3 Actionable Steps to Get Started with Artificial Intelligence in Marketing
There’s lots of commentary on how AI will impact marketers, but not as much about how to actually get started using artificial intelligence in your business. Based on our own work with marketing AI, we’ve put together this short, actionable guide on how to start assessing AI’s potential impact on your business.
First, if you’re an AI novice, read this post to learn what AI is and the different terms you might hear to describe it. Then, come back to this post and follow the steps below.
1. Evaluate repetitive, manual marketing tasks that could be intelligently automated.
Consider how much time your marketing team spends on repetitive and administrative tasks, such as drafting social media updates, writing data-driven blog posts, personalizing emails and website copy, A/B testing landing pages, building lead nurturing workflows, developing advertising copy, managing paid media spend, conducting keyword research, finding insights in analytics and recommending strategies (to name a few).
Now, what if we told you every one of those tasks, and many more, could be done more efficiently using artificial intelligence technology that’s available today? There are 11 activities that we see as prime candidates for AI experimentation:
- Discover content ideas.
- Write content.
- Automate content at scale.
- Optimize content.
- Personalize content.
- Create ad copy.
- Manage digital ad campaigns.
- Test content.
- Draft and publish social media updates.
- Review analytics and write performance reports.
- Recommend strategies and allocate resources.
See this post for a full description of each use case listed above.
2. Assess opportunities to get more out of your data.
Artificial intelligence has an almost infinite ability to process data in ways that create tremendous value for firms. For instance, natural language generation (NLG) turns spreadsheet numbers into narratives. Image recognition systems use photo datasets to identify your pictures. Prediction engines weigh thousands of data points to predict what products or content you’ll love (and buy). These technologies all use different types and quantities of data in different ways to achieve diverse goals.
You’ll want to assess your data to determine where AI might be profitably used in your business. Start by asking yourself these questions:
A) Do you have data?
Some AI technologies can only be used if you have access to data, either generated by a third-party (like a CRM system) or generated in-house. If you don’t have access to data, you’ll need to rule out any solution (like natural language generation) that requires it.
B) What does your data look like?
Is your data structured or unstructured? Structured data is ordered data displayed in columns and rows. Unstructured data is any data that is not organized in a specific way, such as Word documents, social media posts and emails. Which type of data you have determines what AI technologies can benefit your organization.
C) What stories can you tell with your data?
If you create content, consider the stories your data might be able to tell. Natural language generation (NLG) is an artificial intelligence technology that turns structured data into narratives. NLG takes numbers and tells stories about them based on rules that humans create.
Once an NLG system is “trained” to understand your data, it automatically generates content—in some cases, thousands of articles—from your numbers. For example, the Associated Press uses the technology to write its earnings reports and brands use NLG to write narratives about their Google Analytics data.
If you have structured data, NLG might be a good fit for you. Start asking yourself: What stories can your brand tell with its data? What types of content would you like to create at scale? What relationships do your numbers describe that could make compelling narratives?
There are other questions you’ll want to ask too. Find all of them here.
3. Consider the AI capabilities of your existing marketing technology, and explore the potential of emerging AI solutions.
While we expect marketing automation companies to rapidly develop and integrate AI capabilities in the months and years ahead (through both acquisitions and internal R&D), for now, marketers need to piece together AI-powered products and integrate them into their core marketing technology stack.
If you use marketing automation and/or CRM software, speak with your provider to learn more about how they plan to integrate AI into their product offerings. We’ve profiled how Salesforce is baking AI into its entire product line. Other providers are doing the same.
Our profiles of AI solutions providers are also a great place to start learning more about what’s possible. See below for links to Spotlights on AI-powered technologies:
Phrasee: How to Write Marketing Copy With AI
- Pulsar AI: Discover How to Use AI for Automotive Marketing
- MarketMuse: How to Measure and Improve Content Quality Using AI
- Persado: This Marketing Tool Uses AI to Create Copy That Converts
- Mindsay: How to Use AI for Better Customer Experiences
- Cortex: Predict How Consumers Will React to Content Using Machine Learning
- MarketMuse: How to Measure and Improve Content Quality at Scale
- Scripted: Streamline the Content Marketing Process with Machine Learning
- Adgorithms: Optimize Your Multi-Channel Marketing Campaigns with an AI Platform
- Crayon: How to Spy on Your Competitors With AI
- Acrolinx: This Company Uses Artificial Intelligence to Improve Content for Facebook, IBM and Nestle
About Mike Kaput
Mike Kaput is Chief Content Officer at 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.