If workers leave bosses instead of jobs, then customers arguably leave bad experiences rather than brands. But artificial intelligence from Contentsquare is sticking its automated finger in the mess, the hope being that you'll have a better, more consistent way to tell just how happy your customers actually are.

The flaws that blatantly show

Right now, the big problem with other satisfaction metrics is that contextual factors--for example, seasonal promotions or product launches--can create biases among buyers. Traditional methods of measuring happiness typically don't block out this "noise", so companies can get a really misleading picture of what or how to improve.

Individual metrics have their own problems, too.

For example, people can be vague in surveys, and those can include just a subset of your customers.

And while typical analytics can tell you facts like how much revenue or visitation your site has, they don't show you how engaged or frustrated people are with specific site elements. They don't let you see the bulk of behavior that happens between clicks, either, which can leave you clueless about why vistors are (or aren't) happy.

"Customer satisfaction is supreme," says Akin Arikan, Director of Product Marketing Strategy for Contentsquare, "but we should not lose sight of how you get an unbiased and benchmarked assessment of customer satisfaction. And how do you make it actionable, so you can operationalize/prioritize the right action?"

So Contentsquare's AI looks at behavioral data, such as mouse movement and finger taps, to be more objective.

Five dimensions, one happiness score

The AI looks at five dimensions to determine customer happiness:

  • Flawless: Is the experience free of technical glitches (e.g., page loads times)?
  • Engaged: Are customers interacting well with the content (e.g, hovers, click ratios, etc.)?
  • Sticky: Are visitors loyal? Do they come back to the site a lot?
  • Intuitive: How simple and understandable is the navigation? Does it make it simple to enjoy a complete, frustration-free experience (e.g., not having to hit the back button a bunch of times)?
  • Empowered: Can buyers avoid feeling lost (e.g, going in loops between search and products) and find the products and services right for them?

Then, the AI pulls all the data together to give you a final Digital Happiness Index (DHI).

"If your DHI is lower than average, you look at the five dimensions to see why," explains Arikan. "If, for example, journeys are not intuitive and customers aren't empowered to find the right content or products for them, you prioritize action there."

Other journey and content zone insights can help you narrow down exactly what to improve so you can make real changes.

Not just for your specialists

Arikan stresses that the AI (and the Contentsquare platform in general) is designed with the idea of enabling everybody on your team.

"Ensuring your customers' digital happiness is too important to be the job of only analysts or the customer feedback management team--everyone should be able to improve customer satisfaction."

With that attitude behind the AI, the tool seems to be getting results across all five of the DHI dimensions. Fashion company Moss Bros, for example, focused on improving empowerment and intuitiveness. They redesigned their site so that customers could get reviews (and the reassurance they needed to make a purchase) without having to scroll to the bottom of the page. Mobile sales shot up 13 percent.

Better, but not perfect

Of course, a big consideration is the five DHI dimensions themselves. Leaders consider these to be good areas to investigate when it comes to performance, but there is inherent bias in selecting these areas in the first place. It might be that considering other or more dimensions could paint an even more useful portrait of customer happiness.

And factors like culture or demographics need to be in mind in final analysis of the score, too. The behavior of a shopper in their 80s who doesn't get online every day, for instance, likely is going to be very different than the behavior of a tech-breathing teen.

But ultimately, the tool (or others like it) might mean that leaders consciously start focusing much less on what customers say and more on what they do. This doesn't mean they aren't listening one-on-one or that real conversations aren't necessary. It simply means that the way they are listening is different.

As for what that will do to the perception of authenticity, availability and overall business-customer relationship, we'll have to wait and see.