I’ve made my career as a technologist, inventor and AI (Artificial Intelligence) expert, fascinated by computers anticipating our whims – transforming our intent into better lives. Not only can brands access this AI, they should – it’s already impacting nearly every brand that sells things. One important idea that AI has made real – intent-based optimization – has implications for brands, people and Giants fans in particular.
In 1989, Dr. Philip R. Cohen, a brilliant computer scientist associated with DARPA, authored a paper titled 'Intention is Choice with Commitment'. It explored the balance between the beliefs, goals, actions and intentions of 'intelligent agents'. Cohen concluded that one agent’s intentions, in terms of beliefs about another agent’s intentions (or beliefs), could derive a preliminary account of interpersonal commitments.
Cohen’s ideas blew my young mind.
Here’s what it all means:
Machines, like people, can decide to do something else besides what they intended. Machines need to be able to reason about the plans that other machines have, but also about their commitment to those plans. If one finds out another has failed, the first should be able to predict when the other will try again. It should be able to reason the intentions and commitments of other machines rather than be required to simulate the other’s behaviors. This research was the first formal theory of intention for AI.
Fast-forward to today:
Based on market capitalization, Amazon has overtaken retail giant Walmart. Now we meet the new kid, Jet.com, going head-to-head with Amazon and hyper-focused on becoming the go-to ecommerce site for the best bargains online. Jet.com founder/CEO Marc Lore has a reputation for creating game-changing internet shopping destinations for niche groups, but targeting frugal shoppers is a challenge.
Jet guarantees consumers the lowest prices on the Web, but undercutting Amazon, from membership fees to final price, isn’t easy. Amazon has scale, relationships and massive inventory.
That’s why Jet designed its back-end to work more like a trading system than a traditional ecommerce site. What does this actually mean, and what’s the secret? Consumer intent, which plays a major factor in pushing prices down.
This brings us to intent-based optimization: the idea that brands deliver an optimal online shopping experience that drives sales – resulting in customers feeling they’re being spoken to directly because the message is relevant. Intent becomes vital because it enables emerging players like Jet to connect with consumers more efficiently and intelligently, leading to a differentiated shopping experience and more perceived value beyond price and delivery time.
Understanding a consumer’s intent and in-the-moment thoughts lets brands and advertisers deliver recommendations that convert potential customers more efficiently. Coupling psychographic and demographic information (who) with time of day (when), content a person engages with (where), their specific interest on that page (what/why), and whether they’re on a mobile or desktop platform (how), provides a keen opportunity to discern their intentions.
Say someone buys a New York Giants jersey. It makes no sense to retarget them with an ad featuring that same Giants jersey, but it happens. You’d rather look at their path (who, what, when, where, why, how this fan is navigating and consuming content online), to discern their intent and anticipate a need.
Let’s say an AI knows the fan bought the jersey and purchased tickets to the next Giants home game in the same browsing session. An ad for tailgating supplies makes more sense, leading to a relevant offer with dramatically increased sales. By focusing customer intent, and only engaging through highly relevant options tailored to anticipated interests, we get significantly higher performance.
Jet updates its prices in real-time, based on available inventory, shipping costs and what’s currently in a customer’s shopping cart. By analyzing keyword searches, specific page visits and content downloads a consumer makes across the internet, brands can identify intent and additional related products and services the customer may want.
Another company using intent-based optimization, Yieldbot, uses advertising AI to match ads to a consumer’s mindset, pulling intent data from publishers’ pages (what users are reading, where they came from and go afterward) to deliver relevant ads displayed at the right time.
Google had $17.7 billion in revenue in Q2 almost entirely from search – proving how powerful intent data can be. In about 50 milliseconds it can crawl the internet and return not with just content, but with relevant ads based on search histories. GoogleNow technology expands on this by shifting from a responsive to a predictive system based on location, time of day and app usage.
Other than closing a sale, there are few things more valuable than understanding a potential customer’s intent. In Jet’s case, intent is the fuel energizing the disruption of an e-commerce (wait for it) giant.
Staying ahead is about understanding what data matters the most and when. Data-driven targeting has evolved to encompass the entire digital services landscape. From mobile to virtual reality, they are all pieces of today’s consumer puzzle. Tracking behaviors and understanding context to optimize intent is the only way forward. And nearly 30 years after Cohen’s landmark paper, the marketing technology stack has caught up to the theory of intent.
Jason Alan Snyder is chief technology officer at Momentum Worldwide. He tweets @evil_robot