Why FriendFeed Deserves a Billion Dollar Valuation

I know, I know.  They’ve been around for less than a year, so how could they possibly be worth a billion dollars?  It’s basically just a Twitter clone that’s a little bit faster and doesn’t go down as often, right?  Despite the surface similarities, FriendFeed has the potential to become one of the more valuable services on the Internet, and here’s why.  Google’s primary goal is to index the world’s information.  FriendFeed’s primary goal is to index the world’s conversations.  We all know the value that Google created out of their index.  Here’s a quick overview of how FriendFeed can do the same.

Phase 1: Grow a Rabid User Base

In order for FriendFeed to build up a index of the world’s conversations, they first needed to create a front end with two important components.  First, it needed to be as easy as possible for people to pull in their conversations from all over the web, and to do it in the most automated format possible.  Second, they needed to build in a viral distribution model that would allow them to build up their user base as quickly as possible.  My guess is that somewhere in the FriendFeed offices, they have a graph on the wall that shows two curves.  One is an exponential growth curve that represents their predicted growth (based on power laws and estimated viral coefficients) with a clearly defined upper threshold.  The other is a line showing the actual user activityThe one thing FriendFeed should focus on in this initial phase is to ensure that their actual growth is showing a viral growth pattern and will reach their target threshold by a certain date.  Once they reach this threshold, they will have proven out their viral distribution model.  Take an exponential growth pattern and multiply that by an exponential content aggregation engine, and FF has the underpinnings of a massively powerful engine that can quickly build out the data needed to form the basis of their “conversation index”.

It will be pretty obvious when they hit their target threshold.  It will be approximately 2-3 weeks before they announce a pretty sizeable VC investment.  FF won’t be the only ones who are watching this growth curve very closely.  🙂 

Phase 2: Mine for Context

At this point, FF can use the new investment to build out a pretty sizeable server farm to handle the incredible amounts of data that will start flooding in.  You’ll probably also see some job postings on their site for PhD’s with backgrounds in data mining and contextual relevance.  Why?  Because unlike a traditional search engine that can do a pretty good job of indexing information just based on things like page rank and keywords, extracting value from conversations needs to take context into account before it can truly be valuable. 

For example, compare the view of Twitter posts on the Twitter public feed to the view of Twitter posts on Twistori.  This is a very crude example of type of analysis needed to pull a signal out of the noise.  Once the algorithms have been created to extract the context, FF just has to sit back and wait for their index to grow to a point where they are able to provide statistically significant results for search queries.  Which, of course, brings us to the start of phase 3.

Phase 3: Search v2

And here’s the real value of FF gets unlocked – search.  Scoble actually touched on this a few weeks back (see #3), but here’s my take on it.  Imagine you’re looking to buy a new laptop.  You go to FF and ask the question “What laptop should I buy?”.  The results will come back in two forms.  First, a list of posts from your friends displaying their opinions on their favorite laptops.  Note that unlike the search that is on FF now, these contextual results will filter out any noise such as conversations about problems they are having with their laptops, posts that have the word “laptop” but are not specifically about laptops, etc..  Second, a list of posts from all users displaying information about their favorite laptops.  Again, this will be a filtered list, and it could also be aggregated in a format like “120 people like the MacBook Air, 75 people like Dell Latitude D820, etc..”.  Of course, you could click into any of these lists to see the details of the conversational threads.  And finally, if you didn’t get a satisfactory answer from your search, you could simply post your search query as a message post to your followers, and get a special notification back once people start responding.  This goes one step beyond anything a traditional search engine can do, and really takes a best-of-both-worlds (mechanical vs personal) approach to finding the information you’re looking for.

In addition, there’s one more killer application of this new way to search.  Imagine you’re in downtown Seattle and you’re looking for a place to eat.  You pull out your phone, do a search for “best restaurants in Seattle” (or click on the “Restaurant” icon on the FF mobile app), and get the same FF search outlined above for both your friends and everyone – filtered to show only opinions from people from within 1 mile of your current location. 

I’m not in charge of the budgets at G, M, or Y – but if I was, I don’t think it’s too crazy to think that a service like that tied into my advertising platform might be worth a pretty nice chunk of change.

What do you guys think?  Am I drinking way too much of the Web 2.0 Kool-Aid, or is FF really on to something here?  I’d love to hear your thoughts in the comments below.

Update: Jeremiah Owyang just posted an interesting analysis on FF that’s worth a read as well. 

Update #2: TechCrunch is reporting on FF’s hockey-stick growth.  Now it’s time to keep an eye on their “We’re hiring!” pages… 

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Brain Interface Getting One Step Closer to Reality

Slashdot is reporting on the applications of a 2002 brain interface technology that is finally being used with an actual prosthetic arm:

“A team at the university of Pittsburgh has finally advanced a 2002 technology enough for use in prosthetic limbs, the targeted application all along. Training computer models to the firing patterns of the neurons in the parts of the brain that control motion, they are able to project the intentions of a monkey to a robotic arm, which follows the will of the animal. The sad thing about the articles is that the beauty of the mathematics used to create and train the models is totally ignored.”

I’m way interested in this stuff, as back in 2001 I worked on a project called the “Direct Brain Interface Project” at UM where I built out a little computer game that would be used to train the underlying computer model that would detect brain waves for a given stimulus.  I loved that project, it’s great to see that there’s some real progress being made in this area seven years later.

From Hatchlings to Borg

The Armchair Theorist has an awesome post outlining the various stages of startups.  Here’s a quick sample:

Tier 2 – Local Sensations

Your Local Sensation startup has survived the first six months to a year, and is beginning to build up a loyal community of users. Some people recognize the value of the service you are providing, but you either still have a ways to go to unseat the leader in your space, or your startup concept is so niche or so new that many people have been slow to sign up. Most of your users are either part of the Silicon Valley echo chamber or are geographically located in the country in which you are based.

Reputation: For the particular service you provide, you are recognized as a player in this space, but not the leader. Your startup may only be well known only in the country in which it is based. Your startup’s name is recognizable by roughly half of the Web 2.0 evangelists and early adopters, but almost none of your friends outside of the IT industry. Your friend’s mom has never heard of your service before.

Adoption: You may have anywhere from 1000 to 10,000 active registered users, most of which are based in your home country. Some Web 2.0 evangelists and early adopters may use your service for a bit to see if you are bringing anything new to the table.

Buzz: Your startup may be mentioned once or twice on either FriendFeed, Twitter, Techmeme, Digg, Reddit, or Slashdot. You are likely to have been mentioned on TechCrunch or other Silicon Valley evangelist blogs like Robert Scoble’s or Louis Gray’s.

Monetization: You may or may not have a business plan in place to make money. However, it’s still waaaaay too early to talk about monetization now. Let’s get even more users first!

Mulligans: If your startup is unstable and shows scalability or usability problems at this stage, it’s game over. Most early adopters will not bother giving you a second chance and will jump ship to your competitor instead.

Examples: Polyvore, SharedCopy, Twine

Where does your startup land?

Top Five Tech Quotes of the Day

My mom wants me to move in with her, so my demand will be being able to rewire the entire house with cat 6, and a file server running either solaris 10 or debian stable in the basement.

Comment by a reader referring to DLink’s plan to route Ethernet packets through existing co-ax cable lines (link)

I like Google

Jerry Yang, responding to Walt Mossberg’s question at the D conference about outsourcing Yahoo’s search advertising to Google (link)

Well it wouldn’t be a Developer event if there wasn’t a long-haired developer from Seattle

Nat Brown, CTO of iLike, during the Google IO keynote (link)

Microsoft has built up a culture of crisis

Ray Ozzie, talking about Microsoft’s historical ability to respond to competitive threats (link)

He stated he needed the money to pay off debts and stated that this was one way to earn money…

Reasoning behind Michael Largent’s Office-Space-esque plan to write scripts to open several thousand accounts and accumulate the pennies that are deposited every time online trading sites check a bank account for authenticity.  It might have worked, but he probably forgot to put in a decimal point.  (link

Pay Attention to Privacy vs Convenience. It’s Important.

There is a lot of information about me out on the Internet.  My nameWhere I work.  What bands I likeWhat TV shows I watch.  Heck, even my shoe size is now out there in the public domain.  In addition to this explicitly posted data, there’s some other stuff out there that web sites know about me.  For example, my IP address can be mapped to my current location.  If I’m using the latest beta version of Flock or IE 5.0, you could probably draw some inferences about me.  If I arrived at the URL from a link posted in Facebook or MySpace or FriendFeed or a banner ad or a specific blog, what might you know about me?

This isn’t a new argument, privacy is dead and it’s getting worse the more these whipper-snapper kids start flocking online. However, if my information is already out there, why aren’t you using it to my advantage? 

  • If I visit www.abc.com from a Lost forum, why don’t you show me a trailer for the next episode on the home page?
  • If I visit your band’s web site, why don’t you show me the next time you’ll be in Seattle?
  • If I visit www.zappos.com, why don’t you show me all the size 10.5 Steve Madden’s and Nike’s from your clearance section?

Sounds great, right?  But what about this scenarios?

I open an Email from my brother that starts off with comments on some photos that I’ve taken recently.  He then asks me to click on a link to donate to a cause that he is promoting.  I click through to the site and give my credit card info, only to find out later that my brother never sent me a donation request.

This is one area that we’re all going to have to pay a lot more attention to in the years to come.  And it’s important to note that this isn’t a black and white issue.  I’m probably not alone in welcoming in a new set of services that are automatically personalized to save me time and give me a better experience.  I’m even willing to take on some additional risk of facing some very sophisticated spamming/phishing techniques. 

The question is where to draw this line?  And my answer is, let me decide.

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Buying Stuff Online

It’s not a mutli-billion dollar a year business for nothing – advertisers are spending money to get users to spend even more money buying stuff online.  So how do people go about finding things to buy online?  I have a simple proxy that I use when I think about questions like this.  What would I do as an early adopter?  What would my wife do as a computer-savvy-but-non-geek user?  What would my mom do as a why-do-you-call-it-a-mouse user?  I’m going to take a simple example of buying a pair of shoes, and thinking through how each of use would typically go about doing this.

Early Adopter

I’m a victim of the recency effect – whatever the prettiest, shiniest thing that people are talking about *right now*, I’m going to go try it out.  For shoes, I heard a podcast last week (I think it was TWIT) where they were talking about how Zappos.com is using Twitter to monitor for customer satisfaction.  So, I’d go to Zappos, no?  Actually, I’d probably first just jump on Twitter, do a quick tweet about Zappos, and see how fast they got back to me.  THEN, I’d click on the Zappos rep’s Twitter profile, and from there click through to Zappos.

Power User

My wife would probably do one of two things.  First, she’d either go to Google and do a search for “shoes <description of shoes>”, or go directly to a site like Nordstrom.com and click on the “shoes” section.  Once she found the shoes that she wanted and was getting close to checkout, she’d jump over to RetailMeNot.com and look for a coupon code.  I taught her that trick, but then again I tell her about lots of sites and that’s the one that stuck, so maybe there’s something there.

Non-Technical User

My mom would type the name of the store into the first text box she could find.  She would then get the phone number and call them to see what their hours were.  The only exception here is if I sent her an Email saying “buy product X from website Y”, and even then she’d generally call me to walk her through the process and make sure that she wasn’t giving her credit card to some phishing site.

So what’s the point of all this?  A couple of things. 

First, it reminds me why online advertising is expected to grow at such a fast rate.  Five years ago my mom didn’t own a computer.  Two years ago she didn’t have Internet access.  Once she gets more comfortable with the idea of buying stuff online, there are some real opportunities to tap into this huge mainstream market.  It also makes me think harder about broad mainstream initiatives that will be there to capture some of this opportunity.  For example, take Yahoo’s Search Monkey initiative – is it more productive to focus on getting my mom to remember a cutesy URL, or to build something that will get her attention directly within her search results?

Second, I really do need to get some new shoes.  I’m a size 10.5, and currently have a pair of Steve Madden’s for my casual work shoes and Nike’s for my sneakers.  Got a recommendation on a pair to buy?  Post ’em if you’ve got ’em.

Lucky Number 7?

Disclaimer: I work for MS and own stock in the company.  Please note that this and all posts on this blog reflect my personal opinions and absolutely do not represent the official views of MS.  If you’re looking for my official MS views, see here and here.  🙂

Big news from the “D” conference last night, as Bill and Steve gave the first public demo of one of the features in the next version of Windows, code named Windows 7.  The one feature that was showcased heavily was the new multi-touch capabilities originally used with Microsoft Surface. While we’ve see this interface before, I see this announcement as the first sign that multi-touch will go mainstream.  This poses a big question that every developer and designer should be asking themselves: what is going to be the “killer app” for multi-touch?  Considering this is about to be rolled out to hundreds of millions of users within the next five years, you may want to spend a few minutes today brainstorming the possibilities.  I know I will.