Ai Marketing Examples
The widespread adoption of artificial intelligence (AI) was once considered a far-fetched notion dreamed up in sci-fi stories, but it’s now a living, breathing entity of our everyday reality.
In today’s fast-changing marketspace, marketers seek new ways to find and attract their ideal audience. But in the ever-evolving digital marketing landscape, reaching people and getting results is getting harder than ever.
Here enters AI. Artificial intelligence marketing (AI Marketing) is leveraging customer data and AI concepts like machine learning to anticipate the customer’s next move and improve the customer journey. Advancements in artificial intelligence offer companies much better ways to do that. AI can help build more effective marketing strategies, improve the customer journey, and change how businesses attract, nurture, and convert prospects.
Big advertising companies around the world are trying their hands on this new technology to upgrade their game. Let’s look at few of those examples:
Netflix: It is a nobrainer when we talk about the importance of AI in Netflix’s marketing efforts. But one thing that stands out is its use of AI for personalization. Netflix does this by using the data about what content its members watch and enjoy along with how they interact with the service to get better at figuring out what the next great movie or TV show for them will be. AI collects the data and recommends the shows and movies; even the artwork that you see is personalized according to the user. As a result, Netflix’s recommended engine is worth over $1 billion per year, which mostly comes from the personalized grid of suggestions that is catered only to the viewers’ taste.
Coca-Cola:With the world’s largest beverage distribution system, the Coca-Cola Companymarkets, manufactures, and sells beverage concentrates, syrups, and finished beverages, including sparkling soft drinks, water, sports drinks, juice, dairy, plant-based drinks, tea, and coffee. Coca-Cola uses AI to personalize its marketing campaigns and improve customer engagement. The company uses AI algorithms to analyse customer data and create personalized messages that resonate with its audience.
Sephora: Understanding the power of AI early on, thriving cosmetics brand Sephora has been using chatbot technology to offer its audience the most personalized, informational customer experience possible. After conducting some extensive consumer research, the brand realized that many customers found Sephora’s extensive choice of products overwhelming, having to browse through a host of pages to find something suitable in certain categories. Hence, to eliminate the exhausting process, Sephora launched an interactive quiz to help guide its users through the shopping process, led by chatbots which offer tailored tips and suggestions based on specific answers or responses. Due to the success of the initiative, Sephora now offers its very own chatbot-powered shopping service via Facebook Messenger as it continues going from strength to strength. This ultra-personalized AI-powered Messenger service includes a virtual colour match assistant, a reservations assistant, and even, KitBot which is an autonomous chatty makeup tips and advice expert.
American Express:American Express is a leading personal, small business, and corporate credit card issuer. The company’s travel-related offerings include traveller’s checks, credit cards, corporate and personal travel planning services, tour packages, and agencies for hotel and car-rental reservations. American Express uses AI to analyse customer data and detect fraud. The company uses machine learning algorithms to identify patterns and anomalies in customer transactions and prevent fraudulent activities.
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Nestle:To enhance its content marketing efforts and create personalized communications for its audience, global food and beverage giant Nestle used natural language processing (NLP) technology to produce targeted content for various segments of its audience. In addition to this content-centric innovation, Nestle also uses AI-driven data processing platforms to get well and truly under the skin of its customers resulting in new innovations including virtual assistants and chatbots that are consistently transforming insight into action. It is indeed a digital shift that has advanced sales in recent years.
Amazon: Amazon.com is a vast Internet-based enterprise that sells books, music, movies, housewares, electronics, toys, and many other goods directly or as the middleman between other retailers and its own millions of customers. Amazon uses AI to power its recommendation engine, which suggests products to customers based on browsing and purchasing history. This AI-powered recommendation engine has helped Amazon increase its sales and improve its customer satisfaction.
Starbucks: Starbucks presented a strategic plan for using AI and big data back in 2016, and the brand has made good progress on its promises to investors by enhancing its reward program and personalization to connect more deeply with its customers. Personalization has always been a key part of the customer experience at Starbucks, with the ability to customize drinks for the customer’s individual taste. Moving on, the company also uses its loyalty card and mobile app to collect and analyse customer data including purchases, where they are made, and at what time of day. The company uses predictive analytics to process this data in order to deliver personalized marketing messages to customers including recommendations when they’re approaching their local stores, and offers aimed at increasing their average spend. A virtual barista service on the app powered by AI also allows customers to place orders directly from their phone via voice command. As well as delivering a more personalized customer experience, Starbucks uses their data from 90 million transactions every week to inform business decisions such as where to open new stores, and which products they should offer.
Uber:Uber is a transportation company with an app that allows passengers to hail a ride and drivers to charge fares and get paid. More specifically, Uber is a ridesharing company that hires independent contractors as drivers. Uber uses AI to optimize its pricing strategy and improve its revenue. The company uses machine learning algorithms and predictive analytics to analyse customer demand and adjust its pricing dynamically based on real-time demand.
