Convergence Or Collision? AI and Content Marketing, Part 7

CONVERGENCE OR COLLISION? AI AND CONTENT MARKETING, PART 7
CONVERGENCE OR COLLISION? AI AND CONTENT MARKETING, PART 7

In Part 7 of our Convergence or Collision? AI and Content Marketing series we’re taking a look at the brands, organizations, and publications using AI.

Today, major news outlets, startup brands, and global companies alike use AI to help analyze data, create and deliver targeted content, and to drive more effective marketing strategy. Today, we’ll dive into how brands are using AI to improve their bottom line and customer experience.

But, first, how do the majority of media outlets, marketers, and businesses use AI?

Marketing.

AI is used by businesses, brands, and media outlets for 3 key marketing functions:

  • Content creation and curation
  • Predictive intelligence for more personalized experiences
  • Chatbots for customer service

Content creation and curation

To start, perhaps the most buzzed about quality of AI platforms is the ability of these programs to write content like reports, articles, and more from scratch. Despite the recent onslaught of stories about AI, say, writing the next Great American Novel, AI is most typically used for writing content that relies heavily on crunching big data.

To this end, AI-written content is most associated with shorter sports recaps and roundups, business reports, and other more easily automated pieces that focus on turning data into readable sentences.

In addition to the production of more rote, routine content, AI is also used heavily for content curation. To this end, companies use AI programs to identify trending topics online, through algorithms. By trawling social media channels and published content (like newer blog posts), AI can help drive content planning and creation towards the most timely, conversation-building topics.

Plus, AI tools can also identify the characteristics of top-ranking content, then make suggestions on how to boost the performance of a new or under-serving article or post.

Uses of AI content creation and curation by publications:

  • Associated Press – uses natural language processing to scan and analyze social media feeds for hot stories and trendy topics. AP is also working on their own internal tool to verify social and user-generated content faster.
  • The New York Times – uses automation for some of its wedding announcements.
  • The Washington Post – uses Heliograf, its in-house automated storytelling technology for basic sports coverage and to provide localized election results.
  • Yahoo! Sports – Yahoo! Sports uses NLG to create their massive amounts of fantasy American football draft summaries and match recaps every week.

Predictive intelligence

Secondly, companies are using AI to help identify and target audiences for better and more effective content interaction. Known as predictive intelligence, or predictive analytics, these kinds of AI programs work by ensuring users find the right kind of content, on the right channel, at the right time.

In short, predictive intelligence helps to customize and personalize online experiences through every stage of the marketing funnel, through automation.

So, how does predictive analytics work? By monitoring existing customer behavior and then building a profile around that behavior, predictive intelligence can predict what the user will want next, based on their past actions.

Here’s an example: if a blog reader clicks through multiple posts about setting up a home gym, predictive intelligence could then serve this same reader targeted fitness content. Think: a series of emails promoting an at-home gym equipment sale, blog posts with free downloadable workout plans after an email capture, or a promo for virtual training sessions.

A few interesting ways companies employ Predictive Intelligence:

  • Amazon – the billion dollars e-commerce platform uses natural language processing to automatically recommend items to its customers and predict future purchases, based on a user’s past actions and profile.
  • Nike – uses big data to know where consumers are, then selects and curates products in nearby stores with targeted messaging and ads. AI also helps Nike identify and woo high-value customers with exclusive events, designs, and collaborations.
  • Harley Davidson – the motorcycle brand uses the AI program Albert to identify potential customers looking to purchase a hog. AI also Harley Davidson to target generate new leads and close sales.
  • Starbucks – the coffee giant uses its loyalty card and mobile app to collect and analyze customer data. Then, targeted marketing messages are sent to users that highlight past purchases, specials for the time of day (“2pm slump?”), and nearby stores.

Chatbots for better customer service

Finally, most companies and media outlets today use AI in the form of chatbots, or the 24/7 robo-customer service reps we’ve all interacted with online.

Also known as “conversational agents,” chatbots use natural language processing to replicate human speech or written content during a “conversation” with a real, live human.

Chatbots do this by processing the text presented by the user, and then responding accordingly, based on a series of algorithms. Then, the chatbot presents a series of appropriate responses that should (theoretically) help the human on the other end of the conversation.

While chatbot experiences are rife with screw-ups, brands love bots because they offer an avenue for nonstop customer support. And, even if a chatbot can’t solve a user’s problem, the good ones can help to quickly re-direct users to the correct (live) person or resource that will remedy their issue.

A few interesting uses of chatbots:

  • HelloFresh – the meal delivery service offers Freddy Freshbot, their Facebook Messenger chatbot, to help their users find relevant recipes based on their current pantry and freezer. The AI way of answering, “What’s for dinner?”
  • Hilton the hotel chain launched their chatbot Xiao Xi, for Hilton China mobile apps. Xiao Xi helps guests by answering their questions like their hotel’s information, local weather, Hilton Honors checking, and other customized promotion deals and offers.
  • The North Face – uses a chatbot to recreate the experience of an in-store shopping trip, complete with a salesperson. To do this, the bot asks a short series of questions to online shoppers about their jacket preferences, then offers options based on those responses.
  • Sephora – the makeup retailer offers the Sephora Reservation Assistant and Sephora Color Match. The Reservation Assistant helps customers make appointments with the in-store specialists. Meanwhile, Color Match uses augmented reality to help match and find the correct foundation, lipstick shade, or eye shadow, based on a customer’s uploaded photo.

In our next post, we’ll be discussing what pundits and futurists have to say about AI and the future.

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