Poets, philosophers and scientists have spent generations exploring the question of what makes humans, human.
Laughter? Love? The inclination to text and drive?
For the artistic and scientific, the basic question provides the inspiration for works of great beauty and deep analysis. But today, the question, in a slightly more crass form, has been taken up by marketers — marketers who are not as much interested in the universal answer as they are in the individual answer.
Marketers in the age of digital transformation want to know what makes that particular human, human. And more importantly what makes that particular human tick? It is a question at the root of developing real-time, one-to-one personalization.
In my search for answers, I bypassed the poets and philosophers. I politely sidestepped the marketers and turned to the scientists, in particular a data scientist. Amit Aggarwal is BloomReach’s chief technology officer and a guy who has thought a lot about personalization and its relationship with human intent and human nature.
Aggarwal naturally has a deep technical understanding of the algorithms and data streams that make authentic personalization a real thing. But he indulged me, taking a broader view of personalization and breaking it down into its vital components:
- Semantic language understanding
- Contextual understanding
- User behavior understanding
- Product understanding
Aggarwal had compelling arguments for each. Me? I was fixated on coming up with the most important element of personalization. Aggarwal wasn’t biting. The world isn’t simple. Multi-faceted problems aren’t solved with one solution. Complicated challenges aren’t met with simple solutions. A data scientist knows this.
And the greatest of these is language
A writer does not. And so among the fearsome foursome of personalization, I decided the greatest of these is language. Imagine, a writer choosing language as the key to success. But hear me out. Nothing is more human that language. It sets us apart from the other animals.
It is the basis for all we do. Grand ideas are nothing without a way to express them. Love goes unnoticed if it’s not expressed. The next big thing falls silently in the forest if no one can describe it.
And so, a compromise: I’ll respect Aggarwal’s superior understanding of personalization by presenting all four basic elements of true personalization. But I’ll start with my favorite — language.
First, however, why this whole “what is personalization” exercise in the first place? Because personalization, as a term, needs some refinement. It has become a buzz phrase to mean whatever the one uttering it wants it to mean.
I look at personalization as the ability to understand a consumer on an individual basis; the ability to understand a consumer’s intent in the moment, and the corollary ability to provide that consumer with relevant and personal content as a result.
And that brings us back to Aggarwal’s four elements, starting, naturally, with language.
Semantic language understanding: True personalization begins with a deep understanding of what digital users are saying. One of the deepest human needs is to be understood. And that understanding is achieved through language. Not just words, but language. Language comes with sentiment and context. Language changes. “That’s sick,” meant one thing in 1950. It meant something entirely different in 2000.
The future of personalization
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There is no personalization without language. Language is different from words. Plenty of technologies can understand words. You type in a search query and the machine looks for product descriptions, for instance, that contain those words.
Language is more than that. Language is living and ever-changing. Different digital consumers use words differently. In a sense we all speak our own language. Not only does a real personalization system need to acknowledge that fact, it needs to constantly learn to better understand what language means and what consumers mean by the language they use.
Language includes synonyms, different words that mean the same or similar things. True personalization understands that the user searching for a “camel pocketbook” and the user searching for a “tan purse” might be interested in the same product or the same story about a fashion trend.
Contextual understanding: But when a user says or types “tan purse,” how does a personalization system understand whether the user is searching for a product or a fashion story or even instructions on how to make a tan purse or advice on what colors go best with a tan purse? The system needs to understand context. It needs to understand what a digital user hopes to accomplish.
Is she seeking inspiration? I she researching a product or subject after being inspired? Is she already sure of a product she wants to buy and hunting for the seller with the best price or fastest or most convenient delivery options? Has she already bought a tan purse and is looking for care instructions or whether she can return the purse for a different color or style?
True personalization understands context and constantly learns from interactions with millions of users. It understands that someone in Northern California searching for “water shoes” in the summertime is not likely to be looking for footwear designed for a rainy day. Instead, it’s quite likely that person is searching for footwear meant for the beach and for wading into the water.
User behavior understanding: One part of grasping context is understanding using behavior and what a user’s digital activity and the activity of users across the web tells us about their intent. Here, true personalization parallels the work of a high-quality store associate.
When you walk into a home-improvement store, the human associates who work there can learn a lot about you. Yes, they learn from what you say to them. But they can begin building their understanding before a customer even opens his or her mouth. What aisles and products do you pause in front of? Do you browse one aisle and then head to another with products that might be used in the same DIY project?
Do you examine the top-of-the-line variable speed drill and then put it back and reach for a serviceable model that costs less? Do you stride through the store with a certain confidence? Or do you look a little lost, eyeing the 1-inch, 90-degree PVC elbow segment like it’s something an Apollo crew brought back from the moon?
A perceptive associate, which granted is sometimes hard to find, knows a lot about you already. Or at least he or she knows a lot about you and your intent on this particular shopping trip.
A constantly learning machine that deeply understands language can draw some similar conclusions from online behavior. Moreover, understanding not just what words mean, but how they relate to other words and what their connotations are in different circumstances, means that an artificial-intelligence-driven system can serve up recommendations that are relevant to one, single individual.
Product understanding: Deeply understanding a user’s language and behavior and the context in the moment is a start to providing true personalization. But it isn’t enough. A true personalization system needs to understand what a user is in the market for. Is someone who’s shown an interest in financial products looking for a home loan or a credit card? Is the user who’s shown an intent to learn more about insurance, looking for life insurance or homeowner’s insurance?
A true personalization system must deeply understand content in order to properly match a consumer’s intent with the available content. There is no deep user understanding without a deep understanding of the content they are seeking.
Consumers are the ones defining personalization
What’s crystal clear is that in today’s world, it’s consumers who are deciding what “personalization” means.
And so it’s only right that enterprises listen to consumers and provide what it is their customers are demanding. Not only is it the right thing to do, it’s also the profitable thing to do. It’s clear that the ability to understand language will only become more important for enterprises as the era of digital transformation rages on.
Total Retail Report found that commerce sites that based their site search on keyword search, returning only recommendations that included the keywords, suffered a 40 percent abandonment rate. Sites that rely on semantic understanding experienced only a 2 percent abandonment rate, Total Retail Report said.
A few other statistics help explain why digital consumers can become so frustrated. Google has said that 15 percent of the search queries it receives on any given day are queries that the search engine has never seen before. It’s reasonable to imagine that individual sites are subject to the same sort of effect, meaning the site needs to be smart enough to understand the meaning of what a searcher is saying.
For in the end, we are individuals who celebrate our own individuality in what we believe, how we dress, whom we associate with, where we work and yes, how we talk. In English alone there are more than 1,000 ways to say something is beautiful and more than 1,500 ways to say “happy.”
No doubt we will continue to find new ways to express ourselves, whether we’re talking about beauty, happiness or buying a new pair of shoes. It will be up to those building digital experiences to keep that in mind as they design better ways to keep up.
Photo of books by Jackie Finn-Irwin published under Creative Commons license.
Mike Cassidy is BloomReach’s storyteller. Contact him at email@example.com; follow him on Twitter at @mikecassidy.