What AI Can and Can’t Do for Your Marketing Automation Process
Artificial intelligence (AI) is one of the hottest frontier marketing buzzwords going today. Semantic search, machine learning, and content recognition all fall under the AI umbrella. All of these techniques have incredible implications for cost-effective scaling of marketing automation systems. However, hype may outpace application at this point.
Technology moves faster than money. Well informed marketers understand that AI, at this point, is no silver bullet. Here are some of the applications you can improve with AI and a few things that you should not yet look for it to accomplish.
AI can help generate valuable content.
Given a dataset, AI content-writing programs can give you a relatively human-sounding article. You can actually get a choice of articles, as AI can spin certain content as well. Look to the WordSmith application to lead the charge here. In 2017, this program gave marketers over two billion pieces of content.
AI can't completely personalizeyour copy.
AI works well if you are dealing with an event that centers around data—for instance, generating flyer content for an upcoming convention or your annual earnings report. AI has trouble creating opinion based content. You may even be able to write an article about industry best practices. You are not going to get a sophisticated political opinion piece or in-depth pop culture editorial. Currently, marketers are using AI to quickly generate informational content so they can spend more time on the creative side.
AI can speed up your programmatic media buying efforts.
Machine learning algorithms have the ability to utilize propensity models to place ads in front of highly targeted audiences. The technology works well for businesses in industries that are not controversial, as Google is becoming less forgiving of ads that show up on unsavory websites. Currently, AI has the ability to recognize questionable web pages and quarantine them away from a programmatic ad buy, but the technology is not perfect.
AI can't guarantee you the most efficient programmatic media ROI.
Google changes the rules concerning its ad network when it pleases. Google is under no obligation to inform marketers of these changes or the punishments it imposes on marketers who are not in compliance. The current generation of AI still places ad buys on terrorist websites in some cases. There still needs to be a human at the helm, especially if a business is in controversial industries such as cannabis, weapons and artillery, adult content, etc.
AI can help target an audience and segment that audience into distinct buyer profiles.
Big Data on a wide, general demographic is becoming less relevant to marketers as time goes on. Unless you have the ability to drill down into that data, organize and segment that data, and create trend models based on it, you will begin to leak ROI as you market to its underlying audiences. However, AI now has the ability to predict the segments of an audience more likely to convert, targets who will become more loyal, and prospects who will be first movers.
AI can't function with bad data.
You cannot look to AI to give you good models from bad data, even if you invoke the best machine learning program into your process. The mantra of “garbage in, garbage out” still applies. No AI will be able to tell you if you input bad data. The moral of the story: No matter how sophisticated your AI propensity modeling, you still need a competent human being at the beginning of the process.
AI can help you move prospects through the customer journey.
Marketers no longer have to hold a prospect’s hand through the entire customer journey. If you have precise data, your AI may actually be better than your human marketers in identifying which prospects would convert with a discount. Dynamic pricing is a great application for modern AI, and if you are losing profit margin on samples and free giveaways, this is an application you can use.
AI can't personalize an entire customer journey.
Despite the ability of AI to target a prospect at a specific point and direct that prospect into a new stage of buying, it cannot be left completely alone. Prospects simply have too many choices in their buying decisions. They move in erratic ways and separate themselves from automated marketing schemes. If a prospect becomes a data outlier, AI will probably lose sight of him. Although you no longer need a marketer to babysit the customer journey, you do need a competent human to check in on important clients from time to time.
Overall, do not look to AI to replace your entire marketing department. However, it is a great tool for your marketing team. Use it to track and attack the more stable customer journeys and limit human error within your core marketing program. For the more creative elements of your marketing automation process, you still need great human marketers. AI may be able to replace these people in the future, but do not give anybody walking papers for a few years!
Nayomi Chibana is a journalist and content editor at Visme, a browser-based infographic and presentation tool. Besides researching trends in visual communication and next-generation storytelling, she’s passionate about data-driven content marketing.