“Growth is painful. Change is painful. But nothing is as painful as staying stuck somewhere you don’t belong.”
— Mandy Hale
When I started my company in 2010, my central thesis was that personalized experiences would replace the “one size fits all” digital experience. From a marketing perspective, it wasn’t that companies couldn’t figure out who you were or the experience that would be most pleasing to you. The gating factor was that they couldn’t get the right unit of content in front of you quickly enough to make a difference. Turns out that the trend I spotted was and is still true today. While platforms have evolved to tackle some of these issues, there are still technology, strategy, and process gaps that we need to overcome.
I’ve been clearing my calendar to think about the next decade of work. I thought I’d share the questions I’ve been exploring.
The Mathematics of Experience
Mathematics continues to evolve at an accelerating pace. Our ability to write equations that describe our world and our experience is developing rapidly. How should we be applying advancements in mathematics to business?
If I wanted to write an equation that would describe the relative likelihood that I’d visit a Starbucks at 4:30 tomorrow afternoon, what would that look like? What mathematical domains would be necessary to build a reliable model?
What is the relationship between brand affinity and proximity? You might walk two blocks at lunch for your favorite sandwich, but six blocks would be too far. Is there a level of discounting or incentivization that would impact your behavior to walk those additional four blocks? Ronny Chieng does a routine on Amazon Prime becoming “Prime Now.” Two-hour delivery is no longer sufficient; it needs to be Prime NOW. It’s funny, but there is truth in our growing expectation that companies anticipate our needs. How do we help our clients write equations that anticipate what someone will want now?
Machine Learning and the Customer Experience
Given the advancements in mathematics, how are we going to use machine learning and artificial intelligence to improve the customer experience? The wonderful thing about digital experiences is that they’ve given us sample sizes that are statistically valid. There are millions and millions of digital interactions to measure. When we move from statistically based personalization models to algorithmically based ones, how will that impact personalization? What level of uplift will we get from a marketing and customer service perspective?
What new technologies do we need to master to lead the market in these categories? How will our engineering rigor need to change when the building of the enterprise marketing platform is only the first step in the experiment?
A Grand Unified Theory of Content
We are still in need of a grand unified theory of content. We have good tools for searchability (thank you, Google) and findability, which is a byproduct of standardizing UX, but that’s not sufficient. In spite of all the improvements, consumers are still left with the task of finding and navigating content. We still aren’t able to describe content in terms that allow computers and AI to understand it well enough to build effective algorithms for personalization.
I’ve experimented with using the discipline of semiotics to codify content. Certainly DITA, XML, S1000D, and mapping ontologies are all helpful, but we need to bring all of this together into a unified framework for describing content. I don’t have this all figured out, but I sense there is a path that will combine all of these standards into a game-changing solution.
Complexity Theory and Business
This leads to the next set of questions, which involve complexity theory. A complex system is composed of many diverse parts that are highly interconnected and capable of adaptation. If you think about how a brand interacts with its customers on a global scale, you have a complex system. When you think about a company with many different disciplines all working toward a common goal, you have a complex system.
How do we help clients understand the complexity of their customer engagement? How would we visualize that? How would we understand the interactions well enough to make recommendations that positively impact business outcomes?
I recently connected with Kirell Benzi, who creates art by visualizing complex systems and data sets. For those interested in complexity theory, the Santa Fe Institute is a remarkable resource. One of the most important questions for the next decade: how do we build teams comprised of diverse skill sets that effectively collaborate to serve clients?
AI Will Change Everything
AI will be a couple of orders of magnitude more impactful than the advent of the Internet. Imagine how much the world has changed because of the Internet, then multiply the amount of change in the last 25 years by 100. That is what AI is going to bring to our world. We won’t experience a linear progression of change. There will be quantum leaps in technology and understanding. The advancements in science, knowledge, and technology will be astounding beyond belief.
This will create cultural and economic disruption on a scale not seen before in human history. To put this in perspective, it took the Catholic Church about 200 years to come to terms with Galileo’s notion that the earth revolves around the sun. We won’t have that luxury of time.
The Crisis of Belief
Beliefs are our brain’s way of making sense of and navigating our complex world. They are mental representations of the ways our brain expects things in our environment to behave, and how things should be related to each other. Beliefs are templates for efficient learning and are often essential for survival.
What happens when long-standing belief systems are eliminated or proven wrong, virtually overnight? We won’t have 200 years to come to terms with the change in knowledge or perspective. How would we need to teach differently if accepted truths and norms are regularly in jeopardy? What long-standing principles are likely to be challenged in the next decade?
If capitalism is based on a risk-reward relationship, what happens when the risk is virtually eliminated by computing power? That’s not to say that randomness goes away, just that the calculation of risk will be almost perfect. How do you invest your money in a world where the rate of return is already a certainty? What does that mean for capitalism, and will we need to invent a new economic model? All the people who owned big castles in Europe during the Middle Ages thought they would be the dominant economic model for the foreseeable future. Now they are places to visit on vacations.
Or look at healthcare. What happens when life expectancy skyrockets because we apply virtually unlimited computing power to monitoring your health? What would it mean for our economy if average life expectancy doubles in the next 20 years? What does that mean for managing resources and population? If you think that’s not a possibility, start reading and talking to scientists who are at the forefront of this revolution.
The Governance Question
All of us can see how social media is affecting our democracy. Do the basic concepts of freedom of speech apply to machines and computers too? It won’t be long before computers generate more content than human beings. What laws and rules do we need to govern that scenario? How should we think about government, the rule of law, and self?
There is a great quote by Carl Sagan, written in 1995:
“Science is more than a body of knowledge; it is a way of thinking. I have a foreboding of an America in my children’s or grandchildren’s time, when the United States is a service and information economy; when nearly all the key manufacturing industries have slipped away to other countries; when awesome technological powers are in the hands of a very few, and no one representing the public interest can even grasp the issues; when the people have lost the ability to set their own agendas or knowledgeably question those in authority; when, clutching our crystals and nervously consulting our horoscopes, our critical faculties in decline, unable to distinguish between what feels good and what’s true, we slide, almost without noticing, back into superstition and darkness.”
Eerily familiar given the world today. That can’t be the end state, so what happens next?
What Comes Next
We are seeing the beginning of cultural change at an unprecedented scale. I say all the time that we exist to make millions of people a little bit happier every day. We’ve got the ambition and a company of smart and happy people that are and will continue to make a difference.
I am working on these questions and I invite your input and perspective. The work we do is important, and we need to make sure that our thesis for the next decade is a guiding light.
I am certainly not done thinking about what comes next. I am focused on considering and contemplating what the future holds so we can anchor ourselves to the prospect of creating a better world. While at times I am daunted by what comes next, I am also an optimist and I have an unshakeable vision for a greater and more fulfilling world. It’s up to each of us to make a difference.
Let’s go be great.