i want obsessive usage from our users to happen.

To summarize this post:

• Gaining users is great, but preventing the loss of users is also very important
• Creating a sharkfin graph on your traffic means exponential descruction of value
• Critical mass plus network effects implies that complete collapse of networks is possible too

Every consumer internet company needs to think about user acquisition, even if the site is built to be viral. You need to bootstrap user base, content, and all the other neat effects that kick in when you hit 50k+ users. This is obviously true in the case of social media sites that depend on UGC content.

I’ve been looking for a list for how people go about acquiring users, and I haven’t found a great one. So here’s a group of obvious, standard strategies to acquire users, and details about a couple of them.

10 (obvious) strategies to acquire users

1. Email/IM features for invites and content
 2. Blog/MySpace widgets
 3. Auto-invite for email, social networks, etc
 4. Auto-embed for blog widgets
 5. A/B tested signup pages
 6. Smart adwords buying
 7. Viral referrals
 8. SEO/landing page generation
 9. Push through RSS/Email, etc.
10. Reduce user "drag" through the entire funnel

Let’s drill into more details.

1 – Email/IM features for invites and content

It’s obvious that you need to make it very easy to share content, invites, and other things for your site. So anything that might be an e-mailable article or detail page, put an “Email this to a friend” link there. Same for invites. And don’t have it just be e-mail, remember that lots of people use IM and you can use “aim:goIM” as a prefix to make it easy to send it to a AIM buddy.

2 – Blog/MySpace widgets

Another super obvious feature is to widgetize the most core content on the site, and allow people to embed it into their blogs. They might do that because your site is solving something they want for their site (music-sharing/chat/slideshows), but it might also be something to help them make the site more sticky or content-rich (popular links, interesting news, etc.)

3 – Auto-invite for email, social networks, etc

This is not new, but requires a bit more work. In the case of Flixster, after you sign in, it recognizes that you’re a hotmail.com or gmail.com or whatever user, and asks you for a username/password for that e-mail service. If you agree, it’ll go through and invite users from your address book and folks you’ve corresponded with. Annoying, but a great way to blast several hundred people all at once.

4 – Auto-embed for blog widgets

Same for blog widgets – why trust users to copy and paste when you can get their MySpace credentials, save them, and make it a 1-click experience to add your widget to their spaces?

5 – A/B tested signup pages

Using one headline versus another can create a 5x difference in signup percentages. If you want to make sure you’re not using a bad one, make sure you A/B test your signup pages. Try different value propositions – focus on Free versus Sharing versus MySpace versus whatever Web 2.0 proposition you have. Try them out, and keep a hidden field in the signup on the source. Then track them over time to see what works.

In fact, before you even launch your product, you can build a landing page through something like Survey Monkey. Then, drive traffic to it, and see how people respond to differences in layout, headlines, copy, and others.

Offermatica is the king of this kind of stuff. If someone would like to build a long-tail version of this used by bloggers and such, that’d be a great business.

6 – Smart adwords buying

Once you start getting content, you can get a lot more creative on search keywords buying as well. A lot of people don’t know what keywords to buy, but you should realize that you want to buy literally 10s of thousands of keywords. If you’re a music site, obviously you want to buy things related to “music” but you also want musical genres, artist names, CD names, etc., etc. In fact, once you get some content from your users, you’ll want to take that data and process it for keywords. If you were a fashion site, you want to be buying fashion brands, celebrities, genres, item names, etc.

The folks at comparison shopping engines are complete masters at this, since it’s not easy to score what keyword combinations are the best, and which ones drive the best ROIs.

A good place to understand where you should start is to look at Google referrals and what keywords people are already coming through as.

7 – Viral referrals

Why should people invite people to your site, other than the fact they love your content? Well, people create these incentives in a couple ways – if your site is invite-only, then people give each other value through the invites, regardless of whether or not the sites are good. If your site is like LinkedIn, and it provides a way to manage contacts, that’s another great inherent way to generate e-mails. One interesting vector on MySpace, from people I’ve interviewed, is oftentimes their experienced friends set up their accounts so that they have a way to keep in touch more easily. A lot of thinking can be put into the viral nature of sites.

8 – SEO/landing page generation

When it comes down to it, every site is really divided into two groups – first, you have the sticky audience that is there because they are part of your core userbase. Then, secondly, you have newbies that are coming into your site because of Google. Often the latter is much bigger than the former.

A great question to ask, then, is the following: How do you create more landing pages and opportunities for people to stumble onto your site?

For that, you need to make sure that the titles of your pages reflect the item you’re viewing detail on. You also want your URL to do the same. You want to add links to other sites when appropriate, and syndicate interesting content. Another SEO tactic is to actually generate landing pages that may not even be user-accessible, but rather, just for bringing in folks from Google. This is yet another deep area where you can spend a lot of money.

9 – Push through RSS/Email, etc.

Obviously, another great way to create stickiness is to offer RSS feeds and e-mail subscriptions for everything. This makes it so that people can disengage from the site, and weeks later come back. Emails also offer the great artifact that people will forward them on to friends, if you offer enough content.

10 – Reduce user “drag” through the entire funnel

A bunch of the above points have to do with how you squeeze more people into the top of the funnel, but a final point is that it’s important to optimize (and A/B test) across many different points in the funnel. For example, if someone’s password is too short, you want to alert them immediately, not once they hit submit. If your login forms are multi-step, it’s better to hide the optional stuff and ping them slowly later on. Once they’ve signed on, give them something to do so that they are immediately having fun, rather than leaving the site since there’s nothing to do.

Conclusion The above is a pretty basic list! Feel free to add additional strategies in the comments.

Does everyone remember Metcalfe’s Law? It was formulated by Bob Metcalfe, the inventor of Ethernet and co-founder of 3Com, who stated:

The value of a network is proportional to the square of the number of users of the system (n²).

For those that are interested in the math behind it, basically the idea is that if every new node in the network connects with every pre-existing node, then as you gain nodes, you non-linearly increase the number of connections that everyone has with everyone else.

That’s pretty neat, and for the social networking folks who are aggregating large audiences and treating their businesses like communication utilities, it’s both logical and helpful to think that these social communities abide by network effects like Metcalfe’s Law. In fact, it’s a DIRECT reason why these networks want to get as big as possible, and have a social graph that’s as comprehensive as possible, and why they should ultimately be opposed to Data Portability. And I think we’ll see these players’ strategies ultimately reflect these strategies.

But Metcalfe’s Law can also affect social app creators. Let’s discuss how this might play out for folks who are building apps on social platforms, rather than operating the social platforms themselves:

“Jumping the shark” and Metcalfe’s Law In a previous post, I wrote a bunch about how dangerous (and easy) it is to jump the shark in an enclosed space like the Facebook Platform.

Here’s the good scenario: Let’s say that you retain users well, and you don’t get a sharkfin graph on your traffic. In that case, if you combine the two ideas – Metcalfe’s Law and with the viral loops on the social platforms – you can imagine that in the success case, you are creating N^{2 value with very large N.}

For folks building application on Facebook, Opensocial, etc., it’s nice to think that your new app is gaining value much faster than if you built your own destination site. This allows you to get the N2 benefits of Metcalfe’s Law without incurring significant costs of acquisition as you scale N up to a large number. This the best of both worlds.

Let’s consider the other case, where your app’s retention sucks, and you are going through the sharkfin graph of rapidly acquiring users, hitting a peak, and then falling down:

(scroll past the image for more)

Now all of a sudden, Metcalfe’s Law works against you – for this, I will introduce the corollary, Eflactem’s Law.

Eflactem’s Law Funny enough, everyone always talks about Metcalfe’s Law like it’s a good thing, and they say that because they assume that N is increasing! But let’s consider the opposite: If Metcalfe’s Law says that your network grows value competed by N^{2, then Eflactem’s Law states the reverse. It says:}

As you lose users, the value of your network is decreases exponentially (doh!)

That is:

• If you have 100 users, and then grow to 200 users, your “value” has increased from 10k to 40k.
• But if you START with 200 users, and end up with 100, then you are going from 40k in value to 10k in value.

And that sucks. Perhaps this should be called Murphy’s Law instead?

In fact, you see this happen all the time at dinner parties or events. Things are great until one or two people announce the intention to leave. If those folks are fun and entertaining, there’s an immediate realization that the quality of the experience is about to go down. And yet more people announce their intention to leave, and so on, until you are left with the party hosts and a big mess ;-)

Advanced discussion: Social Network Death Spiral Now let’s do a more advanced discussion using the concepts above – for some new readers, this discussion might completely be incoherent ;-)

Let’s consider a specific scenario where a social network could easily start to “Death Spiral” – here’s some set up on the scenario:

• You have a bunch of users, let’s call the total number N
• The total number of users in the ecosystem, called the carrying capacity, is variable C
• These users all individually require some utility value on a site, let’s call this V_required
• Then there’s a retention %, called R, which depends on two factors: o If the utility value for users is satisfied, that is, V > V_required, then R close to 100% o If the utility value drops under V_required, then R is crappy, closer to 0%
• And to borrow Metcalfe’s Law, the value of the network is calculated at V = N2

So the scenario is that as the total users for the application reaches the carrying capacity, you basically hit a point of maximum saturation – this is defined by the ratio N/C. Sometimes this ratio can also be referred to as the “efficiency” of a user acquisition process, which relays how many people you actually acquire versus the universe of all users. (Obviously you want this to be as large as possible)

Once you hit the carrying capacity and acquire all possible users, N is at the highest point, and thus the network value is also at its highest point, V = N_max^2. Similarly, because the network value V is at its highest, the retention reaches its highest point as well.

The question in this scenario is, at any point during the growth of the network, does the network value V exceed the required value of the site, which we call V_required? Does the network break through the critical mass of value?

If so, retention should be great, as defined by the explanation above. In fact, maybe you reach V_required early on during the growth of the site, which makes the acquisition process much more efficient. Early on, maybe the userbase wasn’t sticking, but a critical mass threshold is met, and suddenly the entire userbase sticks, which creates a long-term creation of ad impressions and company value.

However, if you don’t reach the required value in the network, then you’re pretty much screwed. Then the retention sucks, since the users aren’t finding value, and some percentage of them will leave. This will then remove more value from the system, causing yet another round of users to leave. This continual loss of users is a death spiral that collapses your network in fine Eflactem’s Law style.

A very interesting variation of this is when you apply Metcalfe’s Law not to the entire network of users, but rather think of a social network as a loosely grouped set of connections. In that case, some local networks might have achieved critical mass, and if they are big enough, they will be retained. However, if the smaller networks around any given group start collapsing, then sometimes even the large networks will get pulled down with them.

5 factors that determine your advertising CPM rates

An interesting post at Techcrunch: Pubmatic Data Suggests Small Sites Command Higher Rates For Remnant Ads Than Large Sites.

I love seeing this cross-site ad monetization data, since it’s rare to get your hands on it unless you work for an ad network. For people outside the ad industry, advertising CPMs seem like black-boxes.

How to guess CPMs – 5 factors At Revenue Science, a regular game of mine was to eyeball a site and guesstimate the CPMs.

A couple of the factors that I’d use:

1. Is the site "sticky" or is it a one-hit wonder (like a reference site)?
2. Is the site pretty general, or is it in a particular category (like cars)?
3. Who uses the site? Everyone (including international) or just US?
4. How dependent is the site on Google SEO versus a community site that draws people back?
5. How many pageviews does the site have? Is it a lot? Or is it a small amount

Easy to monetize, hard to monetize For the people who are curious, this is the easiest to monetize:

One-hit wonder site that exist in a particular category, are based in the US, and have lots of search traffic

In particular, your site is likely to have high CTRs since people are in a “transactional” mode. If you have all of those, and have a ton of pageviews, then you’ll make a ton of money.

The hardest to monetize?

Highly sticky sites that are general (like communication), based 100% outside of the US/Europe/Japan, with lots of pageviews

In a setup like this, not only are people unlikely to want to buy anything, even if they did, there’d be no way to make money off of this group.

Example categories As a rough rule of thumb, I’d typically guess the following – these are very rough approximations, just to illustrate a couple points:

• Social sites (forums/chat/etc) without direct ad sales teams: <$0.25 CPM
• Largely international sites: <$0.50 CPM
• Medium-sized sites that use banner ad networks: <$1 CPM
• Reference sites in a specific category: >$5 CPM or sometimes much higher, depending on category – we ran into home improvement reference sites that did $20 CPMs

Because we were mostly dealing with so-called “remnant” advertising, these numbers are likely to be at the bottom of the range for these sites. That is, social networks might quote a CPM of $20 CPM, but what they really mean is that 1% of their inventory is sold at that, and the rest of the 99% is sold at <$0.25 prices.

As you can see, as a website property, you fall into either of two categories:

• Horizontal sites used daily which command low CPMs with huge pageviews
• Vertical sites that capture user intent – often used intermittently (with lots of traffic from search) with high CPMs and low pageviews

Horizontal sites, when scaled up to a large enough site, can employ direct ad sales teams that raise the CPM by a significant amount, but the entire process is demand-constrained.

Google is lucky to be both horizontal and vertical – it’s used everyday by people, but also captures user intent.

As stated before, social networks monetize poorly Of course, sites with lots of pageviews are often ones that are general, are sticky, and have lots of context-less social content. I’ve written up a broader discussion of social network monetization at “5 things that make your social network monetize like crap.”

Back to small sites versus large sites Now, the Techcrunch article discusses the idea that small sites monetize better than large ones. I think that’s actually a correlation rather than a causation. There are a ton of small sites out there, and much of their traffic comes from Google. It’s much harder to build a functioning social site where people coming back daily than a site where people occassionally stumble on it through their search engine.

As a result, my guess is that the mindset of the typical user includes intent – and that makes all the diference.

Are the social networks making tons of money? People have been very excited about the advertising prospects of social networks lately. First you have announcements from MySpace about an 80% rise in CTR through profile targeting, as well as some claims of Facebook’s going rate CPMs being $4. Furthermore, the recent gold rush in Facebook apps has led quite a few folks amassing large userbases with dreams of incredible monetization. It’s quite easy, with all the profile information that social networks have, to automatically assume that this information is the same type that drives Google-like revenue and monetization.

So let’s talk about this… Are social networks making money hand over fist? Why or why not?

To aid this discussion, I’ll go through a couple of the critical challenges that affect social network monetization:

1. Engagement is inversely correlated with CTRs
2. Inventory isn't homogeneous, it's a pyramid
3. Don't confuse interest with intent
4. CPMs are driven by underlying value, not just targeting
5. Brands are a big wild-card

Understanding the CPM formula Before we jump in, let’s talk about how CPMs are generated. For the purpose of this discussion, I’m going to focus on direct response advertising, rather than branding (which we’ll get into later).

Ultimately, CPM is a simple calculation that is determined by:

CPM = Clickthrough Rate * Price Per Click * 1000

For example:
1,000,000 impressions * 0.5% clickthrough * $0.25 PPC
= $1250 per 1 million impressions = $1.25 / 1000 impressions
= $1.25 CPM

This is from the publisher side – if you have a good CTR or PPC or Impressions, you make more money. Now from the advertiser side, you need to figure out what the underlying value is. After all, even if you get a ton of clicks, if you can’t convert them on your side and have a good transactional value at the end, you won’t want to pay a PPC.

CPM = Clickthrough Rate * (Value of Action * Conversion Rate) * 1000

Conversion rate means the percentage of people who do the desired “action” that drives value for you. That might mean the % of people who buy from your e-commerce store, or who fill out your mortgage lead form, or whatever. You could also substitute this for Lifetime Value for your social network, or LTV for your virtual goods-driven casual game, or whatever.

Now let’s jump into how different dynamics on your site drive these different variables…

1. Engagement is inversely correlated with CTRs You know how MySpace and Facebook just encourage you to click-click-click and log in every day and are just incredibly sticky? That’s great engagement, and it helps with a lot of things, particularly growth and competing in strategic areas.

However, the drawback is that the more pageviews people have your site, the lower the clickthrough rate gets. Here’s a great diagram:

You should read the rest of the article on MikeOnAds, it has some other great data on there. This issue of engagement negatively correlating with clickthrough rate is well-documented, and happens at every network.

So how bad are the clickthrough rates, exactly? I’d guess that across all the social networks, something from 0.01% to 0.05% is pretty standard. You might have some higher CTRs in some very specific areas, for example right after a user completes an action (composes an email, friends a person, etc) but in general, they will be quite low.

There’s some evidence for Facebook’s CTRs being about 0.04%, documented here:

2. Inventory isn’t homogeneous, it’s a pyramid Sometimes you might hear the CPMs for one of these social networks is X dollars. And that’s true, it’s exactly the price that SOME people are paying for the inventory. But in general, that’s not how publishers end up managing their inventory. Instead, if you take the impressions for a user across their session, you’ll instead get something like this:

• The first US impression in a session has the most value ($10)
• Then impressions 2-5 have some level of brand value or high CTR value ($3-5)
• Then after that, you’re hitting ad networks selling on category ($1)
• Then eventually, you hit remnant ad networks ($0.50)
• Finally, you hit pure CPA remnant networks ($0.10)

These are just example numbers. Now the problem is that while people often quote the premium numbers, the majority of the impressions happen in the low CPM remnant numbers. The premium ads happen on the homepage, major channel pages (like Music, Games, etc), but not in the most popular pages like forums, profile pages, etc.

I’d expect the top inventory (let’s say 5-10%) end up generating 50% of the overall revenues.

So in your financial forecasting, don’t expect to be able to multiply a big CPM against your ad inventory. Instead, you need to be nuanced about the different sections of your site, and how they sit relative to the ad inventory pyramid.

3. Don’t confuse interest with intent Now to the profile data – how much is this worth? You might expect that by looking at profile keywords like “skiing” or “travel” or topics like that, you could make a ton of money on social networking sites.

Every page should be like Google, right? Wrong. (unfortunately)

The reason is that interest in a topic is different than having intent. Having “skiing” on your profile is completely different than searching for “ski tickets.” The latter means you’re ready to buy, whereas the former simply means that you sometimes buy. This is GREAT for brand advertising, but really doesn’t help on the direct response CPM formula.

Having high intent typically drives a higher conversion rate (driving up the PPC) as well as driving up the CTR. Having interest but not intent should theoretically be better than nothing, but there might be other effects, like having more “looky-loos” click on your ad just out of interest, but not actually buy the product there.

4. CPMs are driven by underlying value, not just targeting Furthermore, you really have to look at the underlying value of the transaction to figure out how the CPMs will turn out. After all, the underlying value drives the PPC, which then drives the overall CPM. In order words:

Mortgage leads trump contextually relevant ads because Mortgage leads can be worth 50X more than a non-transactional site.

This is how a mortgage lead generation site might work: Person enters their contact info, which then gets sold to 4 lenders, which then call the person to work out the loan. Each lead might be worth $10, but because it’s sold to 4 different companies, it’s worth $40 total.

Now a ski ticket might be more contextually relevant service. Or maybe a music subscription service. Or some other mass consumer good. But the increase in clickthrough rate COMPLETELY offsets the powerful value of the mortgage lead, all you will see is LowerMyBills psychedelic peacock ads.

Now targeting really does help advertisements, but the problem with display advertising which shows as you are using a site is that the effects are not going to be as strong as high-intent areas.

In this case, targeting might increase CTRs and conversion rates, but it’s unlikely that it’s so powerful it’ll completely offset the value decrease. People are mostly interested in things that don’t generate lots of money, and because of that, you have to compensate.

5. Brands are a big wild-card Of course, the real wild-card is brand advertising, because it really follow the CPM formula. Brand advertising is really not priced based on any logical way that follows a formula like that. Instead, it’s based on relationships, prestige, audience metrics, and other intangibles. So as the audiences for brand advertisers migrate from TV to the internet, you will see a tremendous amount of brand dollars move as well. These brand dollars will simply follow whatever’s “hot” – thus, because the major portals seem to be growing pretty slowly and/or actually losing engagement, you’ll see brand dollars chase the social networking sites.

However, unless your name is Tom or Mark, you’re unlikely to get your hands on too many of these dollars. And the reason is that brand advertising is sort of a “winner take all” game, where only the largest sites can afford large sales teams that can develop the deep relationships required to sell to Madison Avenue brand ad agencies.

The current hurdle is that advertisers don’t like UGC (er, CGM content) because it requires them to let go of their brand. So until that changes, through technological means or an attitudinal change, the brands are preferring buying video on mainstream media sites.

What’s next? Now, it’s not all bad for social network ad monetization. The place in the CPM formula that’s really driving revenue is that impressions are getting bigger and bigger. What these sites can’t make up via advertising efficiency, they are making up through pure bulk. That’s why you can build sites with 100s of million in revenue, and it’s growing every day. The brand shift is also going in their favor.

More interestingly, I’m looking for native ad units to develop on the site which do work for advertisers. Months ago, I had written about “tag along widgets” which has quickly materialized as the Cost Per Install ecosystem on Facebook. Here’s the excerpt from “What’s a Facebook user worth, anyway?”

Another option would be for some sort of deeper integration to happen as hooks to another widget. For example, I could imagine a company (let's say Apple) creating their own widget. If you as Mr. Travel Widget, when installed, would try to convince the user to also install an Apple widget, I think that'd be an interesting model. Basically tag-along widgets which advertisers pay some amount for every user that is brought along.

As these native ad units mature, I’d expect some new revenue opportunities to be built from scratch. Let’s see how it goes – it can’t be worse than display ;-)

UPDATE: Fixed CPM formula.. note to self: never add changes at 6AM when your brain is asleep!

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Thanks a Million – Open Registration Today Only

April 24th, 2008

The new Evernote closed beta is about two months old and we’ve just passed an important milestone: our first one million notes! During this time, we’ve made lots of improvements to the service and we’ll be announcing a few more big things in the next couple of weeks. Stay tuned.

To celebrate (and to do some stress testing on our registration servers), we’re giving away instant beta accounts to everyone who clicks on this secret url (http://preview.evernote.com/Registration.action?code=1MN0tes) from 6 am to 9 pm, California time, today. If you miss the time window but want an account, just sign up using the normal beta application and we’ll send you an invitation soon.

Big thanks to everyone who’s taken the time to test Evernote and send us feedback! We couldn’t do it without you.