Content marketers who embrace artificial intelligence stand to build a lasting competitive advantage for their brands and in their careers.
How do we know?
Marketers told us.
Using our AI Score for Marketers assessment tool, we’ve asked hundreds of digital marketing professionals to rate the value of intelligently automating more than 60 common AI use cases.
All use cases are scored on a 1 – 5 scale based on the same question: “Assuming AI technology could be applied, how valuable would it be for your team to intelligently automate each use case?”
The majority of the top 10 use cases dealt directly with content marketing. They included use cases like: analyzing content gaps, choosing keywords, creating data-driven content, and optimizing content for search engines.
AI can provide a significant competitive advantage in all of these areas. But getting started isn’t as easy as picking up the phone and asking companies if they have AI.
Instead, use these tips to accelerate your experimentation and adoption of artificial intelligence for your content marketing.
1. Prioritize use cases.
Artificial intelligence is built to perform narrow, specific tasks at superhuman levels. Some of the use cases mentioned above may be valuable areas for you to investigate. But you’ll need to experiment with AI to better understand what it is and isn’t capable of doing.
To do that, list out everything you do daily as a content marketer in a given week or month. This might include tasks like: writing blog posts, uploading content, optimizing articles, drafting social shares, etc.
Next, include a column in your spreadsheet that lists out how much time you estimate each task takes.
Finally, sort your list by the most time-intensive tasks. This list is a good place to start looking for AI applications. Each item represents a use case that AI can potentially do better than humans.
Not every use case will have an AI solution. Patience and experimentation are required to find the AI tools that can actually reduce or eliminate time-intensive tasks.
2. Understand what data you have.
Think about all the data you have access to as a marketer. These data sources might include a CRM system, marketing automation system, call tracking systems, etc. If needed, list out every data source available.
Then, try and figure out if this data can be leveraged to better attract consumers with engaging content. If you don’t have a data-driven background, you may need to enlist others at your company or in your network to help.
3. Go talk to tech platforms and solutions providers.
Once you understand potential use cases and the data you have available, talk to tech companies. A good place to start is with the providers of your existing tech solutions. Ask them about the AI capabilities of any marketing or sales platforms you’re already using.
Many existing platforms are building AI and more intelligent capabilities right into the core product. That makes it much easier to test out AI capabilities for yourself, using software you already know well.
If these platforms don’t use AI, ask if it’s on the product roadmap, so you can get a better idea of what’s coming.
Other AI-powered vendors and startups are happy to discuss their products and use cases with you. But don’t be afraid to ask tough questions about how smart these products actually are.
One of the best ways to get knowledgeable about the marketing AI landscape is to get your hands dirty with demos and trials, so you can see for yourself what AI can—and can’t—do for your content marketing.
Obstacles to Getting Started With AI
Don’t just ask for “AI.”
You’ll want to have a healthy understanding of what AI means before you go searching for solutions. Just asking for “AI” isn’t an effective way to vet solutions. Educate yourself on terms like AI, machine learning, and deep learning before you dive in.
Once you do dive in, don’t bite off more than you can chew.
When you decide on use cases to solve for with AI, pick ones that offer small, quick wins you can rally support around internally. Scoring a win early with AI gives you a much greater chance of success of securing buy-in for the technology long-term.
Look for something where the probability of solving the problem is reasonable, and the investment to do so isn’t substantial — rather than a long-term project that involves every division of the company.
Remember: AI isn’t a silver bullet, but finding the right solution for your business challenges can give you an immense advantage in the marketplace.
If you want to accelerate getting started with AI, I’d encourage you to join us at the Marketing AI Conference (MAICON), July 16-18, in Cleveland, Ohio.
MAICON is designed to help marketing leaders truly understand AI, educate their teams, garner executive support, pilot priority AI uses cases, and develop a near-term strategy for successfully scaling AI. The event has 40+ sessions and 60+ speakers from companies like Amazon and Softbank Robotics.
Written by Mike Kaput