Joanna and Chip Gaines’ physical store, Magnolia Market, is renowned for its exceptional customer service. The physical location of Magnolia has the goal of “inspiring you to own the environment you’re in.” To do this, they developed a genuine brand experience that incorporated dining, entertainment, shopping, and a garden. The team believed that Magnolia Silos’ e-commerce operation needed to provide the same experience since not everyone could visit them in person. Magnolia collaborated with Shopify Plus to develop an augmented reality software that lets customers “put” items in their homes and experience them in 3D. Magnolia used AR to depict its products with the finest level of photorealism imaginable. The achievements set Magnolia apart from its rivals and improved its e-commerce sector, a critical component in corporate growth. The company employs augmented reality to show its wares as realistic-looking, high-resolution pictures. This attribute turned into the primary success factor and assisted Magnolia in differentiating itself from rivals in the eCommerce space.<\/p>\n\n\n\n
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2. 100x More Organic Traffic Is Generated By Tomorrow Sleep<\/h3>\n\n\n\n
Alibaba, eBay, Nike, and BMW. Numerous companies included in this article are well-known worldwide brands and household names with marketing budgets that are much beyond those of regular firms. But as the mattress startup, Tomorrow Sleep has shown, you don’t have to be a multibillion-dollar company to take advantage of Al in marketing. Tomorrow Sleep was introduced in the middle of 2017; content marketing only began one year later. Although the company was aware that increasing organic traffic would be essential for success in the long term, it soon became clear that its more established competitors had a very firm grip on the organic search industry. It had to concentrate on the most significant, intent-driven terms because it lacked the resources and scale to produce endless amounts of material. At that point, it used MarketMuse, an AI-powered platform for intelligence, content research, and writing. MarketMuse first pinpointed the main subjects and subtopics that Tomorrow Sleep needs to write about, after which it examined the top search results for each main subject to look for opportunities and gaps. The outcomes were startling. Within a year, Tomorrow Sleep’s organic traffic increased from 4,000 monthly visitors to 400,000 monthly visitors, enabling it to not only outrank much bigger rivals like Casper for key themes.<\/p>\n\n\n\n
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3. More Humanity Is Incorporated Into Chase’s Copywriting<\/h3>\n\n\n\n
A five-year contract was reached by Chase Bank and Persado, a business based in New York that uses artificial intelligence in marketing. Chase tested Persado’s suggestions and discovered that using machine learning in copywriting enabled them to promote more humanity. For instance, a human-written digital advertisement stated: “Access cash from your property equity.” Contrarily, Persado’s version stated: “It’s true\u2014you can get cash from your property equity.” The latter variant fared well with buyers. Although Chase is the first company to utilize this kind of extensive machine learning copywriting, other companies intend to increase their usage of Persado’s technology. Around 250 marketers from the retail, financial, and hotel industries currently work with the company, according to Persado.<\/p>\n\n\n\n
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4. The Rankbrain Algorithm And Ad’s Automatic Bidding System Of Google<\/h3>\n\n\n\n
Everyone probably uses Google regularly and engages with AI, consciously or unconsciously. The RankBrain algorithm upgrade by Google is the pinnacle of Al in digital marketing, aside from autosuggestions on the search engine. This upgrade began enhancing user experience metrics from 2015 ranking websites, such as bounce rate, CTR, and average time spent on a particular page. Businesses provide material to Google, consumers engage with it, and Google uses this data to learn more and provide users with more filtered results. When “maximize clicks” is chosen for the bidding strategy option, the organization asks the user to make a selection during the campaign setup process for Google AI marketing. Thanks to artificial intelligence, the marketer’s website ultimately receives greater traffic. With low-cost, continuously running artificial intelligence advertising, artificial intelligence encourages Facebook users to build their brand familiarity. To display relevant advertising, it gathers data from recent platform visitors as well as cookies. By providing people with pertinent information, goods, and services, AI can ascertain their interests and have a significant impact on their life.<\/p>\n\n\n\n
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5. eBay Drives Email Marketing Success With Brand Language Optimization<\/h3>\n\n\n\n
eBay, a massive online market, is constantly looking for fresh approaches to interest its users. It has a ton of examples of AI marketing, so to speak. The business has been collaborating with Phrasee, a customer experience platform powered by artificial intelligence since 2016 to improve its marketing text with a focus on email. Optimizing the effectiveness of email marketing is straightforward for the brand. A\/B test a few subject lines or CTAs to determine which is more effective. Then, use that more often. But things get a little trickier when you’re a big company like eBay. The US, UK, and Germany alone have over 100 million email subscribers, making it extremely difficult to create compelling subject lines that can increase open rates. To relieve its internal team of the creative burden, eBay resorted to Phrasee, which combines deep learning and natural language generation to produce copy at scale while constantly enhancing performance. The computational linguistics team at Phrasee created language models for eBay, enabling the world’s largest online retailer to instantly create unique copy tailored to its consumer needs, brand tone, and particular promotions.<\/p>\n\n\n\n
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6. Starbucks Provides Personalized Recommendations Using Predictive Analytics<\/h3>\n\n\n\n
Businesses that use predictive analytics to detect client needs can boost organic revenue by 21% year over year, as opposed to an average of 12% without them. One company example using its mobile app and loyalty card to gather and analyze client data is Starbucks. Plans for personalization were first revealed in 2016. Since then, they’ve developed an impressive app. It keeps track of every purchase’s specifics, including where and when it was made. Starbucks processes this data using predictive analytics and provides customers with tailored marketing communications. These messages contain advice for when a user enters a nearby store and deals to raise the customer’s average order value.<\/p>\n\n\n\n
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7. Mastercard Uses Artificial Intelligence To Produce Large-Scale Content<\/h3>\n\n\n\n
Artificial intelligence (AI) technology known as “natural language generation” (NLG), uses structured data to automatically produce stories. Currently, Automated Insights and Narrative Science are the two NLG service providers. According to Katy De Leon, VP of marketing at Narrative Science, organizations including “USAA, Credit Suisse, Deloitte, American Century Investments, Franklin Templeton, Groupon, MasterCard, and the U.S. intelligence agency” employ Quill, a product from the company. These companies receive assistance from Quill in turning data into narratives. These brands can improve performance by producing more content and by uncovering crucial data insights to guide decision-making by automating content development. Businesses like the Orlando Magic and the Associated Press use a tool from Automated Insights called Wordsmith to create content at scale. The program is used by the AP to generate summaries of Minor League Baseball games and corporate earnings reports. As a result of not having to write these tedious but important tales, AP reporters are free to concentrate on more in-depth reporting for larger stories that demand a human touch. According to Adam Long, product management director at the Orlando Magic, the technology is used to create thousands of individualized fan emails with offers that are “unique to each fan.” NLG makes it feasible to partially automate many sorts of written material, which makes it a logical use case for this technology in content marketing.<\/p>\n\n\n\n
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8. AI In Marketing Aids Ama Boost Newsletter Participation<\/h3>\n\n\n\n
It can’t be simple working as a marketer for the American Marketing Association (AMA). When your audience consists of marketing professionals, sending subpar communications is not an option. Each aspect must be tailored to the demands of each member. But because the AMA covers a wide spectrum of topics, from written content production to UX design, it was practically difficult to meaningfully personalize its email for its 100,000+ subscribers. Without AI, marketing would be impossible. The AMA can utilize an AI engine that generates customized subject lines based on member interest data by collaborating with platforms such as artificial intelligence-driven personalization rasa.io. It allowed the AMA to highlight the most pertinent content to each newsletter recipient. The AMA’s monthly subscriber engagement rate has increased by an astonishing 42% since partnering with rasa.io. Editor-in-chief Molly Soat stated: “Our readers and members come from several backgrounds, so not every marketing-related item will be pertinent to everyone that subscribes. This newsletter’s ability to personalize for specific readers within such a large population is priceless.<\/p>\n\n\n\n
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9. Alibaba Establishes A Fashion Store<\/h3>\n\n\n\n
Alibaba, a leading retailer, has a physical “FashionAI” store in Hong Kong that uses artificial intelligence to improve the shopping experience for clothes. Alibaba outfitted its retail locations with smart mirrors that show apparel information and recommend matching items and garment tags that can identify when an item is handled. Alibaba also intends to incorporate a virtual wardrobe application that would enable customers to view the attire they tried in-store with the physical shop. As consumer expectations change, Alibaba is adapting by using technology. In a poll conducted by the National Retail Federation, consumers reported that 66% of brick-and-mortar stores and 80% of online retailers improved their customers’ online shopping experiences.<\/p>\n\n\n\n
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10. To Produce Content That Performs Better, Nestle Leverages AI<\/h3>\n\n\n\n
AI is employed for more than only large-scale content generation. Brands are utilizing technology to enhance the type and process of content creation. According to founder and CEO Andrew Bredenkamp, Acrolinx produces content for well-known companies like “IBM, Microsoft, Boeing, and Caterpillar” using machine learning and natural language processing (NLP). Customers include Facebook, Wells Fargo, and Nestle. Acrolinx can forecast the success of the content and advise authors on how to maintain it on-brand and on-target. To ensure that your content is following your brand’s and audience’s goals, he claims that “our Artificial intelligence can learn about them.” Publishers like The Economist and Time, and companies like Unilever and NBC\/Comcast, employ Open topic, an artificial intelligence tool, to transform massive amounts of unstructured data into actionable insights. Customers can use this functionality to build hyper-targeted audiences, distribute marketing materials automatically, and automatically improve those materials to meet campaign objectives. Boomtrain collaborates with companies including Forbes, CBS, The Onion, and Chow.com to raise content’s click-through rates, engagement, and income. To accomplish this, Boomtrain’s machine learning algorithms surface material the most likely to engage certain users before automatically distributing it.<\/p>\n\n\n\n
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11. Launch Of Personalize By Amazon<\/h3>\n\n\n\n
Amazon started providing individualized product suggestions using machine learning. Even yet, the brand has found it crucial to make these features available to businesses who use Amazon Web Services for their websites. AWS customers can now leverage the machine learning technology of Amazon.com by using Amazon Personalize, which was made generally available by Amazon in June 2019. Since its first release, the Amazon team has improved its personalized capability to the point where it can now provide up to 50% better recommendations for several products that change quickly, such as movies, books, music, and news articles. Personalize is already being used by brands like Yamaha, Domino’s, Subway, and the wedding planner Zola to emphasize musical instruments, offer ingredient and flavor recommendations, and create unique style combinations.<\/p>\n\n\n\n