Why You Shouldn’t Use Black Box AI for Personalization

By Éric St-Jean

March 1, 2018

As a marketer, you’re hearing about artificial intelligence (AI) everywhere now, and everyone claims some form of AI capability in their product, especially in the field of personalization. And for good reason: AI algorithms can churn through incredible amounts of data about your customers, their behavior, and your business, and determine the best course of action at a scale humans cannot. This is just plain cool.

As a marketer, AI personalization is a fantastic help, as long as it works.

  • But how do you know what works and what doesn’t?
  • How does this help you strategize with the rest of your business?
  • How do you explain the results you’re seeing?

The problem with so many of those AI products is that they are a “black box.” You can’t see how the AI works anywhere in the system, which means you not only don’t know how it works, you also don’t get the insight you need from it to iterate on your programs and inform your strategy. These tools are presented as fancy business automation: no need to check on experience performance multiple times a day since there is a lower risk of taking chances, etc. because “it will adjust itself”. Which may be true, but it’s still a black box.

Bias in Black Box AI Technology

According to the article in MIT Technology Review, Biased Algorithms Are Everywhere and No One Seems  to Care, there are inherent biases in black box technology. Monetate believes that black box technology is a barrier to the adoption of AI and is committed to providing a level of transparency not seen in other personalization platforms.

In 2016 when Monetate began building our Majority Fit (MFE) and Individual Fit Experiences (IFE) capabilities, our AI-powered testing and 1:1 personalizationengines, we knew we needed to build something different. Our clients had explained their hesitance to adopt AI and we felt really strongly that, just like the rest of our platform, we didn’t want to simply build automation machines. So we built our AI to ensure that we built technology that will earn a central place, not only in your technology stack, but in your personalization strategy.

MFE and IFE were introduced accompanied by rich real-time analytics, letting you peek into how our algorithms are performing. And you can see our AI laid out simply in our platform’s user interface. These features gave our customers the comfort with the AI that they needed. Customers using the IFE capabilities of the Monetate Intelligent Personalization Engine have the benefit of understanding how the individualized decisions are being reached. And, as a result, we’ve seen the usage skyrocket! But we knew we could do even more.

And we did! We’ve recently released Individual Fit Insights. Our IFE Insights breaks the whole box open. Wide open. And you’ll have to excuse me for getting geeked out over it.

AI Personalization Improves the Customer Experience

While MFE and IFE leaped over and ahead of AI products that are mostly automations of existing experimentation and personalization processes, our Individual FIt Insights leaps ahead of automated segmentation. It’s a window into complex processes that provides the information marketers need to inform the next experience while also providing insight into the customers, and what makes them tick.

Specifically, the insights surface the most influential data categories used in individual decisions and aggregates these insights at the experience level. With this information, marketers learn which experience variants resonate with which audiences, surfacing directional insight into how to think about their audiences with additional insights on how to develop experiences that resonate with them. Marketers can use this to confirm or challenge any hypothesis about shoppers, so their brands can make the best decisions going forward.

As VP of Solutions Engineering at Monetate, I see and understand the full complexity of the technology environment of brands. And I feel incredibly proud when Monetate brings to market real solutions to real problems for our customers. We want you to meaningfully change the experience of your customers as they interact with your brand and we want to give you both the tools and unrivaled customer intelligence to do it. 

If you would like to learn more about how Monetate can drive your AI personalization strategy further, contact us today.

As the VP of Solutions Engineering, at Monetate, Éric St-Jean oversees a group of engineers who customize our platform, implement advanced use cases and connect it to other systems for our larger clients.

Prior to joining Monetate, Éric has held multiple leadership positions in the last 11 years and has been working on software for 18 years, 11 of which working on SaaS products. Éric holds a Bachelor's degree in Aerospace Engineering from Carleton University and a Master's degree in Engineering from École Polytechnique de Montréal.

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