Today’s marketers are all looking for new ways to find and attract their ideal audience. But in the fast-paced and ever-evolving digital marketing landscape, it’s getting harder and harder to reach your people and get results.
Enter AI in marketing.
What Is Artificial Intelligence Marketing?
Artificial intelligence marketing (AI Marketing) is a method of leveraging customer data and AI concepts like machine learning to anticipate your customer’s next move and improve the customer journey.
Advancements in Artificial Intelligence offer companies better ways to do that. AI can help build more effective marketing strategies, improve the customer journey, and change the way businesses attract, nurture, and convert prospects. The graphic below shows how AI and machine learning can be incorporated into every step in the customer’s lifecycle.
Examples of AI in Marketing
Source: Smart Insights
AI in marketing may feel more science fiction than fact to many, but it’s not a far-off concept; it’s here right now. According to Salesforce, just 29% of marketing leaders used AI in 2018, but that number surged to 84% by 2020. And by the end of 2021, global spending on artificial intelligence hardware, software, and services is expected to exceed $340 billion, per a forecast from IDC.
If you haven’t considered the power of AI for marketing, now’s the time to learn more. To help you get started, we’ve compiled ten impressive artificial intelligence marketing examples.
1. Magnolia Market Bridges Online-to-Offline
Magnolia Market, the brick-and-mortar shop owned by Joanna and Chip Gaines, is known for its stellar customer experience. The mission of Magnolia’s physical location is to “inspire you to own the space you’re in.” They created an authentic brand experience combining food, games, shopping, and a garden to achieve this goal.
Because not everyone can visit the Magnolia Silos, the team felt that its e-commerce operation also needed to deliver the same experience. Magnolia worked with Shopify Plus to create a storefront and an augmented reality app that allows users to view products in 3D and “place” them in their homes. AR allowed Magnolia to render its products with the highest-possible photo-realism. The results set Magnolia apart from the competition and strengthened its e-commerce arm, a key driver for company growth.
2. Chase Achieves More Humanity in its Copywriting
Chase Pairs up with Persado
Chase Bank signed a five-year deal with Persado, a New York-based company that applies artificial intelligence to marketing creative. After testing Persado’s solutions, Chase found that using machine learning in their copywriting helped them achieve more humanity in their marketing.
For example, one digital ad written by humans read: “Access cash from the equity in your home.” Persado’s version, on the other hand, read: “It’s true—You can unlock cash from the equity in your home.” The latter version performed better with customers.
Chase is the first to engage in this type of large-scale machine learning copywriting, but other brands are planning to expand the use of Persado’s technology. According to Persado, the company already works with 250 marketers across retail, finance, and hospitality.
3. Starbucks Uses Predictive Analytics to Serve Personalized Recommendation
According to the research firm Aberdeen, companies identifying customer needs through predictive analytics can increase their organic revenue by 21% year-over-year, compared to an average of 12% without predictive analytics.
Starbucks is one example of a brand using its loyalty card and mobile app to collect and analyze customer data. They announced plans for personalization back in 2016.
Starbucks Personalized Recommendations
Since then, they’ve built quite the app experience. It records the details of purchases, including where they are made and at what time of day. Starbucks uses predictive analytics to process this data and serve customers with personalized marketing messages. These messages include recommendations when a user approaches a local store and special offers to increase the customer’s average order value.
4. Alibaba Opens a FashionAI Store
Retail giant Alibaba opened a physical “FashionAI” store in Hong Kong to streamline the fashion retail experience through Artificial Intelligence. Alibaba equipped its stores with intelligent garment tags that detect when the item is touched and smart mirrors that display clothing information and suggest coordinating items. Alibaba also has plans to integrate the brick-and-mortar store with a virtual wardrobe app that will allow customers to see the outfits they tried on in-store.
Alibaba’s use of technology is a response to the consumers’ shifting expectations. According to a National Retail Federation survey, 80% of shoppers say retail technologies and innovations have enhanced their online buying experience, while 66% say the same about brick-and-mortar retail.
5. Unilever Helps Ben & Jerry’s Identify the Trend for “Ice Cream for Breakfast”
Unilever Uses AI in Marketing
Consumer goods company Unilever uses AI data centers across the globe to synthesize insights from a range of sources, including social listening, CRM, and traditional marketing research. Using this technology, Unilever discovered a link between ice cream and breakfast: at least 50 songs in the public domain include lyrics that talk about “ice cream for breakfast,” and businesses like Dunkin’ Donuts are already selling ice cream in the morning.
Unilever took this insight and developed a range of cereal-flavored ice creams (including Fruit Loop and Frozen Flakes) for the Ben & Jerry’s brand.
6. Amazon Launches Personalize
Amazon was a pioneer in using machine learning to offer personalized product recommendations. Still, it has been a challenge for the brand to extend these capabilities to companies running their sites on Amazon Web Services.
In June 2019, Amazon announced the general availability of Amazon Personalize, which brings Amazon.com’s same machine learning technology to AWS customers for use in their applications.
The Amazon team has enhanced its functionality since the initial rollout, to the extent that Personalize can now deliver up to 50% better recommendations across a range of fast-changing product types, including books, movies, music, and news articles.
Brands including Domino’s, Yamaha, Subway, and the wedding company Zola are already using Personalize to highlight musical instruments, in-store catalogs, deliver ingredient and flavor recommendations, and devise individualized style combinations.
7. Sephora Chatbots
According to Drift’s latest State of Conversational Marketing report, chatbots are seeing faster growth than any other brand communication channel, with usage increasing by 92% between 2019 and 2020.
Beauty brand Sephora was an early adopter of AI. They began using a chatbot to dispense beauty advice on Kik in 2017.
Sephora’s chatbot helped consumers narrow down choices, beginning with a quiz about their product preferences. Product preferences are especially helpful in the cosmetics industry, where the options can be overwhelming and difficult to purchase without testing in person. Sephora gained valuable insights from their chatbot and saw enough engagement from that experiment that it’s since launched more chatbots on Messenger.
8. eBay Uses Brand Language Optimization to Drive Email Marketing Success
Global e-commerce marketplace eBay is always striving to find new ways to engage customers. That means it’s got plenty of AI marketing examples to show us.
Since 2016, the company has been working with artificial intelligence-powered customer experience platform Phrasee to enhance its marketing copy, focusing on email.
For the average brand, optimizing email marketing performance is relatively simple. A/B-test a couple of different subject lines or CTAs; see which works best; do more of it. But things get a little trickier for a company of eBay’s scale. With over 101 million email subscribers across the US, UK, and Germany alone, crafting impactful subject lines to drive open rates is a colossal undertaking.
Wanting to shift the creative burden away from its internal team, eBay turned to Phrasee, which uses a combination of natural language generation and deep learning to create copy at scale while dynamically optimizing performance.
Phrasee’s approach to AI content creation & optimization
Phrasee’s computational linguistics team built language models for eBay, allowing the e-commerce giant to generate custom copy tied to its brand tone, customer needs, and specific promotions at the click of a button.
In the years since it first teamed up with Phrasee, eBay has enjoyed substantial improvements in its key email marketing metrics, including:
- 16% average open uplift
- 700,000+ incremental opens per campaign
- 56,000+ incremental clicks per campaign
- 31% average click uplift
9. Tomorrow Sleep Drives 100X Increase in Organic Traffic
Nike; Alibaba; eBay; BMW. Many of the companies in this article are multinational corporations and household names with marketing budgets larger than most organizations’ bottom lines.
But you don’t need to be a multi-billion-dollar corporation to leverage the benefits of artificial intelligence in marketing, as demonstrated by mattress startup Tomorrow Sleep.
Launched in mid-2017, Tomorrow Sleep only got started with content marketing 12 months later. While it knew that driving organic traffic would be crucial to its long-term success, the company soon realized its longer-standing rivals had the organic search market sewn up pretty tight. It didn’t have the budget and scale to create limitless volumes of content, so it had to focus on the most important, intent-driven terms.
That’s when it turned to MarketMuse, an AI-powered content research, intelligence, and writing platform. First, MarketMuse identified the primary and related topics Tomorrow Sleep needed to create content on; it then analyzed the top 20 search results for each primary topic to track gaps and opportunities.
MarketMuse’s content gap tool
The results were striking. Not only was Tomorrow Sleep now able to outrank much larger competitors like Casper for key topics, but it also saw its organic traffic increase from 4,000 per month to 400,000 per month within a year.
10. Marketing AI Helps AMA Boost Newsletter Engagement
Being a marketer at the American Marketing Association (AMA) can’t be easy. When marketing experts make up most of your audience, you simply can’t afford to send low-quality communications.
Everything needs to be personalized to the needs of individual members. But given the diverse range of the AMA’s content –– covering everything from written content development to UX design –– it was near-impossible to do meaningful personalization for each of its 100,000+ newsletter subscribers.
Impossible without AI in marketing, that is. By teaming up with artificial intelligence-driven personalization platform rasa.io, the AMA was able to take advantage of an AI engine that generates individualized subject lines based on member interest data, thereby highlighting the most relevant and interesting content to each newsletter recipient.
Since joining forces with rasa.io, the AMA has seen its monthly subscriber engagement rate increase by an impressive 42%. As editor-in-chief, Molly Soat explained: “Our members and readers span many industries and specialties, so not every post about marketing will be relevant to all of our subscribers. The ability to personalize this newsletter for individuals within such a massive audience is invaluable.”
From valuable insights to personalized product recommendations and technology-enabled assistance, AI in marketing is already driving some of the biggest advances in overall customer experience. What impressive examples of AI in marketing have you seen lately?
If you’re interested in learning more about how new technologies can help improve your customer engagement strategies, check out our social media strategy conference!