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Machine learning & data science for beginners and experts alike.
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There’s a Starbucks on every other corner in New York, but I still miss my favorite barista in Rome – nearly 20 years later. Every time the barista saw me, he would yell: “Espresso Doppio?” It was my morning ritual of choice 50% of the time. He didn’t just remember people’s orders, he would tailor his demeanor to each customer. To some, he would just say: “Buongiorno!” and get a cappuccino or a macchiato with a cornetto (an Italian-style croissant) going.
For others, he offered more choice - “Espresso? Macchiato? Cappuccino?” - giving the option to start the day with a simple nod or to explore alternatives by making new requests. He would effortlessly go from engaging in conversations (mostly about soccer) with the chattier patrons to nods and eyebrow movements with those who didn’t feel like talking in the morning. This customized treatment, and the good coffee, kept the café as full as a midtown subway car during rush hour. He had found the formula for building long-term customer loyalty by offering the right range of choices and messages to his customers, designing what behavioral scientists would call a personalized choice architecture.
Personalized choice architecture is a new field, aiming to predict and influence individuals’ choices. The traditional behavioral economics aim to nudge a generic persona in a population; machine learning can help to define personalized nudges. In a recent paper, “Nudge Me Right,” Eyal Pe'er et al provide evidence that persuasion messages can be customized to people's personality traits.
It looks like we heavily rely on the “way we are wired” for our most mundane activities. Daniel Kahneman’s Nobel prize-winning research on behavioral economics put the imperfect human at the center of a new economic theory. The human brain consumes 20% of the body’s energy processing information. To conserve, we have learned to rely on autopilot. Heuristics can be mental shortcuts that make us energy efficient when it comes to exercising rational thinking, he found. The modern information overload only reinforces this response: autopilot is now the physiological default option. By paying attention to people’s heuristics, habits and personality traits, one can customize and provide a choice architecture that enhances the experience.
Take the way TV choices are presented to us with streaming services. We are intimately familiar with the choice architecture, which is built on recommendations based on past viewership. And most of the time, we passively accept what’s on the menu. What if we were offered the option to cycle through a few architectures (classic film catalog, recommendation, channel guide)? What if DTC (Direct-To-Consumer) streaming services could personalize the choice architecture striking the right balance between Recommendation and Discovery experience? To take it a step farther, what if personalization meant to speak to someone’s personality? Imagine running the same promo with a text and voice overlay tailored to someone’s personality streaming on a tablet. Personality-based messages don’t necessarily mean narrow segments: you can cast a wide net, but automatically customize the message.
How will consumers deal with the increasingly crowded direct-to-consumer market? There may be a push to re-design the remote control as a smart device to navigate among the streaming apps. Replacing the traditional remotes with our smart phones may be an opportunity to offer a customized experience across DTC services.
But before getting to the remote control of the future, consumers will have to make some decisions. They’re already experiencing “subscription fatigue,” with 47% of the people surveyed in the Deloitte’s 13th edition of Digital Media Trends survey reporting frustration at being bombarded with so many options.
How those decisions will be made doesn’t necessarily rely on data analytics alone. A household may sign up for a service for offerings for kids, another household may find comfort in the option to watch their favorite Friends or Seinfeld episode once a year. For some viewers, the mere availability of classic sit-coms may be the tipping point when it will come to DTC selection, this is a data point that can’t be derived by viewership data alone. Understanding and codifying the human mind and personality traits will unlock the potential of a true personalized message and choice architecture that delivers superior customer experience. DTC provides a data-rich environment for decisions based on machine learning.
New practices are being developed called precision marketing or precision engagement, a discipline at the intersection of data science and behavioral science, stemming from Government and Life Science, now pioneered in the media and entertainment space. Chief Marketing and Research Officers are leveraging data science. Embedding behavioral science in their processes will yield a deeper understanding of their consumers and novel ways to cut through the clutter of modern information overload.
Leveraging an efficient, collaboration platform that can be easily used by ethnographers, designers, marketers, data scientists, creative teams and advertisers will be essential to understand audiences’ personality and build the right personalized choice architecture.