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How to Do Better Content Marketing with AI
Blog Feature

By: Mike Kaput

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August 1st, 2019

How to Do Better Content Marketing with AI

In the course of our work at Marketing AI Institute, we get asked one question often:

How do I get started with artificial intelligence for content marketing?

It's a great question—and one that couldn't be more important to answer.

Artificial intelligence offers marketers unprecedented opportunities to increase revenue and reduce costs. And content marketing is one of the top use cases today for artificial intelligence—with a range of commercially available tools to build smarter content strategies and execute at scale.

But how do you actually determine use cases for AI in content marketing, then apply AI tools to those use cases?

This post is designed to help.

It'll walk you through a useful framework to determine AI use cases in content marketing, then offer a few next steps to actually get started applying the technology.

A Framework to Find Use Cases for AI in Content Marketing

We help organizations large and small apply AI by using a use case model of consulting.

In a use case model, we identify use cases for AI, then ask the following question about each use case:

Assuming AI technology could be applied, how valuable would it be for your team to intelligently automate each use case?

We use our AI Score for Marketers tool as a guide here.

AI Score for Marketers is a free assessment tool that helps marketers evaluate 60+ common marketing use cases for AI. For each use case, marketers assign a Value to Intelligently Automate (VIA) rating to each. The VIA is a 1-5 rating, with 1 being "no value" to intelligently automate a task and 5 being "transformative."

In this post, our examples of common use cases all come from AI Score for Marketers.

For instance, the top-rated use cases for AI that we found from AI Score for Marketers responses are:

  • Analyze existing online content for gaps and opportunities.
  • Choose keywords and topic clusters for content optimization.
  • Construct buyer personas based on needs, goals, intent and behavior.
  • Create data-driven content.
  • Discover insights into top-performing content and campaigns.
  • Measure return on investment (ROI) by channel, campaign and overall.
  • Adapt audience targeting based on behavior and lookalike analysis.
  • Optimize website content for search engines.
  • Recommend highly targeted content to users in real-time.
  • Assess and evolve creative (e.g. landing pages, email, CTAs) with A/B testing

Your ratings for use cases like these are all subjective. They completely depend on the value of intelligently automating the use case for you and your organization.

For instance, our organization spends a lot of time and resources on writing blog content. The VIA of "blog writing" for us is a clear 5.

Ready? Let's get started.

A Framework for Thinking About Use Cases

So, aside from the common use cases we'll be suggesting here, how do you come up with use cases for AI in content marketing on your own?

It helps to have a logical, use-case based framework—so we created the 5Ps of marketing AI framework for this purpose.

The 5Ps of content marketing AI is based on our direct discussions with entrepreneurs and engineers building and applying AI tools. The framework consists of five categories, with potential use cases sorted into each one.

1. Planning: Build intelligent strategies.

Sample use cases:

  • Determine goals.
  • Construct buyer personas.
  • Discover keywords and topic clusters.
  • Analyze existing content for gaps and opportunities.
  • Determine editorial calendar topics.
  • Capture competitive intelligence.
  • Segment contact databases.
  • Identify companies and contacts most likely to convert.
  • Predict conversion paths and points along the buyer journey.
  • Predict churn.
  • Prescribe marketing strategies and tactics.
  • Allocate digital paid budget by channel and audience.

2. Production: Create intelligent content.

Sample use cases:

  • Draft social media updates.
  • Write data-driven content.
  • Optimize content for search engines.
  • Curate content.
  • Develop ad copy and creative.
  • Write email subject lines.
  • Write nurturing/sales email workflows.
  • Convert voice to text, and text to voice.
  • Recognize, categorize and auto-tag images.
  • Analyze (and score) text for grammar, sentiment, tone and style.
  • Design websites.

3. Personalization: Power intelligent consumer experiences.

Sample use cases:

  • Recommend highly targeted content.
  • Deliver predictive product recommendations.
  • Personalize content, offers and web experiences with images, text and CTAs.
  • Engage users through bots and chat.
  • Serve up contextual ads based on user history and look-a-like data.
  • Answer voice and text questions.
  • Deliver customized search results.  
  • Individualize and optimize email send time.

4. Promotion: Manage intelligent cross-channel and cross-device promotions.

Sample use cases:

  • Adjust digital ad spend in real-time by channel and audience.
  • Optimize cross-channel campaigns.
  • Test headlines, landing pages, images and creative.
  • Schedule social shares.
  • Improve email deliverability.
  • Deliver (re)targeted ads.

5. Performance: Turn data into intelligence.

Sample use cases:

  • Score leads and continually adapt the lead scoring system.
  • Monitor activities and outcomes.
  • Discover insights from analytics.
  • Forecast performance.
  • Write performance reports.

Think of the 5Ps as a way to organize all the tasks you and your content marketing team do in a single day, week, month, quarter, or year.

Got it?

In the next section, we'll walk through how to use the 5Ps to identify use cases for your content marketing.

How to Find Content Marketing Use Cases for AI

Now that you're armed with the 5Ps of marketing AI, let's get some actual use cases using the following steps.

1. List out every marketing task you do. [5 minutes]

Write down all the marketing activities you perform over a given timeframe of your choice, either a day, week, month, quarter, or year.

I find breaking down tasks daily or weekly to be most helpful.

Write down tasks big and small, using any language you like. All we're looking to get is a sense of all the things that occupy your time on a regular basis. 

For instance, here's a list of activities I might potentially do on any given day.

  • Create overall marketing strategies.
  • Create marketing campaign strategy.
  • Do keyword research.
  • Do content intelligence research.
  • Do competitor research.
  • Analyze campaign-level performance data.
  • Pull performance reports.
  • Create blog content.
  • Edit blog content.
  • Upload blog content.
  • Find and upload images to go with content.
  • Draft social media shares.
  • Write web copy.
  • Communicate with clients.
  • Build chatbots.
  • Create CTAs and popups.
  • Write marketing emails.
  • Build marketing email workflows.
  • Draft newsletters for subscribers. 

You get the idea. Do the same for your day-to-day or week-to-week activities.

2. Sort your list into the 5Ps framework. [5 minutes]

Now, take your list and sort each item into one of the categories listed above in the 5Ps. This doesn't have to be perfect, and some tasks may fit into more than one category. The goal is simply to better organize the list, so don't overthink it.

For instance, I might organize my list in the following fashion:

Planning

  • Create overall marketing strategies.
  • Create marketing campaign strategy.
  • Do keyword research.
  • Do content intelligence research.
  • Do competitor research.

Production

  • Create blog content.
  • Edit blog content.
  • Upload blog content.
  • Find and upload images to go with content.
  • Draft social media shares.
  • Write web copy.

Personalization

  • Build chatbots.
  • Create CTAs and popups.
  • Write marketing emails.

Promotion

  • Communicate with clients.
  • Write marketing emails.
  • Build marketing email workflows.
  • Draft newsletters for subscribers. 

Performance

  • Analyze campaign-level performance data.
  • Pull performance reports.

Now that you have your use cases sorted, let's figure out which ones to prioritize.

3. Rate each use case's Value to Intelligently Automate (VIA). [5-7 minutes]

Remember how we discussed AI Score's Value to Intelligently Automate (VIA) rating?

This is where we ask ourselves the following question:

Assuming AI technology could be applied, how valuable would it be for your team to intelligently automate each use case?

The rating is 1-5, with 1 being "no value" and 5 being "transformative."

Go through each of your use cases now, and assign a 1-5 VIA to each use case.

When thinking about the potential value of automating a use case with AI, think about the following to inform your ratings:

  • How long do you and your team spend on the task?
  • How frequently do you spend time on the task?
  • How valuable is the time of the people who do the task?

These questions can help you develop a "gut feeling" for how low or high to rate each task.

Anything that takes a lot of time or requires the attention of people who have high-value time is a great candidate for a high rating.

For instance, here are three sample ratings from my list above:

  • Create blog content (Rating: 5)Why? Because we have two full-time team members spending dozens of hours per month creating content, in addition to freelancer hires. It's one of the most common tasks we do, so intelligently automating it with AI would be transformative.
  • Analyze campaign-level performance data (Rating: 4) — Why? Our campaigns run on insights from data, so data analysis is critical to what we do. Our human experts are pretty good at it, but I know machines are far better. If we could outsource this to AI, we'd get better insights and free up time for other tasks, so this is quite valuable.
  • Upload blog content (Rating: 2) — Why? Despite all the content we create, the data tells me uploading blog posts takes very little time at all, and we often have junior hires working on this. It likely wouldn't be very valuable to spend time and energy applying AI here.

Congratulations! You now have a preliminary list of use cases for AI in your content marketing, along with ratings of how valuable each one might be to automate. 

Now, what do you do with this information?

What to Do with Your Content Marketing AI Use Cases

It's time to get your hands dirty with AI.

From your list, pick one or more of your highest-rated use cases.

These will form your first attempts at AI pilots. 

Keep in mind, I say first because we've rated the value of potentially automating each use case. There's no guarantee that AI exists to automate every use case you've listed out.

In fact, AI isn't always the best solution for every single challenge you face in content marketing. In some cases, you might be able to solve your challenges with smarter strategy or better resource allocation.

That means for each of our use cases we'll need to conduct some more research into what's possible with AI. 

Here are three next immediate actions to take once you've picked one or more use cases to explore.

1. Find vendors.

Our Marketing AI Buyer's Guide is a great place to start finding vendors who might be able to help you intelligently automate a use case.

You can sort vendors by each of the 5Ps, which should help you map your use case to potential tools.

If you don't find a vendor for your use case in the Buyer's Guide, don't be afraid to conduct some basic online research. Google is your friend, and you can often make some progress by looking up terms like "AI for [BLANK]."

Run through this step for a number of your use cases, so you come away with at least a few vendors who look interesting to explore further.

If you're really stuck, feel free to contact us here and we'll see if we can help.

2. Talk to vendors and conduct demos.

Once you have a few vendors who look promising, start demoing. 

Many vendors offer demos or free trials, and most are happy to answer your questions. Ask them both about their technology and your use cases. If their product doesn't help with your specific use cases, they may be able to offer recommendations of products that can help.

Many times, the only way to truly understand what AI solutions are capable of is this kind of in-person research and experimentation. 

Here are a few questions you might want to ask vendors:

  • How does your company use AI today?

  • What AI capabilities are on the product roadmap?

  • What type of data do I need for the solution to work?

  • Is there any type of minimum size dataset I need to use it?

  • What kind of in-house capabilities do I need?

  • My top use case is ____. Can you help?

  • Do you have any case studies specifically about AI features?

3. Look at your existing tech stack.

The existing marketing tools you use may have AI capabilities. Many major platforms are actively investing in artificial intelligence. AI-powered capabilities that map to your use cases may exist in your current tools—or be on the product roadmap.

Don't be afraid to call your account rep, and ask about the provider's AI capabilities and plans.

Follow the steps above, and you should be able to make serious strides towards taking AI from theory to practice.

In doing so, you've taken a concrete step towards leveraging the power of AI to supercharge your content marketing.

Get free access to the Ultimate Beginner's Guide to AI in Marketing: https://www.marketingaiinstitute.com/beginners-guide-access

About Mike Kaput

Mike Kaput is the Director of Marketing AI Institute and a senior consultant at PR 20/20. He writes and speaks about how marketers can understand, adopt, and pilot artificial intelligence to increase revenue and reduce costs. Full bio.

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