It’s tempting for enterprise marketing teams to look toward AI-generated content as an easy way to automate and scale creativity. However, like any shiny new coin, there are two sides to AI, especially as it relates to everything from creative endeavors, to content automation, and analytics.
It’s all about nuance.
If you’ve ever used AI-powered Google Translate in a conversation with colleagues or friends overseas, you probably know what I mean. From the cringeworthy, to your friend’s gentle reprimand, “That’s not exactly the way we French/Turks/Japanese/ say it.”
Today’s AI definitely has its limitations.
So don’t go assigning your next blog post to your resident robot just yet. Chances are, you’ll end up with something like the output Content Technologist founder Deborah Carver received when she assigned an AI content creator to write a test paragraph about the value of content marketing:
“The only reason your company should use content marketing in any way is that you can use it to achieve these goals. Therefore, you must always define your business goals and then use them to develop marketing strategies for content. Too often, companies consider content marketing as an independent activity that is done on their own. Instead, first determine the goal based on the value you want to achieve for the company (sales, revenues, potential customers, etc.).”
Meaningless fluff. If one of your copywriters came up with this drivel, you’d likely assign them to write coupons. Maybe forever.
It’s in the nuances that your audience will find meaning.
Is There Any Value in AI-Generated Content?
What can you use AI-generated content for, then? Here are a few suggestions that can help your teams save time and effort.
Micro-Articles and Ads
As Carver points out, companies can put AI to good use to write short, data-based micro-articles, news stories, email subject lines, or short ads. However, be sure to edit them carefully.
Here’s why. AI makes mistakes. If you’ve ever used the premium version of a grammar checker to help you detect typos or grammatical errors, you know what I mean. While checking a post I wrote recently, my grammar checker red-flagged the word “article,” suggesting that I substitute the term “item.”
Sorry, Grammar Police. I wasn’t referring to an “item.” I was referring to an article.
Additionally, some AI-generated subject lines don’t always sound “native.” Again, back to nuances. Just check and tweak them before you send them out to your customers.
Data-Based Insights in Natural Language
Your teams don’t have the time to read and digest data from reports. AI content creation programs can “read” a graph and spit back a rough draft. That draft can serve as a foundation for your content teams to create blog posts, portions of white papers, and video scripts.
Content Topic Generation
As Blogging Wizard’s Elise Dopson advises, content marketers can leverage AI to uncover great content ideas. AI-powered tools, such as Ahrefs or Buzzsumo, can scout out what topics your competitors are writing about. Your teams can use these titles and topics as a springboard for your own.
Similarly, your teams can plug in your brand’s main keywords into Google’s Keyword Planner to prime the pump when the creative well goes dry.
Brief Creation
Creating briefs are time-consuming and often take as much research as writing. Several AI content creation platforms, such as MarketMuse, can look at existing digital content about your topic and create a detailed, structured outline that serves as the skeleton for a blog post, white paper, or website content.
To do so, it uses natural language generation (NLG) to create content that approximates human dialogue. AI content providers often provide templates – also called “narrative types” – to direct the AI solution to follow a given formula, such as a blog post, a subject line, a report, or even a poem. With many solutions, your content teams can also create custom templates that follow each project’s specific style requirements.
Once you have your AI-generated outline, fill in any missing details and tweak it so that your content writers are crystal-clear on what they need to cover. Here’s where a content collaboration tool can be worth its weight in gold.
If the topic is highly technical, you might want to bring some of your engineers or other subject matter experts to contribute information about how something works, why it works, or other pertinent details. On the other hand, if you want to address some of your target audience’s main concerns, consult your sales and customer support teams to introduce real-world scenarios to flesh out your outline.
Writing Rough Drafts
Imagine the time your teams could save if they could spend most of their time polishing articles and other content, instead of slogging through the intensive creative process that goes into creating a first draft.
Today’s AI programs can do that initial work for you. Once you get it, all the facts, research, and preliminary structure are already set. Then, you can restructure it as needed and polish it with the color, nuance, and humanity that will build an emotional connection to your readers.
Editing Content
Once you and your teams polish each piece of content, you need to edit and proofread it for grammatical faux pas. AI-powered grammar checkers are superb time-savers for detecting misspellings, incorrect punctuation, and grammatical errors. And, if your teams get a little wordy, these tools act as a high school English teacher’s red ink on that paper you thought was perfect.
These grammar checkers also help your editing teams detect when writers overuse the passive voice (“The project has been completed”) instead of the active voice (“We completed your project”). When a writer uses the passive voice too much, it bores the reader, and they click away – likely, to one of your competitors’ articles.
Another word of caution here. Proofreading programs often flag transitional language, such as “as a result,” “in addition,” etc. as “too wordy.” However, readers need these verbal connectives as mileposts to help guide them from thought to thought. Therefore, use human editors to check your final copy.
Our favorite grammar checker is Grammarly. However, don’t just mindlessly accept all its suggestions. As with all AI solutions, it works better when it partners with a live person.
Content Amplification and Analysis
Once you have your content ready to go, you need to amplify its reach. Using an AI-powered content automation solution can eliminate the hassle of posting manually – and publish it at the optimum time to reach more of your target audience.
Then, use your content analytics program to analyze the impact of each piece of content on your audience. Those pieces that don’t perform up to par don’t need to end up in your virtual trash bin. With AI, you can go beyond A/B testing to test several improvements against each other and update your piece with the best among them.
I know I’ve talked about a lot of tools here in the post, but it’s inevitable that you’ll need different tools to handle different aspects of your content marketing process. At Divvy, we’re working towards a day when a lot of these AI-based processes can be directly integrated, but it’s still the early days.
In the meantime, just remember that enterprise teams will need a central hub for organizing campaigns and content projects, scheduling deadlines, collaborating on creation, and seeing the fruits of all this labor with content performance analytics. A comprehensive content marketing platform fills these gaps. Get in touch with our team today to request a demo and see how Divvy can help.