While everyone has heard of artificial intelligence and machine learning, not everyone understands how these technologies work and how they support successful marketing. In this blog post, we’ll demystify these technologies and outline four important ways they can help you better know your customers and enhance revenues/ROI.
AI and ML, demystified
The type of artificial intelligence now commonly in use (called “narrow” AI) is a computer program humans teach to do one particular task, like identifying spam email, monitoring customer behaviors, or routing drivers through rush-hour traffic. AI is built upon data: you take data about the past, analyze it, and make predictions about the future.
AI is most effectively used in situations where historical patterns uncovered in the data are predictive of future actions. Machine learning/ML is a field within AI that uses statistical techniques to give computer systems the ability to "learn,” to progressively improve performance on a specific task, without the need for explicit programming (the data itself does the “programming”).
4 ways AI and ML are changing the marketing game
Here are four ways that AI and ML can help your marketing efforts. They are in no way exhaustive but are intended to offer you an idea of what’s possible with this emerging martech:
1. AI can create highly-personalized customer experiences, the kind your customers increasingly demand. As you collect data about what your customers do (and where they go), AI allows you to understand the behavioral factors that drive your customers’ behaviors. With this “actionable intelligence,” you can then send just the right message to the right customer at the right time, leveraging AI. In the same way that Pandora uses machine learning to suggest songs to listeners (based on prior listens), you can use marketing technology to send the right content to the right
customer at the right time.
2. AI can better engage customers. No marketing team has enough members to engage all your customers all the time, but AI and machine learning can be used for customer segmentation, allowing you to send them more personalized messaging resolving their particular issues. Through combining “human + tech,” you can have chatbots perform simpler levels of engagement and then escalate more complex engagement tasks to your human marketers, optimizing efficiency and ROI.
3. Predictive analytics to promote customer retention. Every marketer knows that focusing on turning customers into repeat buyers can positively impact your bottom line. AI and ML can be used to identify patterns among those customers who are most likely to “leak out” of your funnel before they convert. By understanding why they leave, you can take proactive/anticipatory action to keep them within your funnel until ROI and beyond. This is what “retention marketing” is all about. When you keep your customers, you also grow your business.
4. Actionable insights for better performance. In the past, marketers were often blind to the customer’s journey. When might a customer purchase, and why then? These key questions matter for speculation and “gut” thinking. Now, we have data about every step of the customer journey. We can leverage that data to understand our customers and develop actionable insights that inform what we do. Data, the “oil” fueling AI and ML, simply gives us more visibility into the entire customer experience. In the end, AI allows us to market at scales not humanly possible before.
Chuck Leddy is a Zylotech contributing writer.
If you liked this post, check out our other blog post on open source libraries and tools data scientists in marketing should check out.