm to construct a custom solution tailored to the retail company’s business objectives, operational processes, and client base. 4. Build new experience within the store thanks to the retail analytics trends Those who use digital technologies in their stores beat their competitors. Indeed, obtaining and analyzing well-chosen data provides retailers with a competitive advantage. The combination of data from physical store performance and online buyer behaviors can enable merchants to provide innovative services in-store. For example, Uniqlo, a Japanese casual wear designer, manufacturer, and retailer, has launched a click-and-collect service in a number of cities like London, Singapore, making it more convenient for shoppers to collect online orders at a Uniqlo store of choice with no shipping fee and no min. spend required. Another example is that numerous athletic brands, such as Nike or Adidas, often produce limited-edition collections in a specific store to entice customers to visit. Customers are invited through a database (frequent customers, raffles via social networks, etc.): being invited and visiting the store is perceived as a privilege. Data methods enable retailers to reconsider their physical shop environments in order to provide more tailored experiences for their customers. To facilitate effective operational action, all data is homogenized and cross-referenced. Employee performance and comfort are also improved. Shop owners now have access to accurate data and can be more confident in meeting their sales targets. Sales assistants can effectively respond to consumer needs. Your customers will return to your stores if you ensure their contentment and improve their shopping experience. You are providing them with an experience that only pure player stores can provide. 5. Selling online is non-negotiable Online shopping is important for customers and crucial for retailers. Today, 37 percent of monthly retail purchases are made online, and many businesses are addressing those demands. Independent merchants can interact with customers locally while simultaneously expanding their reach by selling online and retaining a local presence. Going online can boost the prospects of success as many retailers change their business strategies to pursue new revenue streams. In fact, among shops who sell online, internet sales currently account for 51% of total income. Moving to the first new channel highlights the need to employ digital tools to assist retailers in continuing to innovate. Despite the widespread popularity of eCommerce and, as a result, the need of establishing an omnichannel strategy, 32% of retailers believe they are unable to sell things through newer online or social channels because they are unaware of their alternatives. Furthermore, 29 percent feel it is difficult to provide consistent purchasing experiences across online and offline channels. Even while retailers are digitizing their processes, it is not an all-or-nothing situation, emphasizing the significance of education about the omnichannel selling options available. Shopping patterns are changing, and an integrated solution that connects different channels while reducing front- and back-of-house operations can help stores succeed. 7. Automated technology is helping retailers get a handle on the labor shortage Almost one-third of retailers are concerned about their ability to attract and retain employees in 2022. To tackle the additional complexity brought on by the manpower shortage, 72 percent of retailers are utilizing or plan to use automation to reduce their team’s time spent on hands-on work. The top three areas where retailers claim automated technology will help replace workforce deficits are streamlining efficiencies for operations like tracking orders, maintaining customer loyalty programs, and connecting with customers. To satisfy the changing needs of the employment landscape, retailers should consider investing in automated tools or improving what they presently use. 8. Voice search With digital assistants like Siri, Alexa, and Google Assistant available at the push of a button, it’s no surprise that more and more people are utilizing voice search technologies to simplify everyday activities. Consumers are increasingly depending on information offered by voice search to make purchases, whether it is to locate directions to a store, learn its working hours, or browse product reviews on the way to the merchant. Retailers who want to take advantage of this AI-based technology must optimize their online presence in the same way that they do SEO for their websites, using natural speech patterns and user intent in their keywords. 9. Extensive reality The rise of extended reality, which includes both augmented reality (AR) and virtual reality, has been one of the most intriguing advancements in retail technology in recent years (VR). Retailers can use this technology in a variety of ways. They can assist potential buyers with experienced products in a way that mirrors real life by producing AR and VR experiences for their clients, such as 360 immersive films, which is very handy when purchasing big-ticket items like furniture or gadgets. AR and VR technology not only allows consumers to see what a specific item might look like in their house, but it also assists businesses by allowing them to visualize in-store layout and stocking as well as evaluate and analyze consumer behavior scenarios. Learn the importance of Video Analytics For Retail 10. Machine learning Machine learning, a subset of Artificial Intelligence (AI), is the process through which computer-run systems automatically learn and improve based on their experience without the need for additional programming. This technology is increasingly becoming the go-to solution for companies and merchants trying to stand out from the crowd. One of the most prominent applications of machine learning in retail is in recommendation engines and conversation bots, which “learn” from their operations and improve over time. Another prominent machine learning-based application is visual search, which allows customers to search an item’s image for characteristics such as brand name and pricing. This can be considered as the most advanced technology to apply to the future of retail analytics. Now, Embark on a retail analytics journey with Synodus today! 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