Making happy customers more profitable

While the key to business success is creating happy and loyal customers, you still need to get them to generate more revenue. A good NPS score and low churn rate shows your customers are satisfied but you only benefit when these customers act on their positive feelings. An article in Harvard Business Review, Make it Easier for Customers to Buy More by Bain Capital’s Rob Markey, shows how to convert this satisfaction into profits.

Learn more about your most loyal customers

The first key to generate more profits from your loyal customers is to understand them better. Markey makes the point that companies focus on learning why detractors, or unhappy customers, are dissatisfied but they do not put the same effort in understanding why the happy customers are happy. As Markey writes, “Converting feelings into action requires knowing exactly what you did to earn their loyalty, so you can replicate the action and extend it. To maintain that kind of intimate relationship with your most loyal customers, you have to create effective mechanisms for staying in close touch.”

Add to all of your communication channels feedback loops to ascertain why they love your company. Have your account or customer service reps ask customers why they first became enthusiastic. When sending out NPS surveys, make sure you ask those providing high scores the reason they gave such a score. Have customers post stories on social media on why they like your offering. Have events for your top customers and ensure part of the agenda is having customers discuss how they fell in love with your brand. Use all of your channels not only to help your customers but to learn from them.

Tune your offerings to meet their needs

When communicating with your best customers, you will learn both what they like and do not like about your offering. You will also understand if your competitors are offering something they want that you do not offer. Markey writes, “ideally, your offerings should be so attractive to your loyalists that they have no reason to look elsewhere for additional products or services.”

Once you understand your customers needs, then adjust your product to meet these needs. It may be by providing additional features or more support services. It could also entail offering your product through new distribution channels or in another format. The key is understanding what your best customers want from your product but are not getting, then adjusting your product to fill this need so they do not move to competitors.

Help them spread the word

Since your most loyal customers by definition love your offering, you want to harness this positive vibe by getting them to promote you to their friends. As people communicate best via stories, you need to provide them with stories that they can share. These stories can range from great interaction with your staff (maybe customer service, VIP management or on Facebook), a great experience with your game or product or even a little bonus you got via email. Once they have the stories, you need to facilitate them sharing the stories. This sharing often is by social media but it can be video testimonials on your website or even quotes in your game.

Loyal customers drive profits

While it is critical to create incredibly satisfied customers, that is not the end of the battle. You need to learn from them, use this knowledge to make your products even more suited to them and then turn them into advocates.

Key takeaways

The first key to generate higher profits is learning from your most loyal customers why they love your product.
The second key is taking this knowledge and further tweaking your product to meet your loyal customers’ needs.
The final key is getting these loyal customers to advocate for you by sharing stories that show their friends why your product or company is great.

Thinking, Fast and Slow, Part 2: Why we should care about judgment errors

As promised last month, I will spend a few blog posts summarizing Thinking, Fast and Slow by Daniel Kahneman. Before diving into the heuristics, biases and processes that he and his colleague Amos Tversky identified, it is important to understand why he wrote the book and why it is so useful. Fortunately, he largely does this in his introduction so it is a great place to start.

Let’s not beat ourselves up but make ourselves better

First, Kahneman points out that the goal of his research is not to prove we are idiots but to help us minimize bad decisions. Understanding flaws in human decision-making is no more insulting or denigrating than writing about diseases in a medical journal belittles good health. Rather, our decision-making is generally quite good, most of our judgments are appropriate most of the time, but there are systemic biases that if we understand can make our decision-making more effective.

By understanding Kahneman’s work, you will be better able to identify and understand errors of judgment and choice, in others and then yourself. As Kahneman points out, “an accurate diagnosis may suggest an intervention to limit the damage that bad judgments and choices often cause.”

Is our judgment flawed?

At its roots, Kahneman began his career trying to determine if people consistently made biased judgments. Long story short, we do.

One example drove this determination home to Kahneman and Tversky and probably will to you also. Early in their collaboration, both Kahneman and Tversky realized they made the same “silly” prognostications about careers that toddlers would pursue when they became adults. They both knew an argumentative three year old and felt it was likely that he would become a lawyer, the empathetic and mildly intrusive toddler would become a psychotherapist and the nerdy kid would become a professor. They, both smart academics, neglected the baseline data (very few people became psychotherapists, professors or even lawyers compared with other professions) and instead believed the stories in their head about who ended up in what careers was accurate. This realization drove their ensuing research, that we are all biased.

How understanding Kahneman’s work impacts the world

The broad impact of Kahneman and Tversky’s work drives home it’s importance to everyone. When they published their first major paper, it was commonly accepted in academia that:

People are generally rational, and their thinking is normally sound
Emotions such as fear, affection and hatred explain most of the occasions on which people depart from rationality

Not only did these two assumptions drive academia (particularly economics and social sciences) but also their acceptance often drove business and government decisions. The work laid out in Thinking, Fast and Slow, however, disproved these two assumptions and thus drove entirely different decisions to generate strong results.

Scholars in a host of disciplines have found it useful and have leveraged it in other fields, such as medical diagnosis, legal judgment, intelligence analysis, philosophy, finance, statistics and military strategy. Kahneman cites an example from the field of Public Policy. His research showed that people generally assess the relative importance of issues by the ease with which they are retrieved from memory, and this is largely determined by the extent of coverage in the media. This insight now drives everything from election strategy to understanding (and countering) how authoritarian regimes manipulate the populace.

Kahneman and Tversky were also careful to ensure the subject of their experiments were not simply university students. By using scholars and experts as the subject of their experiments, thought leaders gained an unusual opportunity to observe possible flaws in their own thinking. Having seen themselves fail, they became more likely to question the dogmatic assumption, prevalent at the time that the human mind is rational and logical. I found the same myself and am confident that you will also. The idea that our minds are susceptible to systematic errors is now generally accepted.

Why it is called Thinking, Fast and Slow

While Kahneman and Tversky’s early work focused on our biases in judgment, their later work focused on decision-making under uncertainty. They found systemic biases in our decisions that consistently violated the rules of rational choice.

Again, we should not discount our decision-making skills. Many examples of experts who can quickly make critical decisions, from a chess master who can identify the top 20 next moves on a board as he walks by to a fireman knowing what areas to avoid in a burning building, experts often make critical decisions quickly.

What Kahneman and Tversky identified, though, is that while this expertise is often credited with good decision making, it is more of retrieving information from memory. The situation serves as a cue or trigger for the expert to retrieve the appropriate answer.

This insight helps us avoid a problem where our experience (which we consider intuition) does not actually help but hinders. In easy situations, intuition works. In difficult ones, we often answer the wrong questions. We answer the easier question, often without noticing the substitution.

If we fail to come to an intuitive solution, we switch to a more deliberate and effortful form of thinking. This is the slow thinking of the title. Fast thinking is both the expert and heuristic.

Example from our world, The Allan Mistake

Many of my readers are experienced “experts” from the mobile game space, so I will start with a hypothetical example that many of us can relate to. In this example, Allan is the GM of his company’s puzzle game division. He has been in the game industry over twenty years and has seen many successful and failed projects. The CEO, Mark, comes to Allan and says they are about to sign one of three celebrities to build a game around.

Allan knows the demographics of puzzle players intimately and identifies the one celebrity who is most popular with Allan’s target customers. Nine months later they launch the game and it is an abysmal failure. Allan is terminated and wonders what he did wrong.

Allan then looks over his notes from when he read Thinking, Fast and Slow, and realizes his fundamental mistake. When Mark came to him and asked which celebrity to use, Allan took the easy route and analyzed the three celebrity options. He did not tackle the actual question, whether it was beneficial to use a celebrity for a puzzle game and only if that was positive to pick between the three. If he had answered the more difficult question (difficult also because it would have set him against Mark), he would have found that celebrity puzzle games are never successful, regardless of the celebrity. Although it may have created tensions at the time with Mark, he probably would have been given an opportunity to create a game with a higher likelihood of success and still be in his position.

Key takeaways

Our decision making is not bad but by understanding our systemic biases we can be more efficient.
Understanding that people are not regularly rational and that this irrationality is not driven by emotion allows us to make better decisions in fields as diverse as medical diagnosis, legal judgment, intelligence analysis, philosophy, finance, statistics and military strategy.
Fast thinking refers to quick decisions and judgments based on our experience while slow thinking is the analysis of difficult questions.

Thinking, Fast and Slow, Part 1: The Linda Problem

I recently finished Michael Lewis’ most recent book, The Undoing Project: A Friendship that Changed the World and it motivated me to revisit Daniel Kahneman’s Thinking, Fast and Slow. Lewis’ book describes the relationship between Daniel Kahneman and Amos Tversky, two psychologists whose research gave birth to behavioral economics, modern consumer behavior theory and the practical understanding of people’s decision making. He explains the challenges they faced and the breakthroughs that now seem obvious.

As I mentioned, The Undoing Project reminded me how important Kahneman’s book was, probably the most important book I have ever read. It has helped me professionally, both understand consumer behavior and make better business decisions. It has helped me in my personal life, again better decision making in everything from holiday choices to career moves. It helps even to explain the election of Donald Trump or how the situation in North Korea has developed.

In the Undoing Project, two things drove home the importance of Kahneman’s work. First, despite being a psychologist, Kahneman won the Nobel Prize for Economics in 2002. It is difficult enough to win a Nobel Prize (I’m still waiting for the call), but to do it in a field that is not your practice is amazing. The second item that proved the value of Kahneman’s (and his colleague Amos Tversky) work was the Linda Problem. I will discuss this scenario later in this post, but the Linda Problem proved how people do not make rational decisions, myself included. It convinced the mainstream that people, including doctors and intellectuals, consistently made irrational decisions.

Despite the value I derived from Thinking, Fast and Slow, I never felt I learned all I could from it. I found it very difficult to read, the exact opposite of a Michel Lewis book, and did not digest all the information Kahneman provided. Even when I recommended the book to friends, I often caveat the recommendation with a warning it will be hard to get through.

Given the importance of Kahneman’s work and the challenge I (and probably others) have had in fully digesting Thinking, Fast and Slow, I will be writing a series of blog posts, each one summarizing one chapter of Kahneman’s book. I hope you find it as useful as I know I will.

The Linda Problem

As discussed above, the Linda Problem is the research by Kahneman and Tversky that largely proved people thought irrationally, or at least did not understand logic. While I normally like to paraphrase my learnings or put them into examples relevant for my audience, in this case it is best to show the relevant description from The Undoing Project, as the Linda Project was a scientific study that I do not want to misrepresent:

Linda is 31 years old, single, outspoken and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations.

Linda was designed to be the stereotype of a feminist. Danny and Amos asked: To what degree does Linda resemble the typical member of each of the following classes?

Linda is a teacher in elementary school.

Linda works in a bookstore and takes Yoga classes.

Linda is active in the feminist movement.

Linda is a psychiatric social worker.

Linda is a member of the League of Women voters.

Linda is a bank teller.

Linda is an insurance salesperson.

Linda is a bank teller and is active in the feminist movement.

Danny [Kahneman] passed out the Linda vignette to students at the University of British Columbia. In this first experiment, two different groups of students were given four of the eight descriptions and asked to judge the odds that they were true. One of the groups had “Linda is a bank teller” on its list; the other got “Linda is a bank teller and is active in the feminist movement.” Those were the only two descriptions that mattered, though of course the students didn’t know that. The group given “Linda is a bank teller and is active in the feminist movement” judged it more likely than the group assigned “Linda is a bank teller.” That result was all that Danny and Amos [Tversky] needed to make their big point: The rules of thumb people used to evaluate probability led to misjudgments. “Linda is a bank teller and is active in the feminist movement” could never be more probable than “Linda is a bank teller.” “Linda is a bank teller and active in the feminist movement” was just a special case of “Linda is a bank teller.” “Linda is a bank teller” included “Linda is a bank teller and activist in the feminist movement” along with “Linda is a bank teller and likes to walk naked through Serbian forests” and all other bank-telling Lindas.

One description was entirely contained by the other. People were blind to logic. They put the Linda problem in different ways, to make sure that the students who served as their lab rats weren’t misreading its first line as saying “Linda is a bank teller NOT active in the feminist movement.” They put it to graduate students with training in logic and statistics. They put it to doctors, in a complicated medical story, in which lay embedded the opportunity to make a fatal error of logic. In overwhelming numbers doctors made the same mistake as undergraduates.

The fact that almost everyone made the same logic mistakes shows how powerful this understanding is. It proves that our judgment, and thus decision making, is often not logical but does contain flaws. This understanding helps explain many things in life and business that sometimes do not seem to makes sense.

The implications

Once you understand how our judgment is biased, it can help you make better decisions. It can also provide insights into how your customers view different options and why people behave as they do. In future posts, I will explore all of Kahneman and Tversky’s major findings and how they apply.

Key Takeaways

In the Undoing Project, Michael Lewis writes about the relationship and research of Daniel Kahneman and Amos Tversky, two psychologists who changed the way we understand decision making
The Linda Problem proved to the non-believers that people made illogical judgments. When given a story about a fictional person and then potential careers for that person, virtually everyone (from students to very successful professionals) chose a persona that was a subset of a broader persona, thus impossible that the former was more likely.
By understanding how people make judgments and decisions, we can improve our own decision making process and better understand our friends, family and customers.

How to manage your own biases

I have always been interested in decision making and how people often are not logical in not only their preferences but even how they remember and look at facts. The most useful book I ever read was Thinking, Fast and Slow by Daniel Kahneman, (highly recommend it if you haven’t read it yet) and one of my favorite academics is behavioral economist Dan Ariely. Not only does Kahneman and Ariely’s research help you understand consumer behavior, it helps you understand your own decision making and, most importantly, mistakes most of us make.

A recent guest blog post on the Amplitude Blog, 5 Cognitive Biases Ruining Your Growth, does a great job of describing five biases that can greatly impact your business. While I will try to avoid just repeating the blog post, below are the five biases and some ways they may be impacting you:

Confirmation bias. Confirmation bias is when you interpret or recall information in a way that confirms your preexisting beliefs or hypotheses, while giving disproportionately less consideration to alternative possibilities.This bias occurs regularly in the game space, especially with free to play games.
A product manager may have driven a new feature, maybe a new price point on the pay wall. Rather than running an AB test (maybe insufficient traffic or other changes going on), they then review the feature pre and post launch. Game revenue per user increased 10 percent so they create a Powerpoint and email the CEO that there new feature had a 10 percent impact. Then the company adds this feature to all its games. The reality is that at the same time the feature was released the marketing team stopped a television campaign that was attracting poorly monetizing players. The latter is actually what caused the change in revenue. As someone who has known a lot of product managers, I can confirm this bias in the real world.
The narrative fallacy. People try to comprehend information in stories, rather than looking at just the facts they create a story that links them together even if there is not really a link. If you watch business news, when the stock market goes up 5 points, the narrative may be the market has rebounded from its Brexit blues. If the market goes down 5 points, the same story would be the market is still suffering from Brexit. The reality is that 5 points is statistically insignificant (the market is an aggregate of multiple stocks) so neither narrative is more likely in either scenario. The key issue here is that we attribute causation where there is none.An example in the game world.
Two branded games are in the top 5 of new releases. All of the analysis is that branded games are now what customers are looking for. The realities is that the two games, totally unrelated, had strong mechanics and were just that lucky 10% of games that succeed. Allowing the Narrative Fallacy to win, however, you then put your resources to branded games, which are no more popular than before the launch of the two successful titles.
Dunning-Kruger Effect. Before the Amplitude post, I had not heard of this bias, at least with this name, but once you read about it I am sure you will know cases of it. The Dunning-Kruger Effect is when incompetent or somewhat unskilled people think they are more skilled than they are. As the article quotes, “incompetent people do not recognize—scratch that, cannot recognize—just how incompetent they are.”
Again, for the example from the game industry. Let’s say you want to port your game to a new VR platform. You go to your development team and they say it won’t be a problem. You sign up for the project, give them the specs, six months later they still cannot get the game to run on the VR platform as they have no idea how to develop VR (this is a nicer example than some others I can remember).
Backfire effect. The backfire effect is after analyzing something that you or your company are doing, if the results are negative and the action was bad, you or your colleagues refuse to accept the results. As they write in the blog post, “the exact definition of the Backfire Effect [is]: ‘When people react to disconfirming evidence by strengthening their beliefs.’”
As an example, you decide to analyze how your company has been calculating LTV. You look back at the analysis done the last two years and see how actual LTV tracked with projections at that time. You discover that you underestimated actual spend by 50 percent. Should be great news, will allow you to ramp up dramatically your user acquisition. Instead, when you present this data to your analytics team, they refuse to accept it, saying your analysis is flawed because you are not looking at the right cohorts.
Bandwagon effect. The bandwagon effect is what you would assume, the tendency to do things because many other people are doing it. People will rally around a cause, an idea, a candidate, a variation, or a strategy simply because it is popular.
Given that I want to keep this blog post under 500 GB, I will not list all the examples of the bandwagon effect I have seen in the game industry. Product strategy, however, is the most obvious culprit. When the free to play game industry started to evolve to mobile, everyone started porting its Facebook games over to mobile. Since Zynga and the other big companies were doing it, all of the smaller companies as well as newly funded ones also tried to bring the same core mechanics from Facebook over to mobile. Mechanics that worked on Facebook, however, did not work on mobile but companies continued doing it because everyone else was. Rather than identify the market need and a potential blue ocean, companies just joined the bandwagon.

Avoid these biases

The key to making the right decisions is not to assume you do not have biases, but always to be diligent in reviewing your decisions and making sure you are thinking rationally. All of these biases can lead to personal or company failure, so the inability to identify them can have extreme consequences.

Key takeaways

Understanding our biases allows us to not only understand our customers but make better decisions.
A core bias you see in the game industry is confirmation bias, where someone looks at data to prove their hypothesis (or brilliance), even if the data does not really support it.
Another critical bias is the narrative fallacy, where we create a story to explain an event even if the story is not the cause of the event.

Neuromarketing and gaming

I recently finished a class on Coursera, An Introduction to Consumer Neuroscience & Neuromarketing, that gave some great insights applicable to gaming and the greater tech sector.

Neuromarketing is a very exciting new field that is driving business growth, think Big Data ten years ago. The course, taught by Neuromarketing pioneer Thomas Zoëga Ramsøy of the Copenhagen Business School, delves into neuroscience and how both small and large companies can use it. It leverages increasing understanding in how the brain works with the emergence of behavioral economics and data-driven marketing.

While marketing in the past largely relied on intuition, surveys and focus groups, neuromarketing starts by understanding how the brain functions and what parts of the brain drive different behavior. By understanding what parts of the brain drive emotion, motivation, etc., you can then create products and marketing campaign most likely to get customers to purchase.

While I am not the person to summarize how the brain works, below are some of the key learnings from Professor Ramsøy’s course and implications for the game industry.

Cognitive Load

The concept of cognitive load is critical to the success of many products, from games like slots to apps like Uber. Given the the human brain consumers 20 percent of the body’s energy but only is 2 percent of the body’s mass, it is important to understand that people will subconsciously work to reduce the amount of energy the brain is using.

Cognitive load is how much info people are processing at any one time. Cognitive load is tied to working memory, the more information in that short-term memory the higher the cognitive load. As cognitive load increases, consumers are less likely to make a purchasing decision.

The concept of cognitive load also confirms why UIUX is often better when simpler. A simple user experience minimizes cognitive load, thus not creating too much strain.

Implications

It is important to manage proactively consumers’ cognitive load. Giving consumers many choices increases their cognitive load, thus making them less likely to purchase. Thus, it is critical that rather than giving your customer 25 different packages they can buy, keep the purchasing decision simple.

While simpler is better is often considered the goal of UIUX, it often is abandoned so new features can be added. The reality is that simpler is more important than features and you need to build your products not as a tradeoff between the two but as something that focuses on minimizing customers cognitive load.

Uber is a great example of the success of this strategy. From a very simple interface to only a few options to not even letting customers think about tipping to not even having to worry about paying, using Uber requires very little thought. Yet this incredibly simple app has made Uber worth over $60 billion.

Not only is cognitive load important when creating the overall product but also the underlying mechanic in the product. People often question the enduring popularity of slot machines. There are, however, virtually no game mechanics that have lower cognitive load than slots. The slot mechanic provides entertainment without using too much energy. When creating other mechanics, it is critical to understand how much mental energy they will consume.

Search and attention

One of the most powerful applications of neuromarketing is related to search and what consumers select following the search process. Critically, there are two types of search, and each is driven by different parts of the brain.

First there is bottom-up search, which is largely unconscious. This is where a person comes across something and it grabs your attention. Certain receptors in eyes more receptive to things like contrast and density. The best example is when you are in a grocery store and you notice something you were not planning on buying. This type of search is generally driven by colors, shape and density. Consumers are likely to buy some that grabs their attention. As much of consumer behavior is unconscious,

The other type of search is top-down, which is primarily conscious. This is when somebody is searching for something in particular. You may again be in a grocery store and looking for eggs. You will focus your mental energy on thinking hard and finding what you need.

Implications

You need to design your UIUX based on what type of search your customers will be conducting. If they are conducting a top-down search, then you do not have to prioritize making it that visible. They will find it regardless. Conversely, if you want to engage your easier (get them to try a new feature or new content or have them think about monetizing), then you want to stand out during a bottom-up search.

In this case, there are some great new tools for UIUX to optimize visual search results. Professor Ramsøy, who taught the course, has a commercial product called Neurovision. Neurovision allows you to put in an image of your game (in our case) and see what players will notice without the need of a fancy heat test, thus what will jump out in a bottom-up search (see example below):

It is also often used by retailers (including Walmart and Home Depot) to understand what consumers will see while walking through their store, it can even analyze what people will notice during videos. Neurovision is one of a host of new products based on Neuroscience that help you scientifically improve your products rather than relying on anecdotal experience with a limited number of users.

Branding

The value of brands is often debated but neuromarketing shows the value of a brand. Brands impact how we perceive and enjoy a product and stimulate additional parts of the brain that the product would not normally impact.

As discussed with cognitive load, the brain uses a lot of energy and consumers are constantly looking at ways to minimize this energy usage. Brands help consumers save energy because when they see a brand they are familiar with, the branding fills in a lot of information that they do not have to then ascertain (quality, style, etc.). Thus, when deciding between a branded product and a brand they are not familiar with (or no brand) the branded product has an advantage as choosing it requires less energy.

While this analysis may not seem like neuromarketing, neuromarketing confirms it. When people who have been exposed to branding for a certain paint are then in the paint section of a hardware store, eye-tracking confirms that they spend more attention on products from brands they are aware of. This phenomenon then leads to a higher likelihood of purchase.

Branding also helps with search, particularly bottom up search. While a consumer focused on finding a specific product or specific feature set may not respond to branding, as they are doing a top-down search, someone who is browsing for a new product (say a new casino app), a familiar brand would make it more likely to gain a customer’s attention.

Finally, branding stimulates parts of the brain that then impact how consumers feel about a product. A strong brand will create positive emotions around a product even before the consumer evaluates the product.

Implications

Branding is not dead or useless in a performance marketing world. Strong brand can translate into a higher impact from your performance marketing, customers are more likely to click on your ads. They are also more likely to pick your product when searching organically for one.

Using Neuroscience

Neuroscience is a strong tool to help improve your product and marketing. By understanding how the brain processes information, you can tailor your product and marketing to optimize your chances for success.

Key takeaways

Neuromarketing, based on neuroscience, uses understanding of the brain to drive product and marketing decisions, just as big data creates much higher returns.
You can increase sales and satisfaction by minimizing cognitive load, how much your customer’s brain has to process navigating your app or store
Your UIUX should account for whether your customer is conducint a top-down search (looking for something in particular) or bottom-up search where you want them to find something.

Don’t Reply All, for Gods sake

I recently had an epiphany, that the Reply All option to email creates undesirable and sub-optimal behavior, similar to the proliferation of meetings and Powerpoints. Rather than progressing a conversation, Reply All often keeps people from making substantive contributions and prompts people to ignore the key issues. Of course, sometimes there is value to Reply All, you share information with multiple people who need it, but it is something you should use judiciously rather than as a default.

Communicate

The key problem with Reply All is that it is often used by someone to make a point or impress other people on the thread, normally higher-ranking executives. Some people see it as an opportunity to present knowledge or an idea not necessarily relevant to the message, to impress some on the thread. This creates a situation where people discount the entire thread and sometimes the original reason for the email is lost, without appropriate action taken on that email.

Rather than Reply All, you should determine who you want to communicate with and only include those on the response. Then, rather than using it to posture, you are proactively moving the conversation forward with relevant parties.

Watch what you say

While most people are polite to their colleagues in person, Reply All often invites boorish behavior. Building on people using it to impress, some people feel the best way to impress is by disparaging a colleague. The thought is that by making your colleagues seem weaker, it elevates them. The reality is that degrading a colleague will often permanently weaken your relationship with that colleague, they are less likely to support your future initiatives or go out of their way to help you and if they reach a leadership position they are likely to remember your behavior. Others on the thread, however, are also unlikely to be impressed, they will actually probably question your character and be less likely to support you in the future.

If there has been a legitimate mistake, reply directly to the person who made the mistake and give them the opportunity to correct it. Your goal should be ensuring the organization has the right information, not that you know more than your colleagues. If they do not agree with you or fail to correct, then respond (but only include relevant stakeholders) but do it in an objective manner that does not throw your colleague under the bus.

Why be the smartest person the thread

The biggest negative often of replying all is that it dissuades others from being part of the conversation. As I wrote several months ago, you should not try to be the smartest person in the room, and the same holds true for email threads. Rather than trying to impress everyone, learn from them so you can come to the best possible solution. Let everyone put forward their best ideas. Ensure a vibrant conversation, listen to others and, if anything, respond primarily to solicit more ideas.

Just think and reply appropriately

The key to communicating effectively is to think first. Determine who you should be speaking with and limit your communication to them. Then ensure you are propagating a message that moves the conversation forward, more likely to a better solution. Most importantly, avoid trying to impress others, especially at the expense of colleagues, and focus on the appropriate message to the right people.

Key takeaways

Simply replying all to an email often does not provide the highest value to the business, ensure that you really need to Reply All before doing it.
Do not use Reply All as an opportunity to impress, instead use it only to move conversation forward.
Never use Reply All to denigrate a colleague, if you must question someone do it directly.

How to create a valuable product or game

A colleague of mine recently used in a presentation a chart from a Harvard Business Review article and it was so helpful in defining a new product I wanted to share the concepts with everyone. In The Elements of Value by Eric Almquist, John Senior and Nicolas Block of Bain’s Strategy Practice, the authors discuss that while consumers evaluate a product by its perceived value versus cost, most marketers and executives focus on the price side of the equation. They attribute this focus largely to it being easier to manage price, as there are limited variables involved and it is easy to test.

It is more challenging to measure and optimize what customers truly value, whether functional (giving someone more capabilities) or emotional, because it is often a combination of multiple components. While value is always intrinsic to the customer (different people have a different value for the same attributes), the authors have identified universal building blocks of value to improve performance in current markets or enter new markets. Their analysis shows that the right combinations of these attributes leads to higher customer loyalty, greater willingness to try a brand and sustained revenue growth.

In the article, they have identified 30 elements of value (see below), fundamental attributes in their most essential and discrete forms. You can categorize these components in four buckets:

Functional
Emotional
Life-changing
Social impact

From Harvard Business Review, Sept 2016

Some are inwardly focused, like motivation, while others help people deal with other or operate in the world, Not surprisingly, the Value Pyramid is related to Maslow’s Hierarchy of Needs. For those not familiar with Maslow’s work, Maslow’s hierarchy of needs is often portrayed in the shape of a pyramid with the largest, most fundamental levels of needs at the bottom and the need for self-actualization and self-transcendence at the top. The most fundamental and basic four layers of the pyramid contain what Maslow called “deficiency needs” or “d-needs”: esteem, friendship and love, security, and physical needs. If these “deficiency needs” are not met – with the exception of the most fundamental (physiological) need – there may not be a physical indication, but the individual will feel anxious and tense. Maslow’s theory suggests that the most basic level of needs must be met before the individual will strongly desire (or focus motivation upon) the secondary or higher level needs.

According the Almquist, Senior and Bloch, “the elements of value approach extends his insights by focusing on people as consumers—describing their behavior as it relates to products and services….The elements of value pyramid is a heuristic model—practical rather than theoretically perfect—in which the most powerful forms of value live at the top. To be able to deliver on those higher-order elements, a company must provide at least some of the functional elements required by a particular product category.”

Depending on your industry and product, the elements of value will vary. Some industries or geographies will focus more on basic elements, those near the bottom of the pyramid, while others will be focused higher.

Product lifecycle is critical

One area the authors did not explore that I think is critical is product lifecycle. Also, although not a feature of the article, an industry’s stage of development strongly impacts which elements will drive value for a consumer. In an emerging industry, consumers will be much more driven by the functional features. As an industry matures, you no longer will be able to compete on the functional elements but instead will need to move higher up the pyramid. Everyone in the industry will be providing the functional features, so you will have to deliver emotional value. Even there, your competitors will catch up and you will then have to deliver life changing or social impact attributes.

The social slots business is a great example of how the value pyramid has driven success. Five + years ago, companies experienced great success just by providing an online version of slot machines that people formerly only played in casinos. As long as you had a game that worked, priced it correctly (free to play) and made it simple to use, you had a ticket to print money. As the market became more mature, emotional attributes became the factor that generated success. Companies late to the market leap-frogged the Functional leaders by making the products nostalgic (classic slots by DGN or Rocket Games) or better design and more attractive (Hit It Rich by Zynga). As the market gets even more mature and competitive the companies that are experiencing success are those that are introducing life changing elements, primarily affiliation and belonging (such as Huuuge Games).

Using the elements to grow

An area where the elements can help you succeed is by improving on the elements that form your core value, so you can differentiate from the competition and better meet your customers’ needs. The elements can also help you grow your product’s value without overhauling your game or product.

Some companies use the elements to identify where customers see strengths and weaknesses. First, they look at which elements are important in their industry and how they compare with competitors. Then if there are any significant gaps, the priority is eliminating those gaps. Once the gaps are closed, you can then see what elements could create a new gap above your competitors.

Implementation

To leverage the elements model effectively, you should integrate it into several key areas of your business:

New product development. The elements framework should provide ideas for new products and enhancements to existing products.
Pricing. If you are looking to increase your prices, you can soften the blow of the increase by concurrently increasing the value your customer receives from your product. Amazon Prime is a great example, as the service started at $79.99 (I think) with frequent discounts and is now significantly higher but the free shipping is only a side thought, as you get everything from streaming services to special credit cards.
Customer segmentation. Rather than only segmenting customers by demographic or behavioral group, you can use the elements to segment them by where they are deriving value. You can then focus on delivering more of the elements that these segments want or highlighting the elements that may exist but they are not aware of.

While adding value to increase competitive is not the most unique or newest idea, Almquist et. al., have created a framework to focus on creating the most value for your customers and knowing where to focus to increase that value. If you continue to deliver more value than your competitors, you will succeed.

Key takeaways

There are 30 core elements that drive the value a consumer derives from a product and the more they are willing to spend on the product
The values are hierarchical, similar to Maslow’s hierarchy of needs, and once a consumer gets the base value they will be more engaged by life changing or social impact elements.
The value you need to deliver is based on the life stage of the industry. Young industries are focused on functional value while you need to deliver higher level value to compete in a mature industry.

Do people really have a short attention span

A few months ago I posted about the cadence of releasing new content, citing Netflix as an example, and it got me to start questioning a related commonly held belief, that consumers attention spans are shrinking. It goes without question that people today have shorter attention spans than previous generations, look at YouTube videos versus television shows. Common sense says game players or tv watchers now want a faster, more intense short experience. Whenever I hear “commonly held, “goes without question,” or “common sense” I get very skeptical, as it often means we are assuming something without evidence to prove it.

Television actually shows an increased attention span

The launch of 24: Legacy helped crystalize my suspicion against the case of shorter attention spans. When the original 24 series launched in 2001, it was a tremendous success largely because it went from a model where an episode on network television was primarily self-contained to a story arc that spanned an entire season.

Fast forward to 2017 and most of the dramas on television involve a story arc that lasts a season (or more). From Game of Thrones to Luke Cage to Man in the High Castle to Mr. Robot, each episode leads to the next and the story arc is not complete until the end of the season. Even popular network television shows like Quantico and The Flash have story arcs that pull you from one episode to the next.

A season of a TV series now is closer to a mini-series in the 1970s and 1980s (Roots, V, Holocaust). Rather than watch a single episode and be done with it, people are eager to watch 10-13 episodes (about 10 hours of programming), demanding more, not less, attention of viewers.

Games also have captured our attention for longer

Some would argue the rise of mobile, casual games shows that the game industry is experiencing shorter attention spans, as players are looking for a short (5-15 minute experience), but wait, maybe games are experiencing the same phenomenon as television. In the early 2000s people would wait anxiously and buy an Unreal or Halo or Final Fantasy, play it for days or weeks (often without sleeping or at least showering) and then go on the next big game. Now you may actually shower but instead of playing for days or weeks, you are actually playing the same game for years. The top grossing games in the iOS US iPad AppStore include Minecraft (launched 2009), Game of War (2013), DoubleDown (2010), and Candy Crush (2012), ranging in age from 4 to 7 years. These games shown that rather than lasting minutes, game players’ attention span last years.

What this means

Rather than just being an interesting discussion point, the attention span issue has significant implication for game producers as well as other entertainment companies. When you are designing your product, rather than just focusing on short and intense play sessions, understand how you will keep players engaged for years. Rather than trying to stick a metagame on top of your product, you need to build it for long-term engagement from the ground. Only then will you satisfy the demand for a sustained entertainment experience. And most importantly, never use conventional wisdom or common sense to plan your product or strategy.

Key takeaways

While it is commonly accepted that consumers’ attention span has decreased, the opposite is actually true.
Rather than just watching one television episode or play a game for a few days/weeks, viewers now will watch a full season to grasp the metastory and play the same game for years.
To satisfy the new consumer, you need to create entertainment products that can last for years, not minutes.

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