Enter Boxee. The first time I heard about Boxee, I was excited. Over the past five years or so, there has been an increasing demand by consumers to watch digital video content on their TV. A few years ago, Microsoft proclaimed the future to be a PC hooked up to your HDTV powered by Windows Media Center. I think it’s safe to say that vision didn’t quite pan out. However, we can thank Microsoft for creating the XBox because from that XBMC was born. XBMC was the first powerful glimpse of what a media center should be. It allowed streaming of video content over the network and, being open source, many interesting features, such as web browsing and music players, were integrated into it. The problem with XBMC was that you had to find and hack an XBox to get it. Not mainstream. Apple TV could have been a breakthrough product but, in true Apple fashion, the closed nature of the product and DRM restrictions limited its potential it. XBox360 and PS3 make major leaps by allowing users to stream unlicensed video content, but stop short of really embracing the media center concept. Finally in June of 2008, Boxee releases an Alpha of what eventually could be the first mainstream media center software product.

I’ll let you visit Boxee’s web site and discover all the useful features of the product and how you can obtain it. One of the killer features the Boxee team added was Hulu streaming.

Hulu on Boxee (courtesy of Fred Wilson)

Last week alone, Boxee claims to have streamed over 100k Hulu streams. That’s a huge number considering Boxee’s installed base is still pretty small. At a glance, this would all seem like a win-win-win. Big media companies control content delivery via Hulu and Boxee enables Hulu users to enjoy the flexibility of using the service on their TV. Unfortunately, good things don’t last forever. Somebody was going to get hurt. It turns out, it’s Boxee.

Apparently, the big media guys didn’t like that consumers could watch shows like Lost and 24 on their TV via Hulu. After all, big media makes its money by selling TV ads. If Boxee users could enjoy their favorite shows on their TV via Hulu, then big media sells less ads and earns less from cable providers for channels like FX and USA.

The problem in this logic is that it seems to me that Fox/NBC hasn’t really thought this through. What will these Boxee users do instead of watching on Hulu? My guesses are:

1) Tivo/DVR the shows. Result: Ads are skipped altogether. No cable viewing.
2) BitTorrent. Result: Ads are non-existant. No cable viewing.
3) Doesn’t watch the show. Result: This hurts the media companies in several ways. Ads are not seen and no cable love because the show is not seen. The show ultimately becomes less popular, ad space is less valuable, less DVD box sets are sold, less syndication monies, etc., etc.

See a pattern? =) By blocking Hulu on Boxee, Fox/NBC are simply creeping back into their old-school mentality that is slowly bleeding their ad money dry. My hunch, like many others who have blogged about this story, is that this decision will be overturned. Unfortunately, I wouldn’t be surprised though if there are some restrictions placed on Boxee to encourage Hulu users to watch on their PC. Such restrictions could be no HD content or more annoying ads. We’ll see…

One of the items I put on my to-do list is to do some research on what the ad rates are for Hulu (and others like MTV’s Overdrive) and how that compares to TV on a per impression basis. My hunch is Hulu is way higher…I’ve found myself actually intently watching the 30-second ad spots! That rarely happens on TV. Plus the other side benefits of delivering the ads online like opportunities to interact with the ad. I’ll report my findings in a later post!

Citi “providing stability” and “securing the future”? Hmmm… I guess they’re assuming that NY Times readers doesn’t actually read any of the headlines. =)

It should probably read “needing stability” and “destroyed its future”…

What’s most interesting about Latitude is thinking about why Google prioritized this feature over others for Google Maps. To kill off Loopt? I just don’t see that. After all, how much of a threat is Loopt to Google? Not much. Google Maps is the dominant mapping application on every mobile platform. Ultimately, tracking the location of your friends is a feature not an application. The idea that users were going to launch Loopt on their phone for the sole purpose of checking their friend’s location is just not realistic. It’s natural that this feature was eventually going to come to GMaps. But in the meantime, I doubt Google was losing sleep over Loopt.

So why now then? My guess is amassing more user tracking data. Note that when you enable Latitude on GMaps, Google now ties your Google login to your GMaps installation. This was a link that did not exist before. As a result of all this Google can now record data points such as:

1) Where you go, spend time at, etc.
2) Where your friends go, spend time at, etc.
3) What types of POI’s you search for
4) What routes you take

All very interesting (and very scary) primary data points. It’s not clear if Google can do anything meaningful with this data yet. However, it’s reasonable to expect that that in a year or two, once a lot of this data has been collected, either Google’s search or ad targeting technology will incorporate this info. However, if I am correct that Google is recording this data, they really should make the user aware of this. Of course you can argue that none of the ad networks, including Google, makes online users aware that their every click is being recorded. However, I think there’s likely to be many users who are concerned about their physical location being tracked!

Finally, Latitude is a fantastic way for Google to get users to formally “friend” their contacts. In order to use Latitude, you must have friends on Google’s social network. I, like the vast majority of Google users, have plenty of contacts (via GMail and GTalk) but never formally friended them. Latitude forces users to do this in order to use the service and should help Google build up its social network. This will pay dividends for Google as they continue to expand their social product offerings.

I must say, Google getting serious about mobile is exciting. It’s forcing all the players to step up their game. In fact, my hunch is that Android’s ability to run background tasks had something to do with Apple killing off the push notification system in favor of a more robust background task function for the iPhone. In the end, the consumer wins. I love it!

Advertising is everywhere we see. Our brains are trained to automatically ignore much of it. While some ads are so extremely unrelated to our interest that it catches our attention. That’s spam. Yet some minority of ads catch our attention because they’re so interesting as to be highly informative. In this case, the ad is a service to the consumer. Think of it like a continuum where the variable is relevancy.

|min—–RELEVANCY—–max|
|spam———————service|

So what if a publisher served only those ads that were very relevant to each consumer. The consumer is happy. The advertiser is happy because their message is reaching exactly those consumers who are likely to act on that message. Publishers are thrilled because they’re making money by very efficiently connecting advertisers with consumers. Win-Win-Win.

Of course, this “perfect” targeting is the holy grail. It doesn’t really exist in any sort of mass scale. But, what if I told you that a company in the UK is so good at doing this that they claim to generate enough ad-based revenue to pay for your cell phone & service? In fact, that company is Blyk. Blyk offers teenagers and young adults in the UK a phone, and service for free. The recipient agrees to receive occasional ads. About a year ago (the service was quite new back then), they claimed 29% average response rate to ads. How do they get such high response rates?

Well, in a sense, Blyk lets its customers control the ads they receive. Customers might receive texts along the lines of:

Are you a UFC fan? [*Y/*N]

XBox360 or PS3? [*X/*P]

Want to hear a sneak peak of the new Radiohead album? [*Y/*N]?

Essentially, Blyk polls the customer to learn about their preferences. They

1) Send a text with content that encourages a simple call to action (”Watch UFC?”)
2) Based on this primary data, they send an ad in the future (”Check out UFC 49 this weekend. $20 on PPV… Call now to order!”).

Blyk’s advertisers and customers are happy. Everybody wins, especially Blyk.

Let’s think about how this might work for a site like Facebook. On Facebook, users are already expressing their interests in a variety of areas. They do this not just statically on their profiles, but constantly via the other social interactions like fan pages, groups, status updates, wall posts, etc, etc.. Fan pages and groups are useful data points but mining user-created content is extremely challenging.

I think a Blyk-inspired system could work on Facebook. I’m curious to know the response rate of the existing Facebook Polls feature. If it’s even somewhat high, and since it’s in the feed I have a hunch it is, Facebook could very easily start to poll users for the purpose of collecting high quality data that makes sense to advertisers. Or, as is suggested in this Telegraph article today (the story is now being denied by Facebook PR), advertisers themselves could poll users via Facebook. Facebook wins two ways. First they earn revenue from the advertiser to run the poll. Secondly, Facebook can charge a very nice premium for enabling advertisers to then deliver ads to specific sets of users (based on their answers to prior polling).

If Facebook executes this well, this may actually improve the user experience. Instead of Facebook being increasingly cluttered with spammy ads, Facebook could serve fewer ads that are, referring back to our earlier continuum, so relevant to the user that the user is happy to see them. Moreover, from a revenue perspective, the rate they could charge for serving a single highly-targeted ad earns orders of magnitude more money than serving hundreds of garbage remnant inventory ads.

Sounds like a plan to me?? Opinions?

Voyij is the creation of Nick Atkins and Paul Kim, friends and former co-workers of mine at SideStep. Voyij is the best search engine for travel deals on the Web. The great thing about Voyij is that you don’t need to know exactly where you want to go. If you have some ideas about what you want to do on your vacation (e.g. skiing, gambling, beaches, etc..), Voyij will find you deals based on that criteria. The team has still got some wrinkles to iron out but the site is absolutely worth checking out next time you book travel.

If it’s just a hotel that you need then check out DealBase. My former manager, Sam Shank, continues his reign on the hotel deals & reviews space after he sold TravelPost.com to SideStep (now Kayak). Like TravelPost, DealBase offers consumers honest, comprehensive hotel information. This is in contrast to some of the market-leading travel sites which may encourage you to book the wrong hotel because it earns them the most commission.

If you play the guitar, then you need to check out FretBase. (The *Base.com thing is a coincidence..) The site is the brainchild of another of my former managers at SideStep, Brian Stolte. Recently launched, FretBase has already grown to include an impressive amount of information on everything guitar-related, from music to artists to the guitars themselves. With the passion that Brian and the rest of his founding team has, I’m very excited to see what they do with the site.

Finally, my long-time buddy, Rob Poitras has just embarked on a new project called FashionLuvr. Rob has proven himself to be an online marketing expert in the fashion world. He’s leveraging that expertise to create the defacto website for the latest sales at online clothing boutiques. Rob’s got an intriguing strategy to grow FashionLuvr and particularly given the lull in demand for high-priced clothing, he may just have exactly what the market needs.

Btw, come on guys, make proper linkable logos!!

StockTwits is a community of people who follow the equity markets and exchange thoughts, via Twitter, about both single names as well as overall market movements. On StockTwits.com, any user can browse all the latest Tweets amongst the community members. Here’s the StockTwits AAPL page:

Now, this concept in and of itself is interesting but not really thought-provoking. However, what I found sort of fascinating is the mechanics of StockTwits. StockTwits users include $[Ticker] in their tweets to let StockTwits know what ticker they are microblogging about. So, for example, “long $RIMM short $AAPL has been a heck of a trade in 09″ indicates to StockTwits that the tweet is relevant to RIMM and AAPL. Because all tweets follow this convention, it is easy for StockTwits to organize the massive number of tweets into channels. In this case, the channel is a single equity name.

Let’s say you started a baseball twittering community. You might create conventions like $[LastName][Jersey#] or $[FirstName][LastName] or whatever.. in fact by applying a bit of intelligence when processing tweets, the system can probably be quite flexible and still correctly resolve player names. The bottom line is that as long as users are OK with including these inline tags in their tweets, systems can then make meaning. Sort of like tagging a post on one’s blog, but the difference being that everyone agrees to use the same set of tags.

In today’s blogosphere, tags are arbitrary. That’s the way it’s always been and this behavior is unlikely to change. The result is that the blogosphere is difficult to aggregate. The only way to create a structure out of related blog posts is through links and trackbacks. While this kind of works (Techmeme is certainly a shining example), there are tons and tons of unlinked posts about the same topic everyday in the blogosphere that, while related, cannot be aggregated.

In contrast, I think there’s a real chance for these twittering tag domains (for lack of a better name for this) to catch on. Tweets don’t really live anywhere per se. Blog posts do…they live on your blog (a web page). Thus, there’s a tendency for people to want to express their blog posts in their own individual way. That means categorizing and tagging the post in their own preferred way. However, for Twitter users to join a conversation on a specific topic, they will need to tag their tweets with a common folksonomy, like we see with StockTwits. Without this concept, a community like StockTwits would be utter chaos.

There’s definitely something interesting about structuring conversations in Twitter. Both for the purpose of making richer experiences for those involved in the same conversation and for the purpose of search/aggregation.

For those that aren’t familiar with what a search fund is. It’s essentially entrepreneurship through acquisition. The basic steps are:

1) Small “search” team of entrepreneurs rounds up a dozen investors who will front some cash (about $25k each give or take) to cover the cost of the search team finding a great business to acquire.
2) Once the search team finds such an investment (this can take a couple of years) the original investors can invest at a discount.
3) Assuming the deal closes, the search team then takes over the operations of the company and grows it.
4) PROFIT.. =)

If you have a couple of hours, these videos are definitely worth watching even if you have no desire to be involved in a search fund. I learned countless practical lessons on how to create and manage proprietary deal flow, negotiate, deal with accountants and lawyers, obtain debt financing, and even how to successfully lead and manage a growing organization.

HBS - Search Fund Videos

So..where does alpha come from? Benjamin Graham, the father of value investing, found excess returns by buying attractive stocks that were very underpriced — priced far below their tangible book value with no warning signs to justify it. Back then (in the early to mid 20th century), analyzing securities was a challenge. Access to financial statements and timely market news was difficult. Thus for people like Graham — and his disciples — who 1) put in the effort to obtain the relevant data 2) crunched the numbers (remember no Excel!) 3) had the proper analytical framework (courtesy of Graham) and 4) were patient there were bonafide bargains to be had.

Over the course of the 20th century, access to market information improved substantially and the number of “sophisticated” investors skyrocketed. This trend continued until the point where toward the end of the century, all investors both big and small were essentially on an even playing field. Obvious bargains in the equity markets dried up. Given that classic Graham-esque bargains were sparse and that his assets under management was ever increasing, Buffett describes how his investing philosophy evolved over time to focus on concepts such as intrinsic value and economic goodwill.

Today, with ubiquitous access to real-time market information, markets are efficient. An important note here is that I define efficient to mean that the price of a security on the open market is an accurate, without-time-lag reflection of the collective sentiment of investors’ opinion on where the price should be based on news and forecasts as well as emotions/irrationalities. I am not using the word efficient to imply that market prices are always rational. Humans, for reasons that only some of which are scientifically understood, are susceptible to biases and irrational behavior. The bottom line here is that investing, even for the most disciplined strategies, has become difficult. Wouldn’t it be nice to rewind the clock a hundred years back to the Benjamin Graham’s day when access to information was difficult?

I think so.. and this leads me to wonder that maybe investors need to dig deeper to find new sources of information that aren’t obvious to other investors. As I’ve discussed many times before on this blog, there has been an explosion of news publishing because of the Web in many forms, the most obvious perhaps being blogs, both professional and personal, and the less obvious mediums such as twitter and message boards.

One concrete example that comes to mind is a blog post from January 2008 by Markus Frind (founder of plentyoffish.com, one of the largest dating web sites in the world). The post talked about how because of a subtle design change by Google, his AdSense CTR (click-thru rate) dropped by 60%. The change was that in late ‘07, Google changed AdSense so that only the link in the ad is clickable, not the whole ad area. Google had presumably done this to reduce accidental clicks. In the long term this is a good thing for everyone because it reduces click-fraud issues. However, near-term CTR drops a bit, thus # of clicks drops and thus ad revenue drops. Now, ultimately, advertisers should see a rise in their conversion rates (since the quality of clicks goes up) and thus be willing to pay more for each click, evening out the ad revenue. However, there is a lead time for that to happen. Near-term ad revenue drops and there should, in theory, be a negative impact on Google’s quarter. TechCrunch had actually reported on this change on November 11, 2007 but the post came and went without much drama.

Now, fast forward to February 26, 2008, comScore publishes a report indicating that Google’s CTR may be dropping and GOOG drops 4% to close at $471..down from the mid $600 range in January. On February 29, 2008, TechCrunch posts Google CTR Down Due to Click Area Changes referencing the ealrier post in January by Markus Frind.

I remember thinking in January that I should take a short position in GOOG. Of course, I didn’t really take myself seriously, but when the comScore report came out and GOOG dropped sharply, my jaw dropped. At that moment I realized that my idea of finding these nuggets of gold on the Web isn’t crazy. In fact, I’m not the only one with the idea. Roger Ehrenberg, a wall street veteran, had co-founded a company named Monitor110. The company has since went under, but here’s an excerpt from a TechCrunch article on the company:

Monitor110 gathers information from 40 million sources of various types (100 million by the end of next year they say), ranked by financial market knowledge through a proprietary algorithm that takes 50 factors into account - inbound links being just one reputation metric. Users can chose between top sources preselected for their market sector and subscribe to sources of their own. Static sites can be monitored for changes with good granularity. Premium subscription and other deep web sources, blogs, forums, news and regulatory filings are among the sources included.

Here’s an image that used to be on Monitor110’s homepage. It elucidates the concept very well:

Think about an engineer who blogs about how he’s working like crazy because his project at work is behind schedule. If we know that he works at THQ, this information could be valuable to an investor. That’s precisely what Monitor110’s business model was. Sell to hedge funds and other folks desperate for alpha. Is this scalable? I’m not sure. Probably? Maybe too early for it’s time?…it was for Monitor110.

I’m a huge proponent of the idea that the newspaper, with it’s one-size-fits-all news, is dead. I discussed this in my prior post, Ok, I admit it one size fits all news will die. In this prior post, I discussed the fact that I consume most of my news today using my RSS reader. I’ve added several news feeds, from many topic areas, that I respect and enjoy to my reader and I check it every few hours. I have found that over the past couple years, my awareness of current events in topic areas that I am interested in has risen considerably.

However, there are limitations to the RSS reader. “Rolling” your own news feed takes time to create and maintain. I don’t expect that many will do this. More importantly, though, the scope of the news that is available to me is bounded by the content of those news feeds which I have explicitly included. I don’t doubt that every day I miss news stories that would be of high interest to me because they originate from news sources that I am not following. A news application that can show me news from both my explicitly chosen news sources as well as news stories that come by leveraging recommendation technologies (e.g. “Story X is similar to news stories which Rishi typically reads” and “Story X is being read by many people who have similar news tastes to Rishi”) will be the ultimate solution for me. What’s exciting is that I expect such a news application to be available very soon…

So what’s the right attitude? Humility. It doesn’t matter how smart and successful and qualified you are, you simply don’t know what you’re doing. The good news is that nobody else does either, though some are foolish enough to think that they do (and that’s why you can beat them).

What is the humble approach to product design? Pay attention. Notice which things are working and which aren’t. Experiment and iterate. Question your assumptions. Remember that you are wrong about a lot of things. Watch for the signals. Lose your technical and design snobbery. Whatever works, works.

What I tell people over and over is that one can be the most accomplished product designer/manager/engineer, but when developing a new product, you are really just making an educated guess about what will resonate with your user. Sometimes what makes so much sense on paper just doesn’t jive with users. In a sense, the design+requirements for the initial product is the hypothesis and the v1.0 of the product is the experiment that tests the hypothesis on users.

What separates the winners from the losers is the analysis of the results, which in the case of web-based products can be efficiently done by looking at specific engagement metrics. This does not just mean pouring through Google Analytics data. Instead, I’ve found it to mean combining the analytics data with database queries that measures key application engagement metrics.

The point is that the development of innovative products must be both rigorous and methodical. Use the standard scientific method. The unknown question is “What do my users want?”. Start with a hypothesis, experiment by testing your products with real users, analyze what worked and what didn’t, modify your hypothesis, test, …