Data

Markets of one: After years of hyperbole, mass customization is finally within our grasp

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We are, all of us, sitting on a gold mine. For the last three decades or so, we have been collecting a treasure trove of digital information on everything from changing weather patterns to the spread of infectious diseases. We have digitized the history of the world’s literature. We track and store the movements of automobiles, trains, planes and mobile phones. And we are privy to the raw, real-time sentiments of billions of people through social media.

Individually, each of these digital resources has been immensely useful, applied to solving specific problems in dozens of industries. But collectively, when integrated, cross-referenced, and analyzed, this body of information represents the most powerful natural resource the world has ever known. And it is growing at a rate of 2.5 billion gigabytes every day.

It is not unreasonable to expect that within this untamed corpus of data lay the secrets to defeating cancer, reversing climate change, or managing the complexity of the global economy. But until recently, we have not had the means to mine this resource properly. It was too big, too messy, and too disparate.

Today, all of that is changing. For the first time since the digital revolution began in earnest, the tools we use to process and analyze data are catching up to the tools we use to produce it. Some call it artificial intelligence. Others call it cognitive computing. Whatever the name, the potential to quickly and purposefully analyze the world’s information and put it to use is suddenly available to us. Using machines that learn, reason, and understand, we can transform vast amounts of complex, ambiguous information into insight, including things that don’t fit neatly into databases or spreadsheets: images, video, text and sound.

This capability holds profound implications for nearly every company in every industry. But for those of us in the marketing profession, it brings us ever closer to reaching a long-sought-after goal: markets of one.

It’s easy to misunderstand or underestimate the implications of this concept. In part that’s because we’ve been promised this capability for years, but all we’ve gotten is incrementally smaller market segments. Now we’re finally in a position to literally tailor millions of customer relationships to each individual, from the way their products and services are designed and delivered to the way their customer service requests are addressed.

I believe the impact of this capability will go far beyond improvements in marketing efficiency and customer satisfaction. While those are worthy pursuits, they are just the beginning. In our lifetimes, we could be seeing the disintegration of mass markets, the death of one-size-fits-all, and a redefining of economies of scale. It’s actually already happening.

In February 2011, the world was introduced to Watson, IBM’s cognitive computing system that defeated Ken Jennings and Brad Rutter at Jeopardy! It was the first widely seen demonstration of cognitive computing, and it marked the end of the so-called AI winter. The pace at which this technology has progressed since then is breathtaking.

My agency, Havas Worldwide, works closely with IBM’s Watson team. We help with their digital marketing efforts, of course. But we also employ Watson as a resource in our other client accounts. I have been in a constant state of awe for the last 18 months as I’ve watched the technology develop and the capabilities unfold. But the future of my profession started to come into clearer focus recently when IBM announced a new partnership with Sesame Street, in which Watson will be crafting individualized curricula for early childhood learning.

This is the customizing of educational programs to fit child’s skill level and learning style. Those of us who have fretted over the class sizes at our children’s schools understand what this means: classes of one. More than that, Watson is not limited to what has been tried before. It has no preconceived notions about the best way to teach. It has no biases. It can try out entirely new combinations, and adapt its content to each person that’s using it.

I’ve watched as Watson has analyzed the genetic makeup of a cancer tumor and searched thousands of medical journals to identify the treatment options with the best chance of success. And I’ve seen it analyze the sum total of the world’s cookbooks to design unprecedented – and delicious – new dishes: Peruvian potato poutine; Belgian bacon pudding; Vietnamese apple kabob.

What happens when that same capability is applied to marketing? Or advertising? Or investing? We are currently working with a financial services client that is using artificial intelligence to gauge each investor’s risk tolerance, financial sophistication, and the clarity of their goals. It doesn’t do this by asking them to fill out surveys (which we know are inaccurate and rife with bias) or have a conversation with an investment advisor (which doesn’t scale.) It assesses the investor by having a natural language conversation, chatting about sports, food, and money. And it then offers unique investment advice based on the results.

We’re applying similar technology to improve the customer call center experience for major telecommunications companies. Using a combination of self-service solutions, in which customers use natural language to query the system and find fast answers, and agent assist solutions, in which call center agents use artificial intelligence to resolve complex customer issues, we can finally scale competency in the call center; a problem that has plagued thousands of companies for decades.

And on a more whimsical note, we worked with a shoemaker that wanted to recommend products to customers in a more personal way. Using a cognitive computing app, they are analyzing customers’ social media posts on Facebook and Instagram to get a sense of their customers’ personalities. Based on that profile, the product feed is customized to that individual.

The fundamental building blocks of this future are in place: broadband, data centers, cloud, analytics, and IoT. They are the drivers of modern day insight. And together they will yield a new understanding of the complex systems that facilitate life on this planet and drive the majority of economic development.

As a marketer, I’m excited about the prospects of mass customization. But as a global citizen, I’m even more excited about the potential to mine the world’s greatest natural resource – its data – for centuries to come.

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