Photo Credit: Mel B,

Viral Loops or Viral ‘Oops’?

Recently, MessageMe announced it had grown to 1 million users in a little over a week’s time. The revelation captured the attention of envious app makers throughout Silicon Valley, all of whom are searching for the secrets of customer acquisition like it’s the fountain of youth. “Growth hacking” has become the latest buzzword, as investors like Paul Graham profess it’s functionally that matters.

Clearly, everyone wants growth. To someone creating a new technology, nothing feels better than people actually using what you’ve built and telling their friends. Growth feels validating. It tells everyone the company is doing things right. At least that’s what we want to believe.

GOOD GROWTH, BAD GROWTH

Sometimes viral loops drive growth, because the product is truly awesome, while in other cases growth occurs for, well, different reasons. As an example of good growth, it’s hard to top PayPal’s viral success in the late 90s. PayPal knew that once users started sending money to each other, mostly for stuff bought on eBay, they would infect one another. The allure that someone just “sent you money” was a huge incentive to register.

PayPal nailed virality. Both sides of the transaction benefited from utilizing the platform and a classic network-effects business was born. In order for users to get what they wanted, they had to open an account and the product spread because it was useful and viral.

However, sometimes viral loops are less about the customer’s interests and more about short-term greed. When the product maker intentionally tricks users into inviting friends or blasting social networks, they may see growth, but it comes at the expense of goodwill and trust. When people discover they’ve been tricked, they vent their hatred and stop using the product. Unfortunately, we’ve all encountered the ways companies drive growth in deceptive ways known as “dark patterns.”

VIRAL OOPS

Good and bad growth is relatively easy to identify. What is harder to decipher is the gray zone in between. A “viral oops” occurs when users unintentionally invite others, but when they look back on what happened, they blame themselves, not the app.

When MessageMe pre-selects everyone in my contact list as a default, I’m likely to think that only those who are un-checked will be invited. However, the opposite is true. With two taps, my list of hundreds of contacts gets swamped with a notification email personalized from my email account.

Could users really make such a mistake? After all, the send button is clearly labeled with the number of people who will be invited. I am also well aware of the convention that a check mark means the contact is selected and not the other way around.

However, say I was not in UX businesses? What if I were a tech novice living outside our little Silicon Valley bubble? What if I were slightly far-sighted? Or perhaps if English were not my first language (it isn’t)? Or maybe if I were attempting to make a quick decision while outdoors and couldn’t clearly see my dim screen? In any one of these scenarios, I could have easily triggered a viral oops.

The surprising math of viral growth reveals it doesn’t take many users to make this kind of mistake. Only 5 percent of users screwing up can get an app to a million downloads in two weeks, assuming the average user has 200 people in their contact list. The assumptions are for illustrative purposes (see note at bottom) but the point here is to show how powerful exponential growth can be, whether or not it is intentional.

WHO REALLY GETS TRICKED?

Admittedly, a careful review of the interface would reveal the user’s mistake. It’s hard to fault MessageMe. Though my requests for an interview were not returned, I assume their intent was not to trick anyone.

However, the example illustrates what makes the viral oops so troublesome. It is impossible to look into the minds of customers while they use an app. For all I know, MessageMe users intend to send the app to every single one of their contacts. But how would the app maker know if it was done in error? They wouldn’t.

A VIRAL OOPS NOT ONLY DECEIVES THE USER, IT FOOLS THE DEVELOPER.

Unlike an intentionally deceptive technique, where the user gets angry and stops using the product or uninstalls the app, with a viral oops, users blame themselves. They’ll most likely keep the app and move on with life. With no metric indicating the user’s unintended mistake, the app maker is none the wiser.

A viral oops not only deceives the user, it fools the developer. There is no way to know if the invite was sent in error. Without an understanding of why users share the app, developers are liable to gloss over significant shortcomings that must be addressed for the app to achieve long-term success. Given how easy it is for us fallible humans to believe convenient truths, it is too enticing to interpret growth as validation instead of a mirage.

MessageMe just happens to be the latest hyper-growth app making headlines; I could have picked any number of other cases. In researching this article, I discovered multiple examples of the viral oops in companies large and small, and I’m sure the comments section will uncover others.

Developers should make sure they know why people are sending invitations to others and not be guided by growth for its own sake. App makers would be wise to be particularly careful in encouraging people to invite others before users really know how the app works. For example, prompting invites at first login is a remarkably common and potentially specious practice.

For creative people working on exciting new technologies, growth feels great. But we should be cautious of using techniques that have a high likelihood of being viral oops instead of viral loops.

Note: The virality math assumes a starting base of 1,000 users and a daily cycle time of 1 with a 10% invitation acceptance rate.

Thanks to Jules Maltz and Max Ogles for reading previous versions of this essay.

Next Story — Should We Worry About the World Becoming More Addictive? Q&A with Nir Eyal
Currently Reading - Should We Worry About the World Becoming More Addictive? Q&A with Nir Eyal

Should We Worry About the World Becoming More Addictive? Q&A with Nir Eyal

Nir’s Note: This Q&A recently appeared on the 15five.com blog and it pulled out some thoughts I’ve been chewing on regarding technology, addiction, and our relationship with the products we use. I’ve edited it slightly and hope you find it interesting.

Should We Worry About the World Becoming More Addictive?

Question: Pokémon GO is all the rage right now. Can you talk about that in the context of a habit forming product? Is it negative or positive?

Nir Eyal: We have to think of technology in the broader context of the environment that we live in. The knee jerk reaction that always occurs with a new technology is that we don’t like it. We are averse to change and fear new technologies.

When you think about Pokémon (which is a lot less revolutionary than other technologies) in the context of what else people could be doing with their time, I think it’s pretty good. Pokémon can be considered one of the first mainstream fitness apps with wide appeal, that just so happens to be disguised as a game. You can’t play it sitting in your living room. Compare it to Clash of Clans or Candy Crush, that are not social and very sedentary.

Q: People are so engrossed in the game that they are actually getting injured. What is the difference psychologically or physiologically between habit and all-out addiction? Is Pokémon an addiction or just lack of awareness.

NE: A habit is just a behavior done with little or no conscious thought, about 40% of the behavior that you do every day is impulsive. Habits can be good or bad, but addictions by definition are always bad. An addiction is a persistent compulsive dependency on a behavior or substance that hurts the user.

There should be a rule that any sufficiently good and popular technology will form an addiction. But if a user is not harmed and the behavior is not something that the user can’t stop without assistance, then it’s not an addiction. When we look at Pokémon GO, it doesn’t really pass that test. It’s enjoyable, engaging, and habit forming. And yes, some folks won’t be able to stop and will become addicted. What to do about them is a different ethical question.

The good news is that for the first time in history, people who are making products that are potentially addictive can mitigate the harm. Addiction is nothing new, but now the maker of an addictive product knows who the addicts are. Distillers of alcohol don’t have that much insight into the identities or behaviors of end users, so there’s not much they can do for them. With companies who create products like Facebook, Instagram, or Pokémon GO that will create addicts, they could do something if they wanted to.

As I work with these companies and consult them, I know that those addicted are a small number, only 1–2% of the population. But for those small percentage of users I think these companies do have an ethical responsibility, and I increase awareness of this issue to encourage them to do something about it.

For most of us however, what most people flippantly call an “addictive product,” like Pokemon Go or Facebook, is just an engaging products. But would we want it any other way? No, we want products that we enjoy using. The vast majority of people know when they are using these products too much, and they opt to self-regulate.

Q: In Hooked you raise the ethical question of manipulation. Research is emerging that overuse of social media (if not outright addiction) has negative impacts on mental health. Couldn’t Google, Facebook, and Twitter get ahead of inevitable tech-burnout by advocating for something like an hour of downtime each day, even factoring the disruption to the revenue stream?

NE: What we’re seeing already is the proliferation of what I call attention retention devices — technologies specifically designed to block out the triggers and distractions from other technologies. Here are some examples that I use:

- DF YouTube is a Chrome browser plugin that gets rid of all of the videos on the sidebar of YouTube. This prevents me from watching one video after another.

- Facebook News-feed Eradicator prevents something engineered to suck me in, from distracting me.

- I never read an article on my desktop, I always save it to Pocket. The app removes all of the ads and links to other articles. I reward myself when going to the gym by listening to these articles later.

- I use Freedom, to block my internet while I’m writing. This prevents me from checking email or doing research when I should be thinking to get my work done.

Companies would be wise if instead of making it so difficult to leave sometimes, they would make it easier to moderate use. Instead of users burning-out and abandoning altogether, these companies can help us moderate.

This is the challenge of our generation, the first to grow up with interactive technology from birth. We are struggling with trying to figure out how to put tech in its place, even though it’s great and interesting and meets our needs so well.

Information today is no longer scarce. I’m a Gen-Xer, and when I was applying to college I received pamphlets in the mail boasting the size of their libraries. Today information is abundant, but knowledge and insight is scarce. To gain insight we need information, but also the attention and focus to process that information into knowledge. What will differentiate success from failure, and contributors from consumers, will be our ability to focus and control our attention. How will we think deeply and get our work done when there is so much distraction out there?

By the way, this is not really new. Socrates and Aristotle debated the nature of akrasia — the tendency to do things against our interests. We have always had distraction in our lives. When we have to do hard work, we try to weasel out. What has changed is the medium. Maybe for our grandparents it was reading a trashy novel. Maybe for our parents it was radio or TV. Today the new medium is interactive technology, but we’re not hopeless to fight it.

workbook horizontal CTA image rounded corners

Q: I deactivated my Facebook account this week, but I need to post to social media as part of my job. Any suggestions for managers to disrupt negative employee habits regarding social media? Are there any companies that impose these protocols?

NE: So your question is, “as a social media manager, how do I avoid social media?” (Nir and I laugh.) I think the deeper concern is not how to eradicate it altogether, but how to prevent it from creeping into areas of our life where it doesn’t belong.

There are all kinds of things you can do to address that. Speak to your employer about your company culture to see what’s expected. Are you expected to be at the company’s beck and call 24/7? If so you need to know that and maybe you’re not okay with it. Many employers will provide some guidance as to expectations of performance when managing social media and email over a specific time period each day.

Employees should discover how much time they are expected to do what Cal Newport calls Deep Work — that’s thinking and producing as opposed to reacting. You cannot tweet repeatedly while you are writing an article or working in your reflection time.

The other question that I think is more severe is, “what if I don’t like social media at all?” In that case, I don’t see a difference from picking any sort of profession that doesn’t comply with your preferences. For example, I like nature but I don’t like working outdoors all day. Being a forest ranger would not be a good career for me.

We should ask ourselves what suits our temperament. Just because something is a hot field, you don’t have to necessarily work in that field. And if you do like it, then keep it in your professional life and don’t let it bleed over into other segments like your personal time.

You may also enjoy reading:

Next Story — Who’s Really Addicting You to Technology? (slides)
Currently Reading - Who’s Really Addicting You to Technology? (slides)

The Four People Addicting You to Technology

A few months ago, I wrote a blog post titled “Who’s Really Addicting Us to Technology?” Recently, the Pokemon Go phenomenon has reigniting the question of technology’s role in changing behavior.

To put things in perspective, I wanted to share the main points of the article in a quick slide presentation below. Please let me know your feedback and if you enjoyed the slides, please share them.

If you enjoyed this, please click the green heart below!

Related articles you may enjoy:

Next Story — Die Dashboards Die! Why Conversations Will Reinvent Software
Currently Reading - Die Dashboards Die! Why Conversations Will Reinvent Software

Die Dashboards Die! Why Conversations Will Reinvent Software

In years to come, conversations will breathe new life into software — particularly the boring enterprise tools millions of knowledge workers begrudgingly use every day. Conversational user interfaces (CUIs) work because of our familiarity with messaging. Even the most technically complex interactions can look as simple as getting an SMS text when presented as a conversation.

There are three benefits conversational user interfaces have over traditional software and we believe these lessons can inform and inspire the redesign of countless online services. To illustrate the potential of conversational interfaces, we’ve reimagined what Google Analytics, one of the most widely-used (and widely-despised) pieces of enterprise software could look like as a conversation.

What’s it all for anyway?

Before diving into our redesign, it is important to consider some fundamental questions. What is enterprise software for? What job does it do for the user?

Fundamentally, enterprise software helps the user answer one or more of the following questions:

  • What’s important? (Surface relevant information)
  • What do I do next? (Support decision making)
  • How do I do it? (Facilitate action)

That’s about it! Not all enterprise software does all three, but it must do at least one. In the case of Google Analytics, the software is heavy on surfacing information in an attempt to answer the first question, light on decision support, and provides little in the way of facilitating the next action (with the exception of helping the user buy Google ads).

Interestingly enough, the conversational interface answers all three of the above questions better than the software tools we have today.

1. What’s important? (Surface relevant information)

Instead of having to sift through the drop-down menus, tables, functions, and buttons found in today’s software, tomorrow’s conversational interfaces will be able to send and receive messages in plain English. By simply asking a question via a conversational interface, the user will get the relevant information they’re looking for.

But what happens when the user doesn’t know what they want? What about the valuable insights trapped in the data?

With today’s traditional interfaces, like Google Analytics, an alert appears in the top right corner, annoying the user at best or ignored entirely at worst. Opening Google Analytics today reveals an intimidating explosion of charts and graphs full of data but short on insight. What does it all mean? Is the user in the red? Or is everything okay?

Like lots of enterprise software today, Google Analytics is a mess of charts and graphs.
Like lots of enterprise software today, Google Analytics is a mess of charts and graphs.

By using a conversational interface instead, Google Analytics would ensure important information isn’t ignored, making it more easily understood. For example, the mockup below informs the user of an anomaly, namely, that there was a recent spike in the number of visitors to the user’s website. That’s the same information presented in the Google Analytics dashboard, but with a very different effect on the user.

A conversational interface can present the same information as a dashboard but with a much more powerful effect.
A conversational interface can present the same information as a dashboard but with a much more powerful effect.

Dashboards today pump out data and expect the user to do the rest. However, tomorrow’s conversational interfaces will surface insights first, then back them up with data as needed.

Notice how Christina, the new face of Google Analytics, prompts the user with a question to move the conversation along. Christina could be a bot, a human, or hybrid thereof. It doesn’t really matter to the user as long as the job gets done.

2. What do I do next? (Support decision making)

In the real world, when two friends have coffee together, one might raise a topic to gauge the other person’s interest in further discussion. Perhaps catching up on how the kids are doing, how’s business, or a bit of gossip — we test interest to see what’s worth talking about. If the other party wants to talk about something else, it would be rude to stubbornly insist on only talking about one thing. However, that’s exactly what today’s software does. It keeps nagging us with topics we don’t care about because, unlike a good friend, it doesn’t care to learn.

A conversational interface however, can do something no ordinary dashboard can do; it listens and learns. By noting the user’s response to the discrete piece of information presented, the software remembers whether the insight was valuable. If the user continues the conversation about this information, the system learns the importance and raises similar concerns in the future. But if they don’t write back, great, that’s one less notification the app needs to send and one fewer interruption to the user’s day.

Unlike a traditional dashboard, the conversational interface gets better at its job of presenting relevant information the more it is used and therefore becomes a more powerful decision support tool. This concept is called “stored value” and is a key to building habit-forming products according to the Hook Model.

Artboard 1a

Furthermore, the conversational interface can learn from other users to improve the experience for everyone. For example, when Christina points out the spike in traffic is coming from Reddit, the information she presents isn’t just a statement of fact, she surfaces options to consider. To offer intelligent choices, Google could use the behaviors of other users to offer up the best next steps.

Artboard 1 Copy 7

In this example, the assistant suggests a resource for learning how to use Reddit effectively, prompts the user to join the conversation there, and offers to help fix the site’s high bounce rate to increase the number of users who stick around.

Helping the user figure out what to do next is hugely valuable. The easier the next action is to do, the more likely the user is to do it. The conversational interface easily surfaces the next best actions, saving the user time from hunting and second-guessing what to do next. By combining information from the user’s past conversations and other users’ actions, the new interface provides a better decision support tool to answer the question “What do I do next?”

3. How do I do it? (Facilitate action)

Finally, now that the software has elevated what’s important and given the user options to consider, it’s time to facilitate the actions the user wants to take. Unfortunately, actually getting the task done with today’s software requires navigating a hodgepodge of solutions on disparate screens and sites. A conversational interface can eliminate all of that.

For instance, in the example below, when the user asks Christina for help with the site’s high bounce rate, she suggests creating a custom landing page that welcomes visitors from Reddit. Setting up such a page is child’s play for someone who has done it before but for a novice it can be more work than it’s worth.

Thankfully, a conversational interface can get the job done behind the scenes in any number of ways. The assistant can offer upgraded services, summon in-house expertise, or incorporate an outside vendor. Instead of relying on the user to get up to speed on yet another software tool, the assistant turns to people or bots who already know what they are doing. The point is, unlike today’s enterprise software that requires the user to figure out how to help themselves (a task most people just won’t do) a conversational assistant can do the work by taking the path of least resistance.

Artboard 1 Copy 8

Here again, the conversational interface stores value every time a change is made to the site. With each page built or experiment run, the new Google Analytics learns more about the site owner’s goals and past results, making it easier to suggest improvements and making the service truly indispensable.

Die Dashboard Die!

Several workplace surveys have found we spend between 20 to 30 percent of our day looking for information. Even small reductions in the amount of time and effort spent digging around clunky enterprise software would yield significant dividends.

While not ideal for every use case, there are many benefits the conversational interface has over the enterprise software status quo. Fundamentally, it is better at answering what’s important?, what do I do next?, and how do I do it?

By adopting this more novice-friendly interface, tomorrow’s software has the opportunity to cure the dashboard fatigue infecting the enterprise. It also promises to make solutions accessible to people who just don’t have the time to learn new tools.

The future of enterprise software won’t be about complicated dashboards and mind-numbing amounts of big data; it will be about well-designed interfaces that make work a pleasure. Software should be like a good friend — ask and ye shall receive.

What do you think?

Will conversational interfaces kill the dashboard? What other software would be better with a CUI?

Nir’s Note: I co-authored this post with Lakshmi Mani, a product designer with a background in psychology, currently at Stride Health.

Thanks to Ariel Jalali, Shane Mac, Chris Noessel, Amir Shevat, and Matthew Woo for reading early versions of this essay.

Some other articles on the topic you might enjoy…

Next Story — “Think Different” is Bad Advice
Currently Reading - “Think Different” is Bad Advice

“Think Different” is Bad Advice

Nir’s Note: This guest post is an excerpt from the new book Invisible Influence: The Hidden Factors that Shape Behavior, written by my friend and Wharton School professor, Jonah Berger.

Being different, the notion goes, is the route to success. Think different was even Apple’s motto for a period. And Apple is often held up as a poster child of the benefits of this ethos. Conventional wisdom suggests that products like the iPhone and Macintosh succeeded because they were different from the rest. Steve Jobs was a visionary because he thought different from everyone else.

There’s only one problem with this advice. It’s wrong.

While the success of companies like Apple and Google is often attributed to them “thinking differently,” different ideas just as often fail miserably (remember the Segway, the Newton, or Google Glass?). Further, Apple and Google’s biggest successes actually came in areas where they were followers rather than leaders. Apple didn’t introduce the first smartphone, IBM did. Yahoo and AltaVista were doing search way before Google was. Research finds that almost 50% of market pioneers fail, and later entrants, or organizations that don’t enter a market first often end up being more successful.

So if being different doesn’t explain success, what does?

In the 1800s, a new innovation was introduced that had the potential to radically change transportation. At the time, most people traveled via horse and buggy. This was fine for shorter distances, but as cities grew, the method proved restrictive. It was slow, expensive, and even dangerous. The engine (horse) had a mind of its own, and fatality rates in large metropolises like Chicago were seven times what they are for cars today.

Gasoline powered vehicles promised a solution. These early automobiles could go farther, faster, and even cut down on manure, which at the time was threatening to suffocate many major cities.

But getting people to adopt what we now think of as cars required a huge mind shift. Horses (and donkeys) had been the primary transportation method for thousands of years. While there were many drawbacks to this method, people were comfortable with it. They knew what to expect. Automobiles were completely new. They required different fuel to run, different skills to drive, and different know-how to fix.

These changes required some getting used to. The first time people saw a carriage roll down the street without a horse in front, they were shocked. Rural Americans viewed this “Devil’s Wagon” as symbolizing the decadence of the city, and introduced restrictive laws to block its intrusion. Horses, skittish to begin with, were spooked by these loud, rambling horseless carriages and prone to run away, taking their passengers careening with them.

In 1899, Uriah Smith came up with a solution. The issue he realized, was psychological more than functional. Even if automobiles performed better, a horseless carriage was still hard to conceptualize.

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Smith’s Horsey Horseless

So Smith proposed something to make horses, and people, more comfortable. Named the Horsey Horseless, it involved taking a life-size replica of a horse head, down to the shoulders, and attaching it to the front of a carriage.

The buggy had the appearance of a horse-drawn vehicle, and thus horses, and their human riders, would be less likely to be scared when it passed by. The fake head also could be used as a gas tank.

It’s easy to laugh at a fake horse head glued to the front of a car. It seems silly, almost comical. But while it might seem ridiculous today, it’s hard to imagine how daunting and unconventional cars were when they were first introduced.

So rather than highlighting what made the automobile new and different, Smith did the opposite. He made the novel innovation seem more familiar. Similar rather than different.

Smith isn’t alone. Chobani has taken the yogurt market by storm. When they started, so-called Greek Yogurt made up only a tiny sliver of the yogurt market. Less than one quarter of one percent. Now Greek yogurt makes up more than 50% of the market. Chobani alone claims at least half that.

It’s tempting to attribute Chobani’s success to them being different from everyone else. But that’s just not the case. Not only weren’t they first to market, when Chobani came on the scene Fage had already been selling Greek Yogurt in the United States for almost a decade. Chobani succeeded not by being different, but by being similar to existing consumer tastes. In Greece, yogurt often came unflavored in large family size containers. But American consumers were used to buying single serving yogurt with fruit already mixed in, so that’s what Chobani offered. They reinvigorated the yogurt market by providing a healthier take on an old favorite (single serving yogurt with fruit already mixed in).

Turns out that being different doesn’t drive success, being optimally distinct does. Offering the right blend of similarity and difference. Successful innovations and ideas aren’t identical to what came before, but they aren’t completely different either. They mix familiarity and novelty, old and new.

The Toyota Prius succeeded not by going full electric, but making a gas powered car more energy efficient. Highly successful songs blend similar melodies with new lyrics. And high-impact scientific research is often grounded in prior work with a few unusual combinations of new ideas sprinkled in. Sure there is some difference, but there is also a lot of similarity.

Successful companies, products, and ideas, then, are a bit like Goldilocks and the Three Bears. Goldilocks is always turned off by the extremes. The firm bed is too firm and the soft bed too soft. The hot porridge too hot and the cold porridge too cold. But the middle is just right.

The same pattern often occurs with new products, services, and ideas. If something is too different, it requires such a shift in thinking or behavior that it often fails. The Apple Newton, an early predecessor to today’s iPhone, wasn’t just a new device, it was a completely new category. At the time, people had a hard time understanding why they needed it or how it would fit in their lives. The Segway faced similar challenges. Supposed to be a “game changer” in personal transportation, it was so different from anything else that people didn’t know what to do with it.

On the other extreme, if something is too similar, it doesn’t provide enough reason to change. If this year’s software is exactly the same as last year’s there’s no reason to upgrade. If a competitor’s product offers the same features at the same price, there’s no reason to switch.

But in between and it’s just right. Similar enough to what is already out there to evoke the warm glow of familiarity, but different enough to seem new and not simply derivative of what came before. Distinct, but optimally so.

Leveraging this Goldilocks Effect, or optimal distinctiveness, then is particularly important when managing innovation. When launching a new product like the Swiffer, how should it be described? Is it a revolutionary mop? A completely new cleaning category? And what about design? Should seats in driverless cars face forward because that is what people are used to, even if that is no longer required?

The same is true when introducing new ideas. Is it better to present a strategy as completely new, unlike anything the company has ever considered before? Or frame it as the logical progression from something being done already? Focus on difference or highlight similarity and difference at the same time?

Just like the Horsey Horseless, successfully introducing more radical innovations and ideas often involves making difference feel familiar. When TiVo introduced what we think of today as a digital video recorder, they had a similar challenge to the automobile. The technology was innovative and had the potential to create a completely new market. But tapping that potential required getting consumers to shift their behavior.

So to make it easier for consumers to understand the service, and help transition people from passive watchers to active content directors, TiVo designed their device to look like a VCR. A black, rectangle that sat below the TV or above the cable box, just like a regular VCR or DVD player would.

Pry open a DVR and a VCR and the guts are completely different. Digital video recorders don’t contain any film, so there was no need for the device to look anything like a VCR. It could have been shaped like a standard desktop computer, colored bright blue, or made into a pyramid.

But by using a familiar form, TiVo made people more comfortable adopting this radical innovation. By hiding the technology in something that looked visually familiar, TiVo used similarity to make difference feel more palatable.

Many digital actions today visually evoke their analog ancestors. We click on the icon of a floppy disk to save documents and drag digital files to be thrown away in what looks like a waste bin. eReaders have page numbers like physical books. Visual similarity also shows up offline. Digital cameras were designed to resemble film cameras and Edison designed the light bulb to resemble the existing technology of the kerosene lamp. All make the different seem more similar.

That’s not to say that difference is always bad. For incremental innovations, or ideas that seem unoriginal, highlighting differentiation helps. When Apple introduced the iMac in 1998, it featured only minor technological improvements. But from a visual standpoint it was radically different. Rather than the same old black or grey box, the iMac was shaped like a gum drop and came in colors like tangerine and strawberry. The design helped make similar technology more optimally distinct, and ultimately more successful.

For things that provide only a modest enhancement over current practice, emphasizing difference creates the needed novelty to encourage behavior change. But for things that provide a more marked change, embedding them within, rather than distinguishing them from, existing practice speeds adoption.

Too different and it’s unfamiliar, risky, and overly complex. Too similar and its boring, played out, and yesterday’s news. But in between and it’s just right. Optimally distinct. Maybe we could all learn a thing or two from Goldilocks.

Jonah Berger is a Professor at the Wharton School and bestselling author of Invisible Influence: The Hidden Factors that Shape Behavior. For free resources on driving sales and new user adoption, go to jonahberger.com.

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