Marketing segmentation is a critical aspect of any successful marketing strategy. It involves dividing a market into smaller groups of consumers with similar needs or characteristics, in order to target them more effectively. However, it seems that some companies and marketers are failing to fully understand the importance of proper segmentation, and instead are relying on their own flawed assumptions and biases.
One of the biggest culprits of this failure is the Dunning-Kruger effect. This cognitive bias, named after David Dunning and Justin Kruger, is when people with low ability in a particular task overestimate their ability. This can lead to marketers overestimating their understanding of consumer behavior and making costly errors in their marketing strategies.
It’s absolutely unacceptable that companies and marketers are not taking the time to truly understand their target audience and segment them properly. Instead, they are relying on stereotypes and assumptions, and then wonder why their campaigns aren’t resonating with consumers. This is not only lazy, but it’s also a disservice to the consumers themselves, who are not being properly understood or served.
Furthermore, it’s not just the Dunning-Kruger effect that is causing these marketing errors. Companies are also failing to conduct proper market research, which is crucial to gaining a deeper understanding of target audiences and their needs. Without this research, companies are shooting in the dark and hoping for the best. Part of that research is doing the testing that is needed, to know not just that they can identify a segment but that they can actually change their behavior. Failing to do so just leaves groups targeting meaningless distinctions that provide no value to user or company.
It’s time for companies and marketers to wake up and take segmentation seriously. It’s not just about dividing the market into groups, it’s about truly understanding the needs and wants of those groups and tailoring strategies to effectively reach and engage them. And if companies and marketers don’t have the expertise or knowledge to do this, then it’s time to bring in experts who do.
In short, enough with the excuses and the relying on flawed assumptions and biases, it’s time to put in the work and do segmentation right. Consumers deserve better and companies will ultimately benefit from it.
Bandit based yield theory is a branch of economics that deals with the problem of how to optimally allocate resources when there is uncertainty about the returns on different investments. The term “bandit” refers to the fact that there is an element of risk involved in these investments, as there is a chance that the returns will be lower than expected or that the investment will fail entirely.
At its core, bandit based yield theory is concerned with finding the optimal balance between exploration and exploitation. Exploration refers to the process of trying out new investments or strategies in order to learn more about their potential returns. Exploitation, on the other hand, involves sticking with what has been proven to be successful in the past and maximizing the returns from those investments.
The problem with exploration is that it can be risky and costly, as there is no guarantee that the new investments will be successful. On the other hand, if an investor only focuses on exploitation, they may miss out on potential opportunities for higher returns. The goal of bandit based yield theory is to find the optimal balance between these two conflicting objectives.
One of the key concepts in bandit based yield theory is the concept of the “multi-armed bandit”. This refers to a situation where an investor has a number of different investments to choose from, each with its own potential returns and risks. The investor must decide which investments to pursue in order to maximize their overall returns, while also taking into account the level of risk involved in each investment.
One approach to solving the multi-armed bandit problem is the “explore-then-commit” strategy, which involves initially exploring a number of different investments in order to gather information about their potential returns. Once the investor has gathered enough information, they can then commit to the investment with the highest expected return.
Another approach is the “optimistic initial values” strategy, which involves initially assigning high expected returns to all investments, even if there is little information available about them. This encourages the investor to explore more investments in order to gather information and improve their estimates of the expected returns.
A third approach is the “UCB1” (Upper Confidence Bound) algorithm, which involves assigning a confidence interval to each investment based on the amount of information available about it. The investor then chooses the investment with the highest upper confidence bound, as this represents the investment with the highest expected return given the current level of information.
One of the key benefits of bandit based yield theory is that it allows investors to adapt to changing market conditions and adjust their investment strategies accordingly. For example, if an investor is using the explore-then-commit strategy and discovers that an investment has much lower returns than expected, they can adjust their strategy and explore other investments instead.
There are also a number of variations and extensions to bandit based yield theory that have been developed in order to address more complex situations. One example is the “multi-armed bandit with switching costs” model, which takes into account the fact that switching between investments can be costly in terms of time and resources. This model helps investors to determine when it is worth switching investments and when it is better to stick with what they have.
Another extension is the “stochastic multi-armed bandit” model, which deals with situations where the returns on investments are not fixed, but rather vary randomly over time. This model helps investors to determine the optimal investment strategy in such situations, taking into account the level of uncertainty and the expected returns.
At any given time you will often hear me quoting many famous quotes about anything and everything; that is how I relate to new experiences by trying to tie them to some bit of knowledge that I had already picked up. Probably my most common refrain lately is the famous Mike Tyson quote, “Everyone has a plan until they get punched in the face.” It’s true that everyone talks doing the right thing and everyone wants things to succeed, but as soon as there is some challenge to the prevailing world view or as soon as a small bump in the road exists, people often revert back to what they know best and turn back in on themselves. Unfortunately this is especially problematic in the business world as the only way to move forward is to change behaviors and tackle existing problems in new ways. Even more distressing is that as people fall back to what they are most comfortable with they turn towards their own disciplines and their own previous experience, limiting the ability for people of disparate talents and backgrounds to work together.
One of the things that defines people is the concept of viewing the world through their own experiences, and the most powerful experiences that we have in the modern world is our professions. Be it marketing, or engineering, management or data, we all view the world through the lens of the things we do and the challenges that we face day to day. We view the challenge of improving numbers by looking to “dialogue with our customers” or “increase efficiency through data analysis” or by “building better tools and a better user experience”. All of these in isolation seem like and often are very good ideas except when they cloud our ability to prioritize and to focus on a single outcome. Each day in the business world is really a Sisyphean climb to the top and each time that boulder rolls back on us we run back to that which we are most comfortable with. This is especially dangerous when we do not even have true accountability for the tie between those concepts and the functional bottom line outcome that we need to generate.
Abraham Maslow is famous for many things, from his hierarchy of needs to his many contributions to modern psychology. What he is often not associated with is a quote that almost everyone is familiar with, “if all you have is a hammer, everything looks like a nail.” We are all carrying hammers in the form of our world views and our professional disciplines. The key is to accept that there are many things outside of what we accept as “true” about the way to do things and about how to tackle problems. Even more when we do get evidence that does not directly correlate with our existing world view we can not dismiss it or try to understand it through that same tired lens.
Optimization at its core is the act of adding accountability to these world views and about challenging assumptions. It is about taking the existing practices of the entire organization and standing them on their end, shaking them, and finding all the holes and least effective parts. It does this not maliciously but as a mutual benefit to everyone to add a different point of view on the functions and actions that they are taking. This is why the discipline of testing is about everything but test ideas. It is about building rational rules of action and building out alternative hypothesis. This is why you focus on efficiency and multiple options and not just on what won and not about what won elsewhere or about some great idea someone had. It is why it is about patterns and not about some artificial reasoning why something won. You serve the organization a great discipline when all you do is regurgitate the nail back to someone so that they can then hit it with the same tired hammer. Optimization is the act of putting any idea and discipline through a system that allows for it to get better and for everyone to learn and to get better results.
At the same time, it is important to understand that everyone else is viewing the world through a very different lens. They are trying to tie their past experiences with new actions and new results. A marketer has always thought in terms of a dialogue with a certain user or a certain persona. That mental model has gotten where they are today. When you come in and show that there might be more effective ways to look at those same users or the the concept of personalization most likely will not work the way they envision, you are creating a very powerful form of cognitive dissonance and you are forcing people outside of that hammer that they so readily wield. Too much and you will cause major push back and possibly form an ongoing barrier to success. Too little push and you are just confirming their biases and not providing any assistance.
The key in this and in all actions is to be firm on discipline but flexible on tactics. Work with the concepts and push them past their existing barriers. This is why it is so vital to not focus on test ideas when building out a successful test. Talk about what people were already focusing on and how best you can test out that concept against many others. You want to do personalization, great, here is how we take what you were doing and serve that and other concepts to everyone. If you are right, we get to see that and if you are wrong then we found something that is better. In reality there is no downside to performance when we tackle a problem that way. It is about reaching the ends, not about the means that get you there.
Another key to this is to get people to vote on what they think will win for each test. If you do this enough and with enough varied options and you will be amazed at just how bad people are at guessing the right answer. In the last 9 tests that I have done we have averaged 8 options for each test, with some variants coming from the team, some from myself, but a large many simply expressions of the various directions that are feasible. I have asked a large team to pick there favorite and second favorite. In those 9 tests, we have had exactly 1 second place vote for all of the winners combined, and the only reason that the option got that vote was because my very talented designer picked up on the pattern and voted her least favorite. The shock of where we are versus where people thought we would be and the impact to the bottom line (over 200% improvement) has helped open doors to new ways of tackling problems, and it has done so organically.
In both tactics you are giving people the chance to tie their world view in with the results and letting them have a stake in the outcome. You are welcoming that hammer they wield but helping them see that there are many different nails to hit.
Keep in mind however that you are just as guilty as they are. Spend too much time in the world of optimization and you will start to feel like no one has any idea what they are doing and that all ideas are going to fail. It is even more important for you to challenge yourself and for you to go beyond your comfort zone in where you let testing going. Make sure you include ideas from others as much as possible, even if you are sure they are not going to work. Make sure you tie optimization in on actions that you feel might not comfortable or worth your time. Remember that the smarter someone is, the more likely they are to be impacted by biases and that you serve no good to the organization or yourself if you are not more vigilant against your own biases then you are against others.
You are driving down a road when your GPS tells you to turn left. You make a sudden motion, finding yourself down a small side road. It doesn’t look like where you are trying to go, but you have to follow your GPS; otherwise, you will get lost. You continue, then your GPS tells you to go right. There isn’t a road there, and because you are stuck doing only what the GPS tells you, you turn and suddenly find yourself running off a cliff, flying to your demise in a canyon below. Sound like a bad TV skit? The reality is that this is how most people leverage their “roadmaps” in terms of how they run their optimization programs.
While hypothesis is still the most misunderstood term in all of optimization, the most abused may be roadmap. So many different groups claim they have a roadmap or to be following a roadmap or that it is on their “roadmap” and yet so few understand how one is meant to be used. A roadmap (little r) is a list of tests, most of which serve as a great excuse to waste time and effort and to get locked into a system of projects. A Roadmap (capital R) is a constantly shifting list of priorities by which you will create actions and act to discover where to go next. This distinction is fundamental if you have any hope of really achieving great results with your program, and yet so many happily focus on the first for the sake of internal processes or the inability to change how their optimization program operates in producing revenue.
Let’s start with what the goal of optimization is. It is not to run a test.
Tests are a means to an end.
The goal of an optimization program is to produce the maximum amount of revenue for whatever resources you spend on it. The same is true of every effort you do, be it personalization, SEO, content creation or a promotion. You are not just doing it because it is fun, you are doing those things to increase the revenue to your organization. This means that those are just tactics and not the end onto itself. This is fundamental to understanding the difference between a roadmap and a Roadmap.
Anytime we confuse the action for the end goal, we lose almost all possible value because we have lost the ability to go in any other direction. When we get stuck on a review process and a large series of tests you are making the decision to focus on the action and not the value it generates. You become a means to empty action, not a means to the end of generating revenue. You are saying, at that point, that you couldn’t care less if you make money, so long as these few specific tests get run.
If you instead focus on the end goal, then the first and most important piece is to discover how best to do that. You may have some test ideas and some things you are going to execute on, but they are fungible. You must and will constantly shift them as you learn more and as you go in new directions. You cannot be stuck on the path if the end goal is the most important, you must instead focus on the discipline and flexibility to go anywhere the data tells you.
This is why a Roadmap is just a series of places to focus. It might be on personalizing an experience, or improving a product page, or on improving your recommendation system, but that is what you are trying to do. You are hoping that doing that will result in more revenue, but you are not tied to specific tactics, just finding the best way to accomplish the end goal. Often times you will have no more then 1 or at most 2 tests for each area when you start, but you plan out the time to shift and the time to continue down any path that presents itself to you. From there you can work out actions which will produce answers, things like inclusion/exclusion testing, or MVT, or content serving so that you can measure the value of different alternatives. At that point, you then focus on whatever the answers you have are and continue to drive forward based on those results.
The amazing or frustrating part of this, depending on which approach you are used to, is that you never know where you will end up. You might end up with a dynamic layout for your product page, or targeting content based on time of day, or on removing your recommendations system from a page. The farther you end up from where you imagined the more revenue you make. Each step that takes you in a new direction can only do so by proving using rational measurements that it outperforms where you thought you were going to go. You can end up just about anywhere and that is what makes it so powerful.
The most common refrain you get when tackling problems this way is that it is hard to plan resources, but that argument just does not hold water. You know you are going to test and you know you are going to need resources. This just means you plan time. What you aren’t planning on is that time being spend on coding this one specific module 6 months from now. The action of that time is constantly shifting and updating, it isn’t set in stone. you can plan resources extremely easily. What you can’t do however is focus those resources only on one persons opinion or on a singular person’s agenda. It is not that you spend more resources or can’t plan, you just spend them differently and away from empty talks about a test and about building a successful and meaningful program.
The real challenge becomes not resource planning but accountability. So many programs hold onto their list of tests because it justifies their actions. It becomes about checking off that a test was done and not about the efficiency or the value of that test. At the end of the day the people in your program get to choose between their own accountability between just running tests or with actually providing value. If you are focusing on an empty series of tests, then you will always just be doing action. If you can instead view your Roadmap as a constantly shifting series of actions that focus only on the value they derive, then you will never worry about any specific test or about trying to validate test ideas.
In reality the biggest challenge to tackling problems like this is the ego of the people in your program and the executives who might be involved. People protect themselves at all cases because accountability is the scariest thing in the world for most people. The old systems have everything going through them and with their blessing is everything done. When you are going wherever the data takes you then you are faced with going in a direction that might not be where that executive thought of 3 weeks ago. When you just focus on your part of the a lager process or when you accept their divined vision as the only means to an end then you have essentially said that you have no value at all to the organization and are just a fungible means to an empty end.
This is why an education program and why a focus on discover is so vital for the value derived from your testing program. Management might view this as a loss of power but the reality is that it is so much more. They aren’t constrained by some random thought they had, no matter how great it was, and can instead encourage others to expand on their creativity. It is no longer about having the right answer but about measuring and going with the best ideas your entire team can come up with. You can tell just how far you are from this point with the number of empty I believe/I think/I feel conversations you hear in meetings. The less you hear of those the closer you are to achieving real value. It isn’t about a review process but instead about the creation process and the management of the system to ensure rational decision making.
So many organizations are led to drive into that canyon or into a random lake. Even worse there are always people at those organizations who will describe that water they are drowning in as the expected destination. If you really want to go to new places and really want to end up where you should then you are going to need to give up your belief in that roadmap that you hold so dearly to. Find your own Roadmap, let it shift and go where it needs to, and you will be amazed as just how far you can go and how many new sights you will see.