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Anatomy of a good landing page December 17, 2010

Posted by jeremyliew in Ecommerce, UI, usability, viral.
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Both virality and direct response advertising are areas where getting the details right are critical. One element in both chains is the page on your website that a new user lands on (either from a friend invite, or from an ad.) Many developers don’t sweat the details on what they regard as “aesthetics”. Many designers focus more on making a page look good than getting users to do what you want them to.

Here is an ecellent “how to” that breaks down what a good landing page should look like.

(thanks startup digest)


Web based free to play game nuggets from GDC Europe August 21, 2009

Posted by jeremyliew in game design, games, social games, viral.
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Worlds in Motion has coverage of comments from senior figures from Zynga, Playdom and Gameforege speaking at GDC Europe about the free to play game market:

Gameforge co founder Kerstig noted:

Gameforge was formed in 2003 by Kersting and his partner Alexander Roesner as a developer of free-to-play browser and client-based MMOGs and has since released 15 MMOG titles in over 50 different languages. Their games have attracted over 85 million players worldwide and have nearly one million users playing at any one time…

“The challenge for publishers is to make it as easy as possible to get their games to gamers” says Kersting. Online distribution is a much better choice for both developers and users for numerous reasons – the cost of distribution “is close to zero”, access to media is easier and “the customer wants to get what he is looking for as easy and fast as possible”, according to Kersting….

He says gamers buy virtual items “for faster game progres, to enhance their gaming experience” and due to “vanity” — “so that they can say ‘I have the biggest house, garden etc.”

De Loayza from Zynga gives some tips on social game design:

The exec explained that the San Francisco-headquartered Zynga now has 15-20 million active daily users, which compares favorably to existing websites like EA’s Pogo.com, which gets a similar amount of visitors — but every month, not every day….

The Zynga exec noted that simplicity is the key to success for many social games. In fact, he said: “Make it less game, more social,” and it’s important to “focus on traffic as much or more as gameplay.” He cited a successful title like Kickmania, where the gameplay is a simple as ‘kicking’ a friend on a network, with leaderboards and other things layered on top. He also noted that often, the more straightforward mechanic is the better.

There are some particularly good viral-related game mechanics, says De Loayza, with gift giving being a particularly good way to alert other users and get them to join your game. He cited PopCap’s Bejeweled Blitz as a notably interesting example of competition as a viral mechanic, where users can team up to compete and win prizes.

In addition, crew mechanics on more standard ‘spreadsheet games’ like Mafia Wars, where adding friends to the game gets you to level up, can be a major growth factor. As for notifications, which are the way social network games communicate with your users, “use them as much as possible,” says De Loayza. He did acknowledge in the Q&A that what could be considered as ‘spamming’ does happen in the space, even as Zynga tries to keep their notifications useful.

How about the biggest mistakes you can make in the social network game space? De Loayza cited licenses, commenting: “I am not convinced that licenses necessarily work in this space… people just don’t seem to be that interested in it,” as well as linking to a destination site outside the social network, which “breaks the viral loop.”

Meretzhy from Playdom also had some tips on building virality and monetization:

He explained that the key issue of virality, or how to get your game to reach the widest possible audience, can be achieved using several popular mechanics. Game requests, active “wall-posts” and passive notifications are the favored methods where players are prodded to beat each other’s scores, join each other’s mobs or exchange gifts.

However, Meretzky pointed out that it’s not as easy as simply applying these mechanics: “Virality is made more complex by nearly everything falling outside of the terms of service,” making it necessary for a user to be in constant contact with the social networks.

Recently other methods have emerged to further the viral nature of social games.Farmville, Zynga’s hugely popular new Facebook game, uses a combined gifted invite method in its “lost cow” mechanic. When a cow wanders on to your virtual farm you aren’t allowed to keep it yourself, but can send it to a friend to get them started. This type of invite has a much higher acceptance rate than the standard message invite.

Another new mechanic brought in by Big Fish Games in their social game Restaurant Empire is the “be my employee” system, where you can task your friends with jobs in your restaurant. This system has two ways of hooking players: either your friends want to return the favor by employing you, or they want to seek revenge if you have given them a demeaning task. How do they get this revenge? By employing you in their restaurant to perform the same (or even a worse) job…

Meretzky was quick to point out though that, “monetization follows engagement.” In order for the player to start spending money in the game they must be very engaged and invested in it.

Meretzky detailed some of the way to get players to re-engage with a game, including login rewards, collecting stores of money that will not increase over a set amount, harvesting, and notifications of friends beating your high score.

He said of the high score mechanism that when you see a friend has passed you on a leader board, “the natural inclination is to jump right in and pass them right back”, clearly a very strong re-engagement technique.

Median # of tweets = 1 June 3, 2009

Posted by jeremyliew in retention, twitter, viral.

Fascinating study in the Harvard Business Review about twitter. It looks at 300,000 users and covers differences in behavior between men and women, # of followers and # following. But most interestingly, it looks at usage:

Twitter’s usage patterns are also very different from a typical on-line social network. A typical Twitter user contributes very rarely. Among Twitter users, the median number of lifetime tweets per user is one. This translates into over half of Twitter users tweeting less than once every 74 days.

At the same time there is a small contingent of users who are very active. Specifically, the top 10% of prolific Twitter users accounted for over 90% of tweets. On a typical online social network, the top 10% of users account for 30% of all production… This implies that Twitter’s resembles more of a one-way, one-to-many publishing service more than a two-way, peer-to-peer communication network.

The fact that half of twitterers have tweeted once or less, and that 75% of twitterers have tweeted four times or less is quite astonishing. It is consistent with Nielsen’s finding that 60% of Twitter users don’t come back the next month.

With Facebook apps we have sometimes seen amazing growth driven by virality, followed by a dip towards a more sustainable level of usage. When you are viral, a good portion of unique users are going to the site to sign up for the first time. But if they don’t stick, then you can see a “shark fin” shaped curve, as Andrew Chen has posted about in the past.

Twitter is not just another Facebook app. Unlike many of the “flash in the pan” apps, Twitter is a verb, and has entered the popular consciousness. The very high usage of the top users (90% of tweets from 10% of users) also suggests a different model. But it will be interesting to see how twitter usage continues to grow over the next few months

Social gaming is a tactic not a category March 25, 2009

Posted by jeremyliew in business models, games, games 2.0, gaming, social games, social gaming, viral, viral marketing, virtual goods.

I’ve been blogging a lot about social games over the past couple of years and have been a big proponent of the space. However, over the last few months I’ve started to question whether social gaming is a separate category at all. I now believe that the true category is free to play gaming, and that social gaming is simply a tactic (albeit a very important and differentiating tactic) within this category. Although I’ve been saying this in private a fair bit recently, I brought it up at the VC panel at Gamesbeat yesterday and I hear that it caused a bit of a stir. Rather than being quoted out of context in 140 characters, I thought it would be helpful to explain how I came to this view.

At the most basic level, free to play games (with a digital goods or subscription upsell model) need to focus on only two metrics, Lifetime Player Value (LPV) and Player Acquisition Cost (PAC). If LPV > PAC then you’ve got a business. If not, you don’t. This applies to flash MMOs, virtual worlds, facebook games, asynchronous text based MMOs, client downloadable games, myspace games and a whole host of other games, with the key unifying element being the business model, and the importance of those two statistics, LPV and PAC.

The term “social gaming” has been used in two main, and related, ways. I think that both of these definitions are potentially limiting. The first has been to describe games that are played (and spread) on social networks. The second has been to describe games that spread virally, with a PAC of zero because current players invite new players with a K factor above 1.

Let’s start with games played on social networks. This is a terrific distribution tactic as open platforms and distribution are opposite sides of the same coin, and as I’ve said in the past, in the early stages of a new category distribution is the key driver of success. Free to play gaming is certainly in it’s early stages, with many games having to create demand versus simply fulfilling demand. But there is no reason why these games have to be limited to only social networks, and indeed companies like SGN and Zynga have already started to port their games to other platforms including the iPhone and the open web. Social networks offer an easy starting point for new free to play games because of the large concentration of potential players, but there is no reason for free to play games to stop at social networks.

Now lets address viral growth for games. Obviously, this is a wonderful characteristic. It is the cheapest possible channel for player acquisition as with a PAC of zero, you can make money at any level of LPV. However, once again, there is no reason to limit your player acquisition channels to viral growth. You should acquire new players through any channel where your PAC < LPV. For some game developers this is a religious issue; viral is best and nothing else is acceptable. I disagree with such a fundamentalist approach. If your LPV is high enough to allow you to buy users through advertising, distribution deals, search marketing or any other channel, then you should. Mark Pincus, the CEO of Zynga, has been preaching this approach since early 2008. Here is an excerpt from my blog post from the social games panel that I moderated at the Graphing Social Patterns conference in March 2008:

We next talked about how social games can grow. Viral growth has obviously been the key driver of growth up to this point for all the panelists. Shervin noted that they had seen a strong positive correlation between App Rating and rate of viral growth – high quality games spread faster. Mark talked about the importance of supporting a game with advertising, especially at launch.

One reason that Zynga is the largest social gaming company today is that they have been able to afford to promote their games on both Facebook and Myspace, and have done so aggressively.

Obviously, building social factors into games is increasingly important. Multiplayer is the “user generated content” of games, and social interaction is a key part of that. Furthermore, even if your K factor is less than one, it can be a very important force multiplier on your player acquisition. Buying one player if your K factor is 0.8 means that you will generate 5 new players, and this can dramatically average down your PAC, even if it doesn’t take it all the way down to zero.

In conclusion then, I find the term “social gaming” to be limiting. The best publishers and developers of free to play games will make frequent use of social gaming tactics, but they will not refuse to go beyond social networks and viral channels to grow to their full potential.

I’d be interested to hear what you think.

An excellent excel model of viral growth March 10, 2008

Posted by jeremyliew in business models, churn, models, retention, social media, viral, viral marketing.

Last week Andrew Chen wrote an excellent post about the growth and potential decay of viral apps. Rather than just focusing on the elements of viral growth, Andrew also took into account the declining likelihood of an accepted invitation as you saturate a population, and the impact of churn. He provided a useful model to social media founders who are trying to estimate their growth, and what can go wrong when a viral app “jumps the shark”:

shark fin

He notes:

* Early on, the growth of the curve is carried by the invitations
* However, over time the invitations start to slow down as you hit network saturation
* The retention coefficient affects your system by creating a “lagging indicator” on your acquisition – if you have good retention, even as your invites slow down, you won’t feel it as much
* If your retention sucks, then look out: The new invites can’t sustain the growth, and you end up with a rather dire “shark fin.”

I think this is a very useful model, but that it doesn’t quite predict what we typically see in real life. Rather than dropping to zero, failed viral apps typically hover at a steady level much lower than their peak. Since Andrew made the model available under “copyleft”, I made a small edit to his model. Rather than treating churn as a constant percentage of users in each time period, I treated it on a cohort level, with a higher churn rate in the early periods and lower churn as time goes on. This is similar to the churn profiles seen for subscriptions businesses such as AOL’s ISP business. (I was at AOL from 2002-2005 as SVP of Corporate Development, and then as GM of Netscape.) This model better matches active user graphs that we typically see for failed viral apps.

churn by cohort

If you’re interested, the model is available for download here. Viral growth assumptions are in the yellow cells on the “viral acquisition” tab and churn assumptions and output are on the “user retention” tab.

Games 2.0: Asynchronous gaming November 29, 2007

Posted by jeremyliew in asynchronous gaming, business models, casual games, facebook, game mechanics, games, games 2.0, gaming, user generated content, viral, viral marketing, web 2.0, widgets.

I am not a hard core gamer by background; more of a casual gamer. But casual gaming is now widespread; we’re all gamers now. My interest in the area has grown out of my interest in social networks and social media. I’ve long noted the increasing application of simple game mechanics to social web sites and how this can meaningfully increase the levels and types of interactions that users have with each other and the site.

As an investor in Flixster and Rockyou, both highly viral Facebook and Myspace “app” and “widget” makers, I’ve been tracking closely the spread of emergent user behaviors in these social networks. One Facebook app that really caught my attention is Scrabulous, an online scrabble game that can be played asynchronously, ie players don’t all have to be online at the same time.

Online multiplayer games have long been popular at all the big casual games portals. Multiplayer gaming can be viewed as user generated content for games, one of the drivers of Games 2.0. These games typically have a “lobby” where players can meet and match up before entering into a game against each other in real time.

Making the gameplay asynchronous fits better with the “continuous partial attention” world that we increasingly live in. The reason I never became a hard core gamer is that the serial monogamy requirements (one game at a time, total dedication, long periods of gameplay coordinated with others) doesn’t mesh well with my lifestyle. Scrabulous is a better match for the “play a little bit when you have some time, at various points throughout the day” life that many of us lead. Single player casual gaming (whether Bejeweled online or Brickbreaker on the Blackberry) has been filling that need for many players. These are fun, and at least have the “high score” dynamic, but they lack the social aspect that turn based asynchronous games offer.

Asynchronous games also make it easier to play against friends. You don’t have to coordinate to be online at the same time. Playing friends makes games more fun, and gives them a social aspect (the games have context if you have an ongoing relationship with an opponent). Playing with friends also offers an opportunity for true viral growth for the game, as players invite their friends to play.

Although these turn based multi-player games (especially those derived from boardgames) have some social dynamic, they lack the breadth of social interaction of synchronous MMOGs (not just the direct social interaction, but also the perfomative aspects of gameplay) that help make them such compelling experiences. Part of the appeal of MMOGs (whether World of Warcraft or Puzzle Pirates) is knowing that you’re “in game” with thousands of other people at the same time, each of them interacting with the same universe that you are.

So what would an asynchronous massively multi-player game look like? It can’t be turn based because most players would spend most of their time waiting for someone else to move. That’s not fun. It would have to be time based instead. Players would need to make their moves against a real world clock. Games like Duels.com (swords and sandals PvP fighting game), Manager Zone (soccer manager game) and Kings of Chaos (real time strategy game) all employ this dynamic. Massively multi-player games offer even more opportunity for viral growth because a players invitation ability is unbounded by the number of seats at a board game.

This led to me think about games using the framework below:

narrow games framework

I think that we’ll see a lot more innovation in the two sections of asynchronous multiplayer and massively multiplayer games over the next few years. I’m actively interested in investing in these areas. What are the most interesting such games that you see?

Web 2.0 has been driven by variablization November 26, 2007

Posted by jeremyliew in advertising, business models, distribution, platforms, viral, viral marketing, web 2.0.

The last couple of years have seen an explosion of innovation on the web that has broadly been labeled Web 2.0. There has been a lot of debate about what exactly constitutes web 2.0 but what hasn’t received as much attention has been what changes have enabled these Web 2.0 companies to arise – what is different now from the mid 90s and Web 1.0. I think the change can be summarized in one (somewhat clumsy) word: Variablization.

Variablized Development Costs

In the 90s we used software development models, primarily waterfall models, where a usable product wasn’t available until close to the end of the development period. Most code was written from scratch, with little reuse or public domain code, and large teams were necessary.

With the popularization of agile programming methodologies, widespread use of open source software, greater ability to use offshore development resources on a consulting basis, and a culture of “open beta”, the costs of developing a website or web service have become both lower and more variable. Ideas that look promising but fail to capture user interest in beta can be identified much earlier and at much lower cost, and resources can be shifted to more promising avenues.

Variablized Content Costs

In the 90s almost all content was created by professional editors and writers, employed by companies. To launch, they had to create a critical mass of content, which cost a certain amount.

Recently, with lower expectations out of beta products, the widespread adoption of user generated content and emerging best practices in how to use user generated content, the costs of content creation have dropped dramatically and become variable.

Variablized Marketing Costs

In the 90s, there were only two ways to get a large number of users. The first was offline marketing – the famous Pets.com superbowl ad approach. Expensive, and with a high minimum level of spend required to break through the clutter. We all know how that worked out.

Overture and Google have changed that landscape. Their CPC model means that you can spend as much as you choose to gain new users, and that your marketing spend can be completely variable.

Variablized Distribution Costs

The second way to get a large number of users in the 90s was to get a distribution deal with one of the big portals – AOL, Yahoo or MSN. In those days, this was the only way to reach a large number of internet users effectively, and you typically had to sign up for a multi year, multi million dollar deal to do it.

As social network platforms open up, and as the basic principles of viral marketing become better known, distribution has become variable, if not free.

Variablized Monetization

The vast majority of Web 2.0 companies rely on advertising as their business model. I think this is because advertising is the one business model that has become variable (relative to the 90s). Back then, to sell online advertising, you both needed to have substantial scale, and you needed to have your own sales force.

Today, thanks to ad networks and CPC contextual targeting (not just Google’s adsense, but also Quigo, Yahoo’s Publisher Network and others), even the smallest of websites can start earning advertising revenue.

There have not been equivalent innovations for subscription and ecommerce business models, and as a result, we’ve seen far fewer web 2.0 companies that use those models.


These changes in cost structure are a useful lens through which to view the current startup environment. It’s been said before that it is cheaper to build a company than ever before. While that is partially true, it is not the whole story. Digg has raised over $10m, Youtube over $12m, Photobucket and Rockyou (a Lightspeed company) over $15m, and Facebook has raised over $275m. (With the exception of Facebook) while these are lower than the amounts raised by companies in the 90s, they are still large numbers. Variablization of costs only makes costs go away when usage is low. In other words, while it still takes money to succeed, it is cheaper to fail than ever before.

Luckily for VCs like me, that means that successful companies will still need to raise money!

Social Design Best Practices November 5, 2007

Posted by jeremyliew in business models, facebook, game mechanics, google, myspace, open social, product management, social media, social networks, viral, viral marketing, web 2.0, web design.
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Bokardo notes a set of social design best practices as recommended by the Google OpenSocial team:

1. Engage Quickly – (my interpretation: provide value within 30 seconds)
2. Mimic Look and Feel – (make your widget look like the page it is in)
3. Enable Self Expression – (let people personalize their widgets)
4. Make it Dynamic – (keep showing new stuff)
5. Expose Friend Activity – (show what friends are doing)
6. Browse the Graph – (let people explore their friends and friends of friends)
7. Drive Communication – (provide commenting features)
8. Build Communities – (expose different axes of similarity)
9. Solve Real World Tasks – (leverage people’s social connections to solve real problems)

Worth reading the full text from OpenSocial

Viral marketing, randomness and the difficulty of controlling growth in social media September 13, 2007

Posted by jeremyliew in communities, Consumer internet, social media, social networks, viral, viral marketing.

I recently met the CEO of a company who claim to be one of the most popular social networks in Turkey with several million monthly visitors from Turkey. This happened by accident – the founders are Americans who have no prior connection to Turkey.

This is just one of many examples of how difficult it can be to predict or control the growth of viral social media. Google’s Orkut, is a better known example – a social network started by a Turkish engineer working in the US that now dominates in Brazil and India. Friendster and hi5 fall into this bucket as well. As I’ve noted before, the online advertising market in the US is bigger than that in the rest of the world combined. The senior management of these companies know this, and all would love to see more US traffic, but it is now beyond their control.

The reason is the mathematics of viral growth. If the viral coefficient (the number of additional members a new member brings) in a population is less than one, it grows but eventually hits a ceiling. But if the viral coefficient is greater than one, it grows unbounded. Although your social media property may start in many different populations, it will come to be dominated by those with the highest viral coefficients.

This is best demonstrated by example. Consider a new social media property with 30 members, 10 each from three distinct populations; call them Pinks, Purples and Greens. Suppose that by luck and because of the initial users, the viral growth coefficient for the Pinks is 0.6, for the Purples is 0.9 and for the Greens is 1.2. Watch what happens to the populations over time:


All three groups are initially equally represented, But already by time period 4 the population is more than 50% Green. By time period 10 it is more than 75% Green and probably considered a “Green social network”. By time period 16 less than one member in 10 is not Green. For Green now substitute whatever national, language based, religious, racial or other demographic grouping that you choose.

These evolutions can happen very fast since a time period is the time it takes for a new member to invite more members. 2-8 weeks might be a reasonable assumption.

This example is vastly simplified, of course. Viral coefficients vary over time within and between groups. Viral coefficients also don’t vary quite as much between groups; the same underlying feature set is being exposed to all groups. But it illustrates the point that randomness can play a significant role in the eventual makeup of a social media property’s user base.

I posted about a similar finding in May, how you don’t necessarily get the wisdom of crowds, but sometimes just the crowdiness of crowds. It was based on a NY Time’s article that showed how randomness can have a big impact on the most popular songs for a crowd when popularity information is public.

Improving copy; an easy way to increase user interaction August 5, 2007

Posted by jeremyliew in Consumer internet, copy, interaction, Internet, usability, viral, viral marketing, web 2.0.

Wired’s August edition has a good article about how newspapers are putting their readers to work which is worth reading. But one section that jumped out at me has broader applicability:

A GetPublished! button features prominently on many Enquirer Web pages, and the submissions land in Parker’s queue. They almost never resemble anything commonly considered journalism.

“It used to read, ‘Be a Citizen Journalist,'” Parker says. “And no one ever clicked on it. Then we called it ‘Neighbor to Neighbor,’ and still nothing. For some reason, ‘Get Published’ was the magic phrase.”

Changing copy can make a huge difference in your level of user interaction.

Direct marketers have known about the importance of good copy for years. Good email marketers constantly test and refine subject lines to improve open rates. Many best practices in email marketing subject lines have evolved that are often directly applicable to other areas. The same is true of the best lead generation businesses who are constantly tweaking their landing page copy and form-fill flow to maximize the completion rate.

Copy can improve interaction rates in media businesses as well as these more transactional examples. Another example is in social media optimization (an element of search engine optimization). For example, this list of the top 101 advertising headlines ever written (top 10 excerpted here):

1. They laughed when I sat down at the piano – but when I started to play!
2. They grinned when the waiter spoke to me in French – but their laughter changed to amazement
at my reply.
3. Do you make these mistakes in English?
4. Can You Spot These 10 Decorating Sins?
5. How a “fool stunt” made me a star salesman
6. How a strange accident saved me from baldness
7. Who else wants a screen star figure?
8. Who else wants a lighter cake – in half the mixing time?
9. Free to brides – $2 to others
10. Free to high school teachers – $6 to others

may seem dated, but many of them follow the same rules for headlines that help your article get Dugg today.

Email virality and other forms of viral marketing can also often be tuned and improved through better copy. When dealing with email invitations from friends, more social messages may be more effective than the hard-sell/call-to-action type copy of the examples linked to above. For example, Flixster (a Lightspeed portfolio company) asks in the email subject:

Do we like the same movies?

while Tagged‘s subject line is

[Friend] has Tagged you 🙂

In both cases the actual copy is important, but more important is the fact that the companies constantly A:B test their copy to optimize and improve their conversion rates.

The takeaway here is that, although technology startups full of top notch engineers often look to improving the product to improve user interaction rates, sometimes something as simple as a change in words can have much the same result.

I’d like to hear from readers of examples of how small changes in copy improved their user interaction rates. [Note the call to action!]