I recently completed an online course that featured two of my heroes of Behavioral Economics, Oglivy Vice Chairman Rory Sutherland and Duke Professor Dan Ariely, and it included many takeaways that can be applied to gaming companies (social gaming and iGaming). Consumer psychology is changing marketing and product development more than technology so understanding the core principles of behavioral economics is vital to growth, and survival. While I recommend taking the full course (especially the case studies there), below are some of the learnings that would be useful to game companies.
Avoid information or choice overload
A key lesson of behavioral economics is that less choice often drives better results. People can only consciously process a small amount of the information coming in, thus options rich in choice can be too much stimulation. When the number of choices increases, our ability to make a decision decreases.
This issue is clear on a test run in a US grocery store. There was a famous experiment where one group of consumers in a super market had 24 jams available while the other had six. The people exposed to 24 options sampled more but actually bought fewer items. If you are not a big jam eater, another way to visualize the issue is to think of driving into an empty parking lot; with so many choices you have no idea where to park and will probably spend more time driving around than if there were two open spots.
This phenomenon is referred to as choice overload, where the number of choices diminishes sales. For game companies, this issue can translate into how many options to offer in the cashier or how many slot machines to make available when a player first enters your game. The key is more is often not better for your customers or your revenue.
Avoiding choice overload with smart choice architecture
When you are building and optimizing your product, you need to focus on the choice architecture, how you frame and present different options to elicit a desired response. There are several ways to provide the right option for your player while optimizing the choice architecture. One is to consider chunking. In 1956, George Miller found that 7 +/- 2 was the magic number that people could remember. People can recall between 5 and 9 pieces of info in working memory. Thus, rather than giving your customers more than this magic number of choices, create subsets so once they make one decision they can then decide between another seven options. In a game, rather than showing five virtual swords, five virtual arrows, five virtual shields and five virtual loot boxes, offer the customer the choice between swords, arrows, shields or loot boxes. Once they click on one of those, and then show them the five sub-options. Also keep in mind the chunking needs to be meaningful, if you instead sort them by color, people are unlikely to find options they are willing to purchase.
Another technique in optimizing choice architecture is allowing players the freedom to make choice. By affirming someone’s freedom, we can actually make him feel more confident of his decision. To encourage someone to do something, a counter-intuitive response may be to remind them that they are free not to make the purchase.
While there is a magic number, there is no perfect choice architecture for every scenario and product. Hypothesis and testing is critical here. Never stop testing and improving as people will react differently to choices depending on the product, the platform, where they are in the product, etc.
Anchoring is a key driver in perception of cost
Another useful tool for improving performance is anchoring. Anchoring occurs when initial exposure to a number or option serves as a reference point and influences future decisions and purchases. The anchor price, even if a random number, becomes part of a decision set. Once we make a decision about a particular number, that decision stays with us. You then compare other options to the starting point.
Anchoring is used in many situations and businesses. In a restaurant, by having an expensive menu option (i.e. lobster) it makes the other options seem cheap, even though they may be more expensive than you originally were prepared to spend. In the gaming world, if you offer a $1,000 package on your purchase page, while few might buy it, it makes the $50 option look very cheap.
One other element of anchoring is that it is hard to move from free to a cost. We say to ourselves I have been willing to pay zero, I am anchored to zero, so anything above zero does not fit with my historical view of not willing to pay. This is particularly important when we introduce new products to market as it will make it hard to change the price later.
Decoy and middle action
Recently, I wrote about the decoy effect, another pricing strategy based on behavioral psychology. The decoy effect is used when pricing products, adding a third option that drives customers to the most expensive or profitable option. A phenomenon called asymmetric dominance causes customers to change their preference between two options when a third option is presented. The decoy effect is also driven by choice overload, as customers who face many options will adapt by reducing the number of criteria they use for choosing.
What drives the decoy effect is that people derive value not from the intrinsic utility they get from a product but how it compares. Value comes from comparison, if we create comparison, customers will use it, otherwise they will create their own. The simple contrast allows for relativity to show up and point to the option that looks better to something in the set. For example, if you go to Walmart for a TV and there is one option that is $200 and another that is $500, you probably will see if the latter is worth an extra $300. However, if there is also a TV that costs $1,000 but is virtually the same as the $500, you are likely to buy the $500 because it feels like such a bargain, as you are effectively a $1,000 TV. This is a very powerful tool when presenting options to your customers.
Game companies can use the decoy effect when presenting options for in-app purchases. By bundling a high priced virtual good with many other items but not charging for the other items, then putting that bundle next to the virtual good only option, the high priced option appears as a bargain.
We hate uncertainty
Another useful lesson from behavioral economics is that people hate uncertainty. Questions without answers cause fear and kill the user experience and sales, uncertainty is a customer experience killer. Before worrying about motivating your customers, think about the questions and concerns they have and answer them in the first place.
One issues that increases uncertainty (and thus likelihood to lose a sale or customer) is a situation where the customer has missing or incomplete information. Their fears and concerns are not answered. They might not know what happens after they enter their email address or send you their banking information. This uncertainty makes it much more difficult for you to elicit the desired response.
Netflix shows how reducing uncertainty and risk can lead to billions of dollars. The most important message on Netflix’s landing page is not about features, it is the option to cancel anytime. Netflix then sends a reminder email before the free trial ends so the customer can cancel, which answers your uncertainties. This emphasis allows customers to go through the whole process on autopilot rather than full alert. One of the keys to Uber’s success is customers knowing where the car is and expected arrival time, which has proven more important than the car arriving quickly or even price.
Personally, I have found that during the pandemic lockdown, I stopped ordering from local shops that did not provide updates on delivery and kept ordering from the ones who told me when to expect the order. In retrospect, that knowledge (lack of uncertainty) was a much stronger factor than speed of delivery, price or even quality.
Another area of uncertainty that is often neglected is in pricing. Many companies are not very transparent in their pricing, you may not know the cost of a conference or purchase until you click the buy button. What these companies do not realize is that people assume prices are higher than they actually are and may abandon the potential purchase before learning that the price is acceptable.
Other ways game companies can reduce uncertainty include
- Your customers must understand how they can do what they want to do.
- Map the uncertainties and remove them. Give explanations on why you are asking questions or need information.
- Tell people how others have gotten through the process, if others have succeeded customers will experience less uncertainty and feel a reduced risk.
Make it seem easy
As well as reducing uncertainty, you need to minimize perceived effort. Making something easy is different than making it feel easy. Keep in mind that people also equate effort with time, so you should focus on reducing the time people expect to complete a task (purchase, registration, verification, etc) as a proxy for difficulty.
The key is perception. The perceived effort is not about what your customer has to do but how difficult they think it will be to accomplish. To highlight the difference between perception and reality, during the course it was pointed out that if you ask your customers how difficult an action is to undertake, the objective effort only accounts for 1/3 of their answer, 2/3 comes from how your customers feel.
You also not only want to make the desired action easy for your customer, you want them to see it as the easiest option available. There are three ways to make a task seem easy:
- Structure. Our mind works in structures, we seek patterns. That’s why and how we understand information. Bring structure into everything you are telling your customers.
- Language. Avoid toxic words like have to, must, need, it’s required, which make the customer feel it is difficult. Replace these words with ones like easy, quick and short.
- Chunking progress. Seeing the progress is extremely motivating. Chunk the process into small and easy steps and highlight the process.
Reducing friction helps with both ease and uncertainty
Reducing friction is one of the best ways to generate desired behavior. Friction is the blockers that a person needs to go through to complete an action. When making a purchase, it could be entering an email address, credit card number and then setting up an account. The more friction, the more likely the customer will quit before completing the action. Each element of friction increases abandonment rates.
In the course, they use Best Buy (a US retailer) as an example. Best Buy ran a test for its online site to allow people to purchase without setting up an account, what they called Express Checkout. Adding this option increased Best Buy’s revenue $300 million in one year. The cost in lost data was also less than expected, over 60 percent of people still set up accounts (showing that reducing friction early often leads to people completing the same actions later).
The Best Buy example shows that the solution to reducing friction can be eliminating something. Removing a step in the process can be very effective to increase conversion. When designing a process, question what information
is absolutely critical to collect along the process. Part of the design process should be minimizing the subtle cognitive load you placing on your customer.
There are several other ways to reduce friction:
- Pre-fill information so your customer does not have to fill out every field (or preferably any fields).
- Look at pre-existing behavior (paving the cow path). It is easier to design for behavior that is already occurring and not ask your customers to change what they are doing.
- Bundle new behavior with existing actions. Observe existing behavior, possibly things happening at the same time of the year, and bundle it with the desired action.
People need to feel they are treated fairly
Another element of perception important to driving behavior is the perception of fairness. When we evaluate products, we do not just evaluate what we received but evaluate the effort that went into it. If we feel the effort is higher, we are willing to pay a higher price.
People make decisions in context, in large part deciding what is fair. Rather than base a willingness to pay on the value or utility consumers are getting, fairness changes how we evaluate something and how much we are willing to pay. It is why consultants write large reports and why Steve Jobs spent so much time talking about the details on Apple products, letting customers feel it was fair to pay more for Apple products because of all the extra work to build it. We evaluate things based on effort, not on value. It is one of the weaknesses of online companies, especially online gaming companies, where it is difficult to judge the effort the company puts behind the product. If you are doing something magical for people but do not show them, they are less likely to pay a fair price (or monetize at all).
Salaries and compensation are one area where the perception of fairness is obvious. People who receive a high salary but then learn a co-worker is getting more compensation or has gotten a bonus often would look to find a new job or be dissatisfied because they feel they are not being treated fairly, even if their compensation is high. Conversely, employers will often make offers (either higher or lower) to candidates based not on the value the person would deliver or what they expect to pay for the position, but based on what the candidate earned at their current or previous jobs. They feel it is fair to pay candidates based on what they were earning, not on the value they will be delivering.
In terms of selling virtual products, the perception of fairness is often an issue. To many outside the industry, it feels that virtual currency or virtual items are created without any effort, thus it is hard for people to rationalize a purchasing decision. For an online gaming company, one way to mitigate this situation is through your communications. Use social media to take players behind the scenes. Let them see how many people are putting their lives into creating a great game for them.
Do unto others
Reciprocity is another powerful tool often neglected, particularly in marketing. People are much more likely to perform an action if they feel you took the first step. In the course, they discuss a test where they provided customers an unsolicited gift. The test group that received the gift had a much higher conversion rate as customers felt a need to return the favor.
There are several techniques to benefit from reciprocity. To make reciprocity more powerful it should be unexpected, personal and valuable. Order is also very important, you have to say what you are giving first and after that ask for something. It is a technique you should not overuse, you do not want your customers to feel manipulated.
In a social game, you may find that giving your players a free, valuable, gift generates more purchases than a traditional offer. Rather than feeling sold at, they appreciate the gift and are compelled to make a purchase.
The power of loss aversion
One of the strongest drivers of behavior is loss aversion. People are much more sensitive to losses than gains, people are generally 2X to 2.5X more sensitive to losses than gains. That is, the opportunity for gain needs to be more than twice as big as what a player would lose to be a preferred option.
There are several powerful applications of loss aversion:
- Tell your customers what they would lose if they do not take desired behavior, the fear of the loss (including the lost opportunity) can be the strongest motivation.
- Rather than telling people to do something or make a purchase, position the item you want them to purchase as they already own it and have to claim it. If they don’t activate it, they will lose it.
- Reframe message from possibility of gaining to how your player would lose something.
- Make your customers picture what it would be like to own the product, have them dream about what it would be like and they will not want to give up the dream.
- Highlight progress, so they do not want to lose what they have done .
Social proof is one of your most powerful weapons
Social proof is conveying to your customers that others, particularly their friends, are doing something you want them to do. People have a tendency to be influenced by what others do and how they behave. In situations of uncertainty, telling people how others have acted is a strong indicator of what your customers should do.
There are several ways to optimize the effectiveness of social proof. You do not want to be too obvious or superficial, saying 9 out of 10 did something is likely to backfire as it feels like an old commercial. Instead, try to say what the majority does. Also personalize the social proof, make it as close as possible to the person you are communicating with. People are more influenced by others similar to you.
I recently experienced the power of social proof. A friend published a blog post reviewing four World War 2 books and I ordered one as a present for my son. I realized how powerful social proof was after my order as I did not read expert reviews or even see which ones had the best rating on Amazon, I made a purchasing decision based on one person’s non-expert opinion because he was a friend.
Also, avoid social proof in some situation. Do not say how many people are not doing something. It will make your customers questions that maybe they should also abstain. In a social game, you would not want to say 90 percent of players missed the opportunity to win this jackpot, do not be one of those losers. What the player will think is that if 90 percent did not take up the offer, why should they opt for it.
Grab attention with personalization
It is critical that you focus on grabbing your players attention, making things salient. We love the sound of our name; our brain activates differently when we hear our name. Personalization cuts through the clutter and makes communications relevant to us. If you can use someone’s name or make something unique and authentic for them, it will more likely succeed or cause conversion.
Building further on salience and personalization is the concept of idiosyncratic fit, as we see the world relatively, not absolutely. Idiosyncratic fit is the feeling that you enjoy a unique advantage in achieving a goal or completing a task. Consider what your players have already invested, how can you use this information to make them feel they have a benefit to others. In a game, you can give certain rewards to people for having played a certain amount of days or reached a level, ensuring they know they are getting this unique benefit because of things they have already done. This advantage will motivate them to keep purchasing or otherwise engaging.
Defaults are powerful as they help people avoid thinking. If people can avoid thinking, they will. Once you set up the desired action as a default or expected option, they are more likely to perform the activity. Restaurants make wine the default over cocktails (they make more on it) by providing a wine list instead of cocktail list and putting wine glasses on table, thus ordering wine is the default.
In a game, when asking players if they want to receive offers as part of the registration option, pre-check that field. When giving purchase options, test pre-checking the package you are hoping they purchase.
Free is one of your most powerful, and dangerous, tools
Free is much more than another price point. Free is not $0.05 less than $0.05, but is an incredibly powerful motivator. Free makes us think there is no risk (playing to the uncertainty principle) for a given choice. It is very attractive. If yu want people to test a new subscription option, give them a free week or month or year, it will be hard to say no.
The downside of free is that you anchor your customers at that price point.
Moving to free is very tempting, moving away from free is very difficult.
If you sell it for free, people might assume the quality justifies the price.
Test everything and early
One of the most important underlying principles of behavioral economics is that people do not know, and thus cannot tell you, what their preferences are. They do not know what they want until they experience it. Henry Ford said people would have asked for a faster horse. Steve Jobs never used market research on products like the iPod or iPad. Taking what customers say at face value can lead to disastrously wrong choices or limit your creative options. Instead, put your resources into testing.
While many, particularly Product Managers in San Francisco, believe AB testing is a recent phenomenon, it has been used by marketing companies for over 80 years. One of the reasons it has lasted and grown is that it provides clear and actionable results. In contrast, market research is very risky, as it does not show how people will react. People are not intentionally dishonest but are largely strangers to themselves and do not realize what drives their behavior. AB testing (and multi-armed bandit tests) allows you to see how people will react in practice, not theory.
It is both easier and more effective to apply principles of behavioral economics early in the product’s lifecycle. Rather than force your game out, test how people will react when you apply different principles of behavioral economics. Do not build your game based on assumptions how people will respond but instead test it.
If you test something and it works, then test the opposite. You might find that actually works as well or even better as people do not act predictably or linearly. Never stop testing, always look for something better.
- A key lesson of behavioral economics is that less choice often drives better results. When the number of choices increases, our ability to make a decision decreases.
- Consumers hate uncertainty. Questions without answers cause fear and kills the experience and sales, it is a customer experience killer.
- Use AB and multi-armed bandit tests help you understand how your players will react in the context of your game, market research conversely might provide bad information as people do not know what they want.
5 thoughts on “Behavioral Economics Tips for Gaming Companies”
Great thoughts and insights. Definitely agree with reducing the friction. In our latest MVP we tried to delay the login as long as possible to build up the reciprocity. Also really like the idea of Anchoring and Decoy, do you have any stats after implementing anchoring in an in-app purchase screen?
Unfortunately nothing I can share but you also see a lot of variance across games (and even within games based on segmentation). I’d recommend you test different options and with different segments as there is not a one size fits all application of these principles.
I’ve been trying to come up with an interface for my iGaming site through understanding Cognitive Science– this article shows how much psychological play there is when dealing with the abstract process such as our brain
Great article overall!