{"id":1675360,"date":"2021-07-23T18:27:14","date_gmt":"2021-07-24T01:27:14","guid":{"rendered":"https:\/\/www.retailpro.com\/News\/blog\/?p=1675360"},"modified":"2021-08-06T10:21:16","modified_gmt":"2021-08-06T17:21:16","slug":"2-retail-uses-of-artificial-intelligence-in-a-post-covid-world","status":"publish","type":"post","link":"https:\/\/www.retailpro.com\/News\/blog\/index.php\/2021\/07\/23\/2-retail-uses-of-artificial-intelligence-in-a-post-covid-world\/","title":{"rendered":"2 Retail Uses of Artificial Intelligence in a Post-COVID World"},"content":{"rendered":"\n
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The amount of information collected from an in-store POS is vast. Coupled with e-commerce data gathered from online transactions, retailers can glean a pretty accurate picture of who their customers really are: their tastes, sizes, socio-economic status and demographics. <\/p>\n\n\n\n

Artificial intelligence (AI) is being used to correlate all of that information to provide an efficient, personalized experience that caters to shoppers’ preferences. <\/p>\n\n\n\n

Numerous companies are investing significantly in the technology; Meticulous Research predicts the global AI in retail market<\/a> will grow 35.9% between 2019 and 2025, reaching $15.3 billion.<\/p>\n\n\n\n

AI can help discern the patterns in consumer behavior that can answer the questions on every retailer\u2019s mind: how do we keep shoppers coming back?<\/p>\n\n\n\n

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AI for shopper convenience<\/h3>\n\n\n\n
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Using AI to make sense of customer information can help retailers create efficient shopping experiences, whether that’s at a physical retail location or online. <\/p>\n\n\n\n

These types of retailer-directed experiences are particularly appealing to millennials<\/a>, the first digitally native generation.<\/p>\n\n\n\n

In general, the fact that millennials gravitate toward digital-first approaches puts retailers and brands under pressure to continually innovate<\/a>; businesses are striving not only to know what the customers want before they reach the store, but also to have it readily available. <\/p>\n\n\n\n

Retailers that create an atmosphere of convenience and ease are generally rewarded with repeat business. <\/p>\n\n\n\n

That was perhaps most evident at the height of the COVID-19 pandemic, when customers turned to e-commerce because of the ease of filling their shopping needs, from clothing to groceries to cleaning supplies. For 15 months, online ordering surged. <\/p>\n\n\n\n

In response, brick and mortar retailers expanded their channels, and many that once eschewed online orders quickly found significant revenue gains by allowing customers to place orders online and collect them curbside. <\/p>\n\n\n\n

Now, as retailers emerge from the past year with new methods of meeting customer needs, they also have found themselves possessing significantly more shopper data. <\/p>\n\n\n\n

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Personalized promotions<\/h3>\n\n\n\n
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Retailers can use AI to build effective marketing campaigns<\/a> that can not only help shoppers find the products they are looking for, but also to discover others they didn’t even know they wanted. <\/p>\n\n\n\n

Product intelligence plus customer data combined with AI can produce targeted marketing and promotions<\/a> that can encourage loyalty, increase return visits, and increase conversion rates. <\/p>\n\n\n\n

Online, AI can help decrease bounce rates and improve engagement on the website by using personalized recommendations and banners. <\/p>\n\n\n\n

AI can help retailers provide the personalized experience customers receive online when they are shopping in stores. <\/p>\n\n\n\n

For example, AI cameras and sensors can record when an item is placed back after a customer selects it. <\/p>\n\n\n\n

If that action is a trend, the manager can decide if the item should be displayed elsewhere, in an effort to provide it more visibility. <\/p>\n\n\n\n

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Better forecasting<\/h3>\n\n\n\n
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AI-driven tools analyzing Retail Pro POS data<\/a> help retailers understand who their consumers are, which allows them to provide personalized offers and deals. <\/p>\n\n\n\n

Business analytics<\/a> provide valuable insight into customer demographics, peak operation hours, buying trends and inventory. <\/p>\n\n\n\n

Retailers can examine purchasing history from POS transactions to determine what influences customers\u2019 buying habits. <\/p>\n\n\n\n

By integrating automation from AI-driven POS systems in multiple sales channels \u2014 online, in-store, apps, etc. \u2014 retailers can more clearly understand their customers\u2019 experiences and continue to refine them to better suit their needs. <\/p>\n\n\n\n

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AppCard for Retail Pro: AI-powered personalized marketing<\/a><\/p>\n<\/div><\/div>\n\n\n\n

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Integrating Retail Pro POS data and COVID-influx of ecommerce data for hyper-personalization<\/a><\/p>\n<\/div><\/div>\n\n\n\n

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Operational growing pains during COVID-19: Inefficiency stemming from poor data visibility<\/a><\/p>\n<\/div><\/div>\n\n\n\n

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Innovating millennial loyalty<\/a><\/p>\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"

The amount of information collected from an in-store POS is vast. Coupled with e-commerce data gathered from online transactions, retailers can glean a pretty accurate picture of who their customers really are: their tastes, sizes, socio-economic status and demographics.  Artificial … Continue reading →<\/span><\/a><\/p>\n","protected":false},"author":12,"featured_media":1675365,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[175,196,77,176,30,76,29],"class_list":["post-1675360","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-announcements","tag-ai","tag-data-insight","tag-millennials","tag-personalized-marketing","tag-promotions","tag-retail","tag-retail-software-data"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t