For years, the retail business has been undergoing a digital change. It has improved speed, efficiency, and accuracy across the board. The primary asset to run the business efficiently is analytics, and digital will provide the data, using which all retail businesses can draw innovative strategies.Without artificial intelligence, none of these insights would be feasible. AI in retail has given firms access to high-level data and information, which they can use to improve retail operations and create new business prospects. In fact, over three years, AI in retail is predicted to have generated $40 billion in increased revenue. According to a KPMG report, 90 percent of retail industry leaders believe their personnel are ready for AI adoption and have the necessary capabilities. Furthermore, 53% of retail executives indicated the COVID-19 pandemic had accelerated their company's implementation. Simultaneously, 49% say AI adoption in their industry is growing faster than it should. Let us know in brief how artificial intelligence transformed the retail sector.<h3 id="helps-to-make-better-business-decisions">Helps to make better business decisions:</h3>The data collected, labeled, and organized may now be analyzed to find trends and patterns to help retailers make better decisions. AI provides performance insights of their target audience to retailers and helps create personalized experiences for every customer. The simple thing that can be done with the data available to find trends is exploratory analytics. While this is straightforward, it cannot be used to automate decision-making processes.Retailers can use AI to generate data models and, as a result, build prescriptive or predictive decision engines. This can aid demand forecasting and enable them to make more data-driven decisions. In addition, these predictive models can learn to make better decisions over time by incorporating more and more data, allowing them to make better conclusions.<h3 id="data-structuring">Data structuring:</h3>Data structuring is a very hectic process. The bulk data received from the manufacturer should be analyzed, structured, and then transformed into valuable data, which requires enormous effort and a time-taking approach. For example, Brand A puts up a crop top on their platform with a festive sale label, and Brand B puts up another crop top for the Diwali sale. While searching for offers, only Brand A?s will appear, and Brand B will not get so much traction and visibility.AI helps with structuring raw data into valuable insights. As a result, Algorithm helps in identifying potential customers. Moreover, AI helps in identifying patterns of target audience and boosts your platform accordingly. With AI, structuring data can be done easily.<h3 id="data-creation">Data creation:</h3>AI can solve inaccurate and inconsistent data problems. Creating and labeling AI-supported data can be done at the beginning of the digitization process. In addition, AI can create rich metadata for any product, avoiding human fatigue and error.This can be done using a computer vision algorithm that can automatically identify and accurately label various attributes of the product. You can also use the same Algorithmto generate product titles and descriptions, making it easy to search for rich SEO-enabled metadata.SEO-ready tags, titles, and descriptions make finding products on search engines such as Google and Bing. In addition, digitization of image recognition products improves search, browsing, and SEO, achieving 90 ? accuracy and over 20% conversion.<h3 id="boost-visibility">Boost visibility:</h3>Finding a product is the first and most crucial step in a buyer's journey. A straightforward discovery process can help retailers earn the trust of their buyers. Shoppers who find exactly what they are looking for are much more likely to return to the same retail store for their next purchase. On a website, discovery begins with a site search. According to research, 58% of web visitors often use internal search engines to navigate their website.Search engine users are aspiring buyers and an essential segment of e-commerce sites. Therefore, search results on your website should capture the intent of your search query and display products that match the items you searched for as closely as possible.For accurate, consistent, and structured data, the relevance of each individual's results is more important than the relevance of the results. In other words, are the search results tailored to each individual's style preferences?AI-powered personalized retail search helps adjust search results by increasing the specific affinity of each shopper. Each time you click, you can see the buyer's preferences and go to the relevant search bar to understand your customers.<h3 id="increase-in-sales">Increase in sales:</h3>Few people add their favorite items to the cart but never make a purchase. This is known as ?Cart Abandonment.? To help recover this situation, emails are sent to the respective user to purchase as a reminder. According to research, the retailers have lost almost $4 trillion through abandoned sales. Cart recovery emails are the best way to cope up with the loss. More than 60% of retailers utilize it, and it's shown to be the most effective approach to engage with customers and recoup their losses.Since the shopper's inbox is constantly bombarded with many emails, you need to drop mail creatively to stand out from the rest. AI-powered emails help recover loss and build customer relationships, which again helps in conversions and sales.<h3 id="conclusion">Conclusion</h3>Retailers today need automation to collect data; they also need to consolidate that data to speak to the buyer in a single voice. Shoppers should be able to switch from online to offline effortlessly and back online again. This means that the data collected on your website should be made available to store sellers, and your website's recommendations should be improved with products purchased by your store's customers. Once a complete story about each buyer has been created, the data cannot be separated.Retail and e-commerce AI can completely change the way teams work. Automation alone can increase efficiency, give retail units time to think creatively, and provide great online and offline experiences.

Yash Modi

How Artificial Intelligence is transforming the Retail industry

<figure class="kg-card kg-image-card"><img src="https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/151c323fa201f1ab4feff6bc7ee48117.png" class="kg-image" alt loading="lazy"></figure>The retail sector provides <a href="https://www.selectusa.gov/retail-services-industry-united-states">employment</a> to 29 million people directly and supports 42 million indirectly. These pandemic times have brought home how browsing the grocery aisles is part of our normal life that has been disrupted.Organized retail touches several aspects of industry. From real estate operations to merchandising, to shipping &amp; logistics, to customer loyalty programs to old school flyer programs to shopping list apps, the list goes on and on.The grocery industry which is a significant chunk of the organized retail sector has a slim profit margin of <a href="https://thegrocerystoreguy.com/what-is-the-profit-margin-for-grocery-stores/">2.2%.</a>Time has not been kind to this sector. In the UK, over a 10 year period, margins have halved, falling from 8.8% to 4.1%.The industry has to look for efficiencies like never before.Whether a retailer is an old school brick and mortar store or an online only store, from an infrastructure standpoint, there is a large overlap between the two:<figure class="kg-card kg-image-card kg-card-hascaption"><img src="https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/5cb9f07298df483aad201d808da83fc8.jpg" class="kg-image" alt loading="lazy"><figcaption>Unleashing the Power of Machine Learning &amp; AI for the Retail Sector</figcaption></figure>The onset of Machine Learning and Artificial Intelligence has made waves at both kinds of retailers.Here is a quick review of how some retailers are using technology to shave off costs.Automation &amp; Warehousing:Kroger, a leading grocer in the US has been partnering with <a href="https://www.supermarketnews.com/online-retail/kroger-names-location-sixth-ocado-warehouse">a robotics company</a> from the UK to automate a few warehouses to speed up picking of items from its warehouses. Speed is a major consideration for the online ordering segment and continues to push the industry to focus on the use or robots.Walmart has been experimenting with <a href="https://corporate.walmart.com/newsroom/2020/01/08/how-walmarts-alphabot-is-helping-to-revolutionize-online-grocery-pickup-and-delivery">similar robots</a> named Alphabots in partnership with a different vendor. Produce and other fresh items continue to be picked by hand. Alphabots enable real time data sharing and over time this will help better stacking in the warehouses as patterns in items that are frequently ordered together will begin to surface.<h1 id="facial-recognition-loyalty-management">Facial recognition &amp; Loyalty Management</h1>Finally, retailers are no longer content to identify us via swipe of a loyalty card at the point of sale. They want to identify us as soon as we enter the store. The iPhone X has helped to normalize <a href="https://www.theguardian.com/technology/2019/aug/04/facial-recognition-supermarket-facewatch-ai-artificial-intelligence-civil-liberties">facial recognition</a> and using this technology retailers aim to provide a customized experience. By using facial recognition systems retail staff will know what type of products you buy and what your average spend is, so they can give more love to higher spenders. They?ll be able to use software that reads emotion to identify when you are frustrated and notify staff to respond.<h2 id="kroger-app-in-store-recommendations">Kroger App &amp; In-Store Recommendations</h2>Grocery chain Kroger, in collaboration with Microsoft, is testing out the idea of <a href="http://www.digitaljournal.com/tech-and-science/technology/kroger-and-microsoft-collaborate-on-digital-shelf-technology/article/540456">smart shelves</a>. When a customer walks down an aisle and has their Kroger app open, sensors identify the shopper and highlight products they might be interested in. The app might highlight gluten-free products for a gluten-free shopper or kid-friendly snacks for a parent. The app can also provide personal pricing and alert shoppers if an item on their shopping list is on sale.<h2 id="hm-uses-ai-to-keep-popular-items-stocked-popular">H&amp;M Uses AI to Keep Popular Items Stocked Popular</h2>Clothing store H&amp;M relies on staying on top of trends to be successful. The store uses <a href="https://www.reuters.com/article/us-h-m-strategy-ai/back-on-trend-hm-makes-ai-loyalty-drive-to-ride-fashion-cycle-idUSKCN1RT1U7">Deep Learning</a> to analyze store receipts and returns to evaluate purchases at each store. The algorithm helps the store know what items to promote and stock more of in certain locations. The data could find that floral skirts sell well at urban stores and change the inventory to match what customers want.Coca Cola has connected a third of its <a href="https://internetofbusiness.com/supply-chain-iot-coca-cola/">vending machines</a> to the Internet. The company also has its freestyle machines where a customer can combine different combinations of flavours to create their own creation. They have an integration with apps that remind customers when to get hydrated (obviously with a Coke product). Coca Cola also has a mobile wallet which enables customers to use facial id to buy a coke at select kiosks.Facial Recognition to Reduce shopliftingFacial recognition is being used in multiple ways in retail stores. Stores in the UK are using it to detect if purchasers of <a href="https://www.cnet.com/news/with-facial-recognition-shoplifting-may-get-you-banned-in-places-youve-never-been/">alcohol</a> meet the legal drinking age.Stores that have identified shoplifters can share these profiles with other stores too. Shoplifting costs retailers roughly $35.5 billion each year. The initial database can be created by uploading videos of documented shoplifters, organized retail crime associates and disgruntled ex-employees. Of course the Privacy folks may have a field day with this approach.According to the National Retail Foundation, 10.8% of returns made each year are fraudulent, costing the retail industry $9.6 billion a year. Facial recognition also has the potential to protect retailers from a specific kind of return fraud. By uploading images of customers that suspected of abusing generous product return policies, companies can be alerted when such customers come in or make a purchase.Facial Recognition and AR used by SephoraSephora, is a leading example of using AR (augmented Reality) to let the consumer experience a product that many first thought was not suitable for online retail. Sephora took their time and only when they were convinced that the technology had achieved a certain level of preciseness, did they opt-in. Over 20,000 products sold by the retailer were added to the program. By 2018, the <a href="https://www.techrepublic.com/article/how-sephora-is-leveraging-ar-and-ai-to-transform-retail-and-help-customers-buy-cosmetics/">Sephora Virtual Artist</a> has seen 200 million shades tried on, and over 8.5 million visits to the feature, according to the company.IKEA has also use a <a href="https://gizmodo.com/ikeas-expands-augmented-reality-app-lets-you-fill-an-e-1838362429">similar concept</a> where before you buy, you can see how the furniture may look in your home.With so much going on in the retail industry, can any one afford to stand still?

Taha Sherif

Unleashing the Power of Machine Learning & AI for the Retail Sector

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