5 Real World AI in Marketing Examples
Artificial intelligence technologies like machine learning, deep learning and natural language generation (NLG) offer digital marketing professionals unprecedented ability to improve personalization, productivity and performance.
But getting started with AI marketing is easier said than done.
There's plenty of commentary on how brands could use AI marketing. But there are fewer publicized real world use cases that your marketing team can model and learn from.
To address this need, we have collected examples of how real brands are using artificial intelligence marketing right now. These examples are taken from our exclusive Spotlight series with AI marketing solutions providers.
To make this as actionable as possible, we've only included use cases where specific brands were mentioned, so digital marketing pros can connect the dots and model actual companies using an AI solution.
AI in Marketing Examples
1. Create Content at Scale
Natural language generation (NLG) refers to AI technology that automatically creates narratives from structured datasets. Currently, there are two major NLG providers: Narrative Science and Automated Insights.
Narrative Science's solution, Quill, is used by companies like "USAA, American Century Investments, Deloitte, Groupon, Credit Suisse, MasterCard, Franklin Templeton and the U.S. intelligence community" says Katy De Leon (@KatyDeLeon), VP of marketing at the company. Quill helps these firms translate data into written narratives. By automating content creation, these brands are able to drive performance by creating more content in less time, as well as surfacing key insights from data to drive decision-making.
Automated Insights has a solution called Wordsmith that is used by firms like the Associated Press and the Orlando Magic to produce content at scale. The AP uses the tool to automatically write corporate earnings reports and Minor League Baseball recaps. Freed up from writing these repetitive, but critical, narratives, AP reporters can focus on deeper reporting for bigger stories that require a human touch. The Orlando Magic uses the technology to generate thousands of personalized fan emails with special offers "unique to each fan," says director of product management Adam Long (@Adam_B_Long).
The use cases for this type of technology in content marketing are clear: NLG makes it possible to partially automate different types of written content.
2. Improve Online Ad Performance
Albert uses its artificial intelligence and machine learning platform to offer insight into advertising effectiveness. These insights can then be used to inform every marketing campaign and marketing strategy moving forward.
"We've developed proprietary, patent-pending algorithms that leverage predictive analytics to execute on data-driven actions, and deep learning technology to act effortlessly on unpredictable situations that would traditionally require decision-making and reasoning by a human marketer," says CEO Or Shani.
The tech empowers brands to gain insight into advertising activities, determine what works and predict what will work next using Albert's AI algorithms. "Harley-Davidson announced that it credits 40% of its NYC sales to Albert, and global retailer EVISU will soon release results of its first year working with us, which has resulted in a 500% increase in digital advertising ROI," Shani says.
3. Predict Which Marketing Efforts Will Be Successful
With enough customer data, an AI platform may even be able to predict which digital marketing efforts and prospects are the most promising. CaliberMind provides insights about customer behavior that informs marketing decisions thanks to sophisticated artificial intelligence.
"Deep research into B2B customer buying behavior reveals that the most effective customer advocates can't be identified by title, role and function," says CEO Raviv Turner (@ravivturner). "Rather, they fit specific psychographic and behavioral profiles. CaliberMind's is the only predictive marketing AI solution that leverages customer psychographic data to uncover new insights about customer behavior."
The tech is used by beta customers like Citrix, NetApp, Datavail, Convercent and Gusto to target and tailor their marketing efforts more effectively to generate higher sales conversions and better quality deals.
4. Extract Actionable Insights from Data
Marketers are drowning in data. Luckily, AI can be great at sorting out the signal from all the noise. AI system PaveAI processes Google Analytics data from nearly 300 million visitors per month for customers, then turns that data into actionable written reports that surface key insights .
"PaveAI uses machine learning and data science algorithms to implement statistical models," says founder Eric Ho. "Along with context-based knowledge, this allows us predict the value of each segment of users that visit a website. We then use natural language generation (NLG) to make these insights digestible to our businesses and customers."
5. Create Better Performing Content
AI is used for more than just content creation at scale. Brands are leveraging the technology to improve how and what content is created.
Acrolinx uses natural language processing (NLP) and machine learning to create content for major brands like "IBM, Microsoft, Boeing and Caterpillar," says founder and CEO Andrew Bredenkamp (@abredenkamp). Facebook, Wells Fargo and Nestle are also customers. Acrolinx can predict content success and guide writers on how to keep content on-brand and on-target. "Our AI can learn your brand and audience goals and make sure your content is aligned with them," he says.
Opentopic is an AI tool used by publishers like Time and The Economist, as well as brands like Unilever and NBC/Comcast to parse huge amounts of unstructured data into real insights. This functionality helps customers create hyper-targeted audiences, automate the distribution of marketing assets, and automatically optimize those assets to achieve campaign goals.
Boomtrain works with brands such as Forbes, CBS, The Onion and Chow.com to increase clicks, engagements and revenue from their content. Boomtrain's machine learning algorithms do this by surfacing content that is most likely to engage individual consumers, then delivering it in automated fashion.
"We analyze a user's behavior in real-time to track mood and compare this activity to look-alikes, much like Amazon's predictive functionality," says director of partnerships Dheeraj Sareen (@Dheeraj_Sareen).
About Mike Kaput
Mike Kaput is Chief Content Officer at Marketing AI Institute and a senior consultant at PR 20/20. He writes and speaks about how marketers can understand, adopt, and pilot artificial intelligence to increase revenue and reduce costs. Full bio.