We are in the midst of transformation. More and more, today’s customers expect seamless, personalized, predictive journeys. Today, 64% of customers now expect tailored engagement based on past interactions, and 62% of customers expect companies to adapt based on their actions and behavior. Artificial Intelligence (AI) is playing a major factor in this transformation — and the secret to delivering personalization at scale.

How can marketers make the most of their data and AI to deliver the personalized experiences customers now expect? In his presentation at Connections '19, Ray Wang, Founder and Principal Analyst at Constellation Research, outlined some steps you can take:

  1. Understand how your metrics and AI drive personalization. 
  2. Measure meaningful metrics you can act on.
  3. Use your metrics and AI to guide customers to take action.
 

1. Understand how your metrics and AI drive personalization

To many people, AI and machine learning are highly complicated, futuristic technologies. It’s true that increasingly complex algorithms power them, but the basic principle is simple enough to understand. AI and machine learning take inputs (your data), identify trends, apply them to a journey, and guide that journey to a next-best action. 

Here’s an example of this in the real world. A coffee company tracks what beverages customers tend to purchase during different kinds of weather. Through AI, the company learns that when the temperature outside reaches a certain point — say 83ºF — people are more likely to opt for an iced beverage over a hot one. The coffee company can use that insight to push out offers for iced drinks when the temperature is nearing that 83ºF threshold. AI powers all of this. 

In the end, your AI is only as smart as the data you feed it. This is why the data you track is so important. 

 

2. Measure meaningful metrics you can act on

“Ok, that makes sense,” you may be thinking, “but how can marketers make sure they’re capturing ‘smart’ data?” 

The first thing to remember when considering what metrics to measure is to always have ROI in the back of your mind. As Wang pointed out, 77% of marketers seek ROI, yet lack the data to show it. This is because many marketers don’t differentiate between meaningful metrics and vanity metrics. Vanity metrics — like page views, social media likes, and keyword rankings — can make for a nice presentation, but without connecting them to cost or revenue, it’s impossible to tell if they have any impact on your actual business goals. 

For example, if your high-level goal is to increase traffic to your website, measuring conversion rate is more meaningful to ROI than measuring page views. This also helps to inform your AI what campaigns, tactics, and channels work best — not just for driving traffic to your website, but for driving traffic that converts.

Meaningful metrics — like conversion rates, qualified leads, and customer lifetime value — reveal how impactful your marketing efforts and AI are in helping you reduce your costs and grow revenue.

 

Here are some tips to keep you on track:

  • Always keep ROI in mind. Meaningful metrics tie back to cost and revenue. 
  • Avoid putting too much stake into vanity metrics. You can identify a vanity metric by asking:
    • Is it actionable? (No) 
    • Can it be manipulated? (Yes) 
    • Can I tie it directly back to ROI? (No)
  • Focus on actionable data like conversions, qualified leads, and customer lifetime value.
 

3. Use your metrics and AI to guide customers to take action

The power of AI — and the metrics that inform it — lies in its ability to apply that data to personalized customer journeys. From there, you can consistently guide customers to the next-best action.

This starts by making sure your data is useful. With a seemingly unlimited number of tools on the market, marketers should take care to choose tools that work together. Consolidating the tools you use makes your data more manageable, so your AI can use it to identify insights. 

With your tools and data in place, you can deliver personalization at scale. This is where AI comes into play. AI can help you build a 360º view of who your customer is, what makes them tick — including where they are, what they need, and what motivates them.

Based on the actions they take (again, this is why tracking the right metrics is so important), AI can identify trends and insights you can use to build prescribed journeys that anticipate a customer’s next-best action and automatically serve them the most relevant content or call to action. 

 

Here are some steps you should take:

  • Consolidate your tools. Make sure you choose tools that communicate and work together as a single platform. 
  • Gain insights from AI. Use AI to identify insights about your customers and find common trends in how they interact with your campaigns. 
  • Serve customers prescribed journeys. Based on the insights you gain, build predictive customer journeys. Using AI, you can then automatically determine the right time to serve the right campaign to the right customer. 

Using AI to drive personalized customer experiences in this way helps you unlock the power of your data, show ROI, and maximize your marketing budget. In an era when customers care as much about the experience a company offers as the products it sells, AI-driven personalization will only become more important to delivering on your customer’s expectations. 

Interested in learning more? Check out How to Use AI in Marketing: 3 Ways to Improve Your Customer Journeys.