Kalie Fry By Kalie Fry • September 10, 2018

How to Use AI to Produce Content at Scale

How to Use AI to Produce Content at Scale

“So, what is exactly is AI?” This is the million-dollar question right now for clients and marketers alike. With all the splashy headlines and blockbuster movies surrounding artificial intelligence (AI), it can be difficult deciphering what it actually is. Let alone, what it’s actually intended for.

Businesses want to apply new AI technology to their marketing but don’t know where to begin. Beyond the hype is a simple framework that makes AI not only approachable – but actionable. In today’s blog, I’ll walk you through the 5 P’s of the AI model and how you can use these tools to produce content at scale.

(Just a head's up – as artificial intelligence becomes more common, the role that local listings and reviews play in your success will only continue to increase. Learn more here.)


Back to Our Question: What is AI?

To get started, it’s important to boil AI down to its most basic principle: AI augments human knowledge and capabilities. (Ready for that in English?) Think back to your days in math class. Just like a formula, an algorithm is a set of instructions that tells a machine what to do.

Let’s use a marketing example to further illustrate.

Whenever I create an email sequence, I implement a set of rules to determine the path a user will take. For example, if a user was on the growth-driven design page of our website when they subscribed, they’ll be assigned to a specific workflow that shares knowledge on wire-framing, development and UX testing.

This certainly beats completing this process by hand, but it still requires time to input rules, make sense of the data and redirect efforts from there. With AI, the machine creates its own algorithms, determines new user paths and can even provide suggestions on how to tweak your content strategy. Legit, right?

The AI model is the process of presenting use cases and identifying the right tools to make your marketing more intelligent on its own. I recently had the opportunity to sit in on a workshop led by Paul Roetzer of MAII, where he broke the model down into the 5 P’s. (Believe me, this will all make sense later.)


The 5 P’s of Marketing AI

Planning: Predicts behaviors, defines strategies, prioritizes activities and determines how to allocate your marketing resources.

Production: Creates, curates and optimizes content like blogs, emails, landing pages, videos and ads.

Personalization: Personalizes experiences through automated emails, content/product recommendations, AR/VR and websites.

Promotion: Manages cross-channel promotions to drive engagement and actions like audience targeting, social publishing and digital media management.

Performance: Turns data into intelligence through automated narratives and insights – using it to optimize performance.

You may be thinking, “Well, that’s all fine and dandy. But, how do I use AI in my marketing?” It all begins with identifying manual, repetitive marketing tasks you’re already doing that could be intelligently automated. Here’s my 5-step framework for using AI to produce content at scale.


How to Get Started With Marketing AI

Step 1: Evaluate Use Cases

Start by listing out your everyday, repetitive marketing tasks. Then, break them down into repeatable steps. Identify which areas are taking up the most of your time. Some examples of these tasks in the content realm might include:

  • Creating and editing blogs
  • Promoting content using social media and paid ads
  • Sending marketing emails to subscribers
  • Pulling reports on various marketing campaigns
  • Measuring performance against your marketing KPIs


Step 2: Break a Down a Case Into Repeatable Steps

While you may not be able to fully automate your marketing with AI, there’s a good chance you’ll be able to optimize and streamline several tasks. To avoid overwhelming yourself, I’d recommend choosing a single use case to start with. 

For me, something that takes up a lot of time is producing content. However, that’s a bit broad to work with. Blogging requires the most time, so let’s break down that process into a list of repeatable tasks:

  • Keyword research
  • Identifying high-performing topics
  • Building content plans
  • Creating editorial schedules
  • Writing, editing and publishing blogs


Step 3: Research and Narrow Solutions

Once you’ve lined out these repeatable steps, you have a foundation to begin exploring AI solutions. Begin by conducting some basic searches for the use case and/or its steps. Using the blogging scenario from above, here are some examples of terms I’d search for:

  • “AI for blog writing”
  • “AI for content topics”
  • “AI for content performance”
  • “Content calendars with AI”
  • “AI for editing”
  • “AI marketing automation”

You may not have much information on these solutions or their capabilities so it’s important to visit their websites and take notes. I also recommend sifting through articles and reviews on the platform. As you gather ideas, store your ideas in an excel sheet or similar document.

To limit bias during the research process (eye-catching motion graphics don’t always guarantee a good platform), I recommend evaluating each solution based on its capabilities, integrations, usability, data tracking and pricing. For blogging specifically, here are a few solutions that have the potential to cut the planning stages of content production in half:

CONCURED (Topic Strategy): It shows you which topics drive engagement and what to write about next.

Crayon (Competitor Research): It helps you track, analyze and act on everything happening outside of your business.

Acrolynx (Editing): It uses a unique linguistic analytics engine to “read” all your content and provides immediate guidance to improve it.

BrightEdge (SEO): It blends search intent discovery, optimized content creation, and performance measurement into one platform.


Step 4: Demo and Test

In my initial search, I compiled a list of over 50 artificial intelligence platforms. In blogging, one of the most time-consuming areas is content research so I narrowed down my list to the four listed above. Reviewing their websites, each of these tools could benefit the production process in some way. However, it’s crucial to test-drive these solutions before deployment.

AI tools have fairly specific applications, so you need to ensure your business is pulling in the necessary data to make it work properly. Don’t let the flashy language fool you either. It’s easy to get sucked in by bold claims so it’s important to demo the platform to double-check its capabilities. Because marketing AI is still in the development stages, testing is key.

When test-driving an AI tool, I recommend having your use case notes nearby. This way, you can share the specific tasks you’re looking to automate or streamline. This not only saves time but also gives the vendor the opportunity to show you “behind the scenes” features that may not be included in the training.


Step 5: Build an AI Strategy

Once you’ve landed on a couple solutions, it’s time to secure room in your budget and apply these tools to your marketing. If you’re a marketing manager, you’ll likely need to create an AI strategy for your supervisor or stakeholders to formally explain how you’ll roll out these tools.

If you’re a business owner, you can skip this step. However, it's still important to plan how you'll you implement the platform and how it'll affect your marketing team moving forward. You'll also want to think about the KPIs you'll use to test the ongoing effectiveness of the AI tool.


AI is Here: Is Your Business Prepared for the Shift?

At this point, you may be wondering, “Will machines eventually replace marketers?” Though AI has a bright and exciting future, the answer is no. However, I predict that it’ll be a real game changer – similar to the dawn of social media and video. AI will allow you to deep-dive into your analytics, tapping into hidden knowledge you didn’t know about your competitors and your own content.

To prepare yourself for the next big shift in marketing, start compiling an ongoing list of use cases and potential solutions. This ensures that when the time comes, you’ll be ready to roll out with AI and leave your competitors in the dust.


Is There a Way for Robots to Fix Bad Reviews?

Unfortunately, machines can’t change customers’ minds. However, there are some strategies you can implement to handle negative reviews and turn frustrated customers into second-chance sales. In this free ebook, we teach you a 3-step process for responding to negative reviews and how to minimize them moving forward. To access your free copy of the ebook, click below.

How To Respond To Negative Reviews