Powered by the digital revolution, the world of content marketing looks very different than it did 20 or even 5 years ago. It’s no longer enough for businesses to throw up content haphazardly on their blogs, hoping that their choice of topics will somehow attract prospects.
Competition for users’ finite attention grows fiercer with each passing year, as new marketing tactics and strategies rise and fall. In particular, personalization and targeted marketing have enabled companies to better understand and connect with their audiences than ever before.
As a result, customers have grown to expect personalized experiences and interactions with the businesses they choose to patronize. For example, 52 percent of consumers say they’re likely to switch brands if a company doesn’t deliver personalized communications.
Yet all too often, marketers are unable to fulfill customers’ expectations of personalized products and services. Although 77 percent of marketers believe that real-time personalization is crucial, 60 percent also report that they struggle to personalize content in real time.
With hundreds, thousands, or millions of customers, how can your business hope to provide a personalized experience to each one?
The answer is clear: artificial intelligence for marketing. Over 40 percent of marketers who currently use AI say that it’s one of their most important tools for improving sales and marketing performance. And with marketing AI adoption at just 18 percent, there’s plenty of room for future growth.
In this article, we’ll discuss how AI and machine learning are poised to transform the face of content marketing.
In early 2019, AI research company OpenAI announced that it had developed a text-generating AI called GPT-2. Based on a short prompt of a sentence or two, the AI is able to generate a few paragraphs of plausible content that develop on the prompt’s themes and ideas.
While GPT-2 produces results that are often superficially impressive, analysts have noted that the system suffers from issues such as long-term coherence and repetitiveness. This is to say that a general AI that can generate plausible marketing content is still a long way off.
Still, there are certain use cases in which AIs can indeed generate simple content, freeing up human writers for more complex work. Straightforward stories that are largely “fill in the blank,” such as stock reports and football scores, can now be generated entirely by a machine.
In 2015, IT research and advisory firm Gartner predicted that by 2018, 20 percent of business content would be authored by these “robo-writers.” The Associated Press, for one, uses an AI system to publish 3,000 short financial articles per quarter.
Machine-generated content is one example of marketing automation, but the possible use cases go well beyond there.
Recommender systems, like those in use at Amazon and Netflix, suggest relevant content to users, based on their previous purchases or viewing activity. Netflix estimates that 75 percent of viewer activity is driven by these recommendations, and not by intentional searches.
Similarly, marketing recommender systems can suggest the most relevant content to your customers and prospects, based on factors such as:
Using marketing automation systems, marketers can reach out to customers using the most effective platform—whether email, social media, text message, or direct mail—and automatically deliver appropriate targeted messages and campaigns.
It’s hard to browse the web these days without a chat bubble popping up in the corner of your screen, asking if you need any help. Chatbots are tiny software applications that conduct text conversations with human users.
These bots can help with simple queries and issues that may not need the input of a human sales rep or support agent. For example, Whole Foods has debuted a Facebook Messenger chatbot that lets users type in an ingredient or cuisine and discover mouth-watering recipes.
Chatbots can make your sales, marketing, and customer service departments dramatically more efficient, saving them from the hassle of low-level inquiries. It’s no surprise, then, that 80 percent of businesses say they want to be using chatbots by 2020, according to an Oracle survey.
Companies now have more data on hand than they know what to do with, including marketing data. The challenge for many organizations is to turn this raw data into keen insights that can deliver real value for your business.
AI and machine learning technologies can help you rapidly process and analyze vast quantities of information, uncovering hidden connections and ideas. In response to user demand, customer relationship management (CRM) tools such as HubSpot and Salesforce are already integrating AI and machine learning into their platforms.
Which content is most effective at holding readers’ attention and converting them into paying customers? What are the keywords that we should target with our next round of blog posts? AI-enabled marketing tools can provide the answers to these questions and many more.