Impressions from the SaaS nirvana (a.k.a. as the 3rd annual PNC SaaS Founder Meetup)

Last week, we've held our third annual SaaS Founder Meetup in San Francisco. Following the first PNC SaaS Founder Meetup in San Francisco in 2012 and the second one in 2013 in Berlin, this has become a tradition for us: Once a year we're bringing together the founders of our SaaS portfolio companies, co-investors and leading experts for a full day of intensive knowledge sharing. To be precise, it was one day in 2012 and 2013. This year we've extended it to two full days.

It's hard to describe in a few words how awesome it was and how much we and our portfolio founders have been able to learn thanks to all the amazing speakers who were willing to share their insights at the event. I'll try to follow-up with some additional notes later, but for now here are some visual impressions from the meetup:

Impressions from the PNC SaaS Founder Meetup 2014 from Point Nine Capital

Huge thanks to all attendees and a special thanks to all of our incredible speakers and panelists:

Aaron Ross (Author of "Predictable Revenue"; former Director of Corporate Sales, Salesforce.com)
Albert Wenger (GP, Union Square Ventures)
Bill Macaitis (Former CMO, Zendesk; former SVP Online Marketing, Salesforce.com)
Boris Wertz (GP, Version One Ventures)
Colin Bramm (Founder & CEO, Showbie)
David Bizer (Founder, Talent Fountain; former Staffing Manager, Google)
David Hassell (Founder & CEO, 15Five)
Donna Wells (President & CEO, Mindflash; former CMO, Mint)
Doug Camplejohn (Founder & CEO, Fliptop)
Everett Oliven (National VP Sales, SAP)
Gil Penchina (serial entrepreneur & angel investor)
Heiko Schwarz (Founder & MD, riskmethods)
Hiten Shah (Founder & CEO, KISSmetrics)
Jason M. Lemkin (Managing Director, Storm Ventures; former Founder & CEO, EchoSign)
Jean-Christophe Taunay-Bucalo (Chief Revenue Officer, Vend)
Joel York (Founder & CEO, Markodojo; former CMO, Meltwater Group)
Julien Lemoine (Founder & CTO, Algolia)
Lars Dalgaard (GP, Andreessen Horowitz; former Founder & CEO of SuccessFactors)
Lincoln Murphy (Customer Success Evangelist, Gainsight)
Mark MacLeod (CFO, FreshBooks; former GP, Real Ventures)
Matthew Romaine (Founder & CTO, Gengo)
Nick Franklin (former MD Asia, Zendesk)
Nick Mehta (CEO, Gainsight)
Nicolas Dessaigne (Founder & CEO, Algolia)
Nikos Moraitakis (Founder & CEO, Workable)
Omer Gotlieb (Founder & Chief Customer Officer, Totango)
Paul Joyce (Founder & CEO, Geckoboard)
Rian Gauvreau (Founder & COO, Clio)
Ryan Engley (Director of Customer Success, Unbounce)
Ryan Fyfe (Founder & CEO, ShiftPlanning/Humanity)
Sean Ellis (Founder & CEO, Qualaroo)
Sean Jacobsohn (Principal, Norwest Venture Partners)
Sharad Mohan (Chief Customer Officer, Vend)
Steven Silberbach (VP Global Sales, Clio; former Area VP Sales, Salesforce.com)
Todd Varland (Solutions Architect)
Tomasz Tunguz (Partner, Redpoint Ventures)
Zvi Band (Founder & CEO, Contactually)

OKRs – objectives and key results

Last night I returned from a 2-day offsite with the Point Nine team (in Schlepzig, of all places). Our (small) full-time team more than doubled in the last six months, and this was the first time for all of us to spend some time together away from the daily bustle. We had a long list of topics that we wanted to discuss, ranging from investment theses to portfolio companies and to a number of projects that we're working on.

I wanted to kick off things with a session about our OKRs (objective and key results), and we had scheduled two hours for this agenda item. If you haven't heard about OKRs before, it's a methodology invented by Intel and popularized by John Doerr, the famous VC who invested in Netscape, Amazon and Google. The idea is (simply put) that a company needs to have clear objectives and that every department, team and person in a company needs to have objectives – and a set of key results for hitting those objectives – which are aligned with the company-wide OKRs.

We ended up spending the entire first day and some more time of the second day on this topic. This is particularly funny because I wasn't even sure if it's worth talking about our OKRs since I was wondering if they aren't obvious anyway.

Now, to be precise we didn't spend ten hours talking about our high-level long-term objectives. At a high level our goals are pretty obvious and I've written about them here. But diving in deeper and deeper brought us from one question to the next question, and by the time we were finished with the OKR session we've covered most of the topics which we had planned to discuss in other sessions. So on the one hand we completely screwed up the schedule that we had put together, on the other hand we covered most of the stuff that we wanted to get done in the end.

After this experience I am now even more convinced than before that every startup should use OKRs or a similar methodology to ensure that everyone in the company is on the same page and that there are clear and measurable goals. Scott Allison, founder & CEO of Teamly, wrote a great summary of the benefits:

• It disciplines thinking (the major goals will surface)
• Communicates accurately (lets everyone know what is important)
• Establishes indicators for measuring progress (shows how far along we are)
• Focuses effort (keeps organization in step with each other)

But isn't this a no-brainer, don't all companies have a plan for the company as well as targets for most employees? Yes and no. All bigger company presumably have a budget and plan in place which is aligned with the company's objectives, but my guess is that what's often missing is linking that high-level plan to every employee's targets and communicating it throughout the entire organization. I'm pretty sure that if you randomly picked 100 employees of any Fortune 5000 company and asked them about the objectives of their companies you'd get lots of different answers. And in a fast-growing startup which doubles headcount every year and where each individual employee can have a much bigger impact than in a large enterprise, it's even more important that everyone is on the same page.

If you want to learn how Google (where John Doerr helped introduce OKRs) sets goals, watch this video from Google Venture's startup lab.

Know your user cohorts

One of the most important tools to better understand the usage of a web application – or a service, a game or a mobile app, it doesn't matter – is a cohort analysis. In fact, it's almost impossible to get a really good understanding of a service's usage without looking at activity and retention numbers on a cohort-by-cohort basis.

And yet, most startups that we're talking to haven't looked into cohort analyses yet. Often the reason is lack of resources. If you're a young, bootstrapped startup and you have to decide if you want to use your developers' scarce time to improve your product or to get better statistics most founders will decide for the product. That's understandable. Nonetheless I would like to argue for a high quality standard of metrics early on, since the insights that you'll get by understanding your metrics will often be highly actionable. And of course it will make your conversations with investors who want to understand your numbers much easier. At the minimum, I think you should try to make sure from the beginning that you collect the data that will allow you to do more sophisticated analyses later.

Back to the original point, why is a cohort analysis so crucial? Let's take a look at the following chart of an imaginary startup:



Looks like the company is growing nicely, hm? No exponential growth, but constant, linear growth. Now take a look at this chart:



It looks like the number of active users is growing even steeper. Great! 

But now let's take a look at the underlying cohort numbers in this Google Sheet.

The number of new signups are contained in cells D5 to D14, and the cumulated number of signups are in cells E5 to E14 (I used that one to make the chart look better :-) ). The number of active users, which the second chart shows, is contained in cells H15 to Q15.

In case you're not familiar with cohort analyses, here's a quick introduction:

• Each row represents a signup cohort.
• In the "right-aligned" cohort analysis at the top you can see the number of active users of each signup cohort for every calendar month. So, for example, I5 is the number of users who signed up in January 2011 and were active in February 2011, and I6 is the number of users who signed up in February 2011 and were active in February 2011. Accordingly, if you go down to the "Total" numbers in row 15 you'll see the total number of active users for each calendar month. These are the numbers which form the activity chart above.
• In the "left-aligned" cohort analysis at the bottom you can see the number of active users of each signup cohort for every user lifetime month. Example: I20 shows the number of users who signed up in February 2011 and were active in March 2011 (=user lifetime month #2 of the February 2011 cohort).

Row 29 and 30 calculate the monthly drop-off rate and the percentage of users who is still active n months after signing up. Here's where it gets really interesting. Our imaginary startup has a monthly drop-off rate of 50%, which means that after 6 months only 4% of the users are still active! That's not easy to see if you're just looking at the charts above, is it?

Note: In the example that I'm using, a user who registers in month x qualifies as an active user in that month. The assumption is that he logs in at least once after registration and that that log-in makes him count as an active user. That effect completely distorts the real activity numbers. If you're signing up a growing number of users it means that your activity numbers can basically only go up regardless of any real usage activity. So - if you're talking about "active users" it's best to leave out the users who have signed up in the timeframe that you're talking about. That is, if you're talking about the number of active users from last week, include only the users who signed up until the week before.

By the way, while I've used "activity" in this example you can of course use cohort analyses to track other aspects, too. As a SaaS company, for example, you should have a cohort analysis for retention/churn. As an online shop, you should have a cohort analysis for repeat purchases.

Point Nine loves animals

About one and a half years ago I became a vegetarian, after coming to the conclusion that it's impossible to ethically justify to kill – and in almost all case inflict enormous suffering on – living creatures that are capable of experiencing pain, just for the pleasure of eating meat (which, make no mistake about it, is a huge pleasure). Maybe I'll write more about that topic in another post. In the meantime, if you're interested in the rationale behind my decision, read Jonathan Safran Foer's bestseller "Eating Animals" or the hard to swallow but brilliant books of Peter Singer.

Today I want to write about different kinds of animals (sorry for the misleading introduction). I'm talking about business development animals. Coding animals. Usability animals. Design animals. Sales animals. Marketing animals. In short: Founders who work like beasts to make their startups successful.

In the words of the priceless Paul Graham:

What do I mean by good people? One of the best tricks I learned during our startup was a rule for deciding who to hire. Could you describe the person as an animal? It might be hard to translate that into another language, but I think everyone in the US knows what it means. It means someone who takes their work a little too seriously; someone who does what they do so well that they pass right through professional and cross over into obsessive. 

What it means specifically depends on the job: a salesperson who just won't take no for an answer; a hacker who will stay up till 4:00 AM rather than go to bed leaving code with a bug in it; a PR person who will cold-call New York Times reporters on their cell phones; a graphic designer who feels physical pain when something is two millimeters out of place.

Almost everyone who worked for us was an animal at what they did. The woman in charge of sales was so tenacious that I used to feel sorry for potential customers on the phone with her. You could sense them squirming on the hook, but you knew there would be no rest for them till they'd signed up.

When I read Paul's essay "How to start a startup" again a few days ago, I thought about the founders of the companies that I've invested in and was struck by how much truth there is in the "animal test". What all successful founders seem to have in common is perfectionism at what they're doing, coupled with a relentless drive.

I had to think about my old friend Stefan Smalla, who, less than one year after founding, has rolled out Westwing to fifteen countries while managing spectacular growth in Germany at the same time. I also had to think about Guk Kim and Ryan Fyfe, the founders of Cibando and Shiftplanning, respectively. Both are in their mid-twenties and started their companies all by themselves, did everything by themselves in the early days and are now doing an incredible job at running and scaling their companies. These are just three examples – I could go on and on and talk about every founder that I've invested in!

In the meantime, the "animal test" has become something like a running gag here at Point Nine Capital. Whenever we talk about a potential investment we're asking ourselves: Are these guys animals?

Financial planning for SaaS startups

[Update 03/23/16: I've created an improved version of the template - check it out!]

A few people who read my recent post about financial planning asked if I could provide an example for a good financial plan, so I'd like to post one here. The plan is very similar to the one that I created in the very early days at Zendesk and re-used a few times in the meantime, but I had to make a few adjustments to make it more generic.

It's a simple plan for an early-stage SaaS startup with a low-touch sales model – a company which markets a SaaS solution via its website, offers a 30 day free trial, gets most of its trial users organically and through online marketing and converts them into paying customer with very little human interaction. Therefore the key drivers of my imaginary startup are organic growth rate, marketing budget and customer acquisition costs, conversion rate, ARPU and churn rate. If you have a SaaS startup with a higher-touch sales model where revenue growth is largely driven by sales headcount, the plan needs to be modified accordingly.

For non-SaaS business models the template needs to be modified more heavily or may not be useful at all, other than that it shows my way of thinking around business planning. That was one of the points that I was trying to make in the original blog post – you can't simply re-use a template, your financial plan needs to mirror your specific business case.

Here's the plan as a Google spreadsheet. If you want the original Excel version please let me know (yes, Excel is one of the few desktop apps that I'm still using).

[Update: If you'd like to get the original Excel version, which looks a bit nicer, you can download it here. If you like it, tweet it!]

The grey box at the left contains all assumptions (blue text color). Everything on the right is calculated, no hard-coded numbers there. I have, of course, used dummy numbers for all assumptions.

The model should be largely self-explanatory but here are a few notes:

• It all starts with the signups that you're adding. I've separated signups into non-trackable signups (signups that you get from word of mouth, PR and so on) and trackable signups (signups from AdWords and other paid advertising where you can track the costs of acquiring a signup). You may have to break this down further depending on your customer acquisition channels.
• Then I'm assuming that you're converting a certain percentage of signups into paying customers (with a one month time lag, assuming that you have a 30 day free trial). The model contains just one conversion rate regardless of the signup source. You can change that if your conversion rate varies depending on the signup source.
• Next up, I'm calculating revenue by multiplying the (approximate) number of customers that you have mid-month by your average revenue per account. If you have a tiered pricing model or a per-seat pricing, consider modeling that.
• Moving down to the costs side – this should all be self-explanatory. Just replace the dummy values by your actual values or assumptions and add additional expense categories as needed.
• Regarding P&L and cash-flow, I'm keeping things really simple here and am assuming that your EBIT is equal to your operating cash-flow. That is, I'm assuming that you're charging your customers on a monthly basis, that you're not making any investments (in accounting terms) and that there are no taxes or interest payments. I think that simplification works well for most very early-stage SaaS startups but it of course needs to get more sophisticated as you grow.
• Last – but not least because this is one of my favorite parts – the sanity checks: I've seen MANY financial plans with an EBIT margin north of 90% in year 3. That's a classic mistake which can happen if you project your revenues to grow exponentially but don't provision realistic increases on the costs side as well. Adding some sanity checks will help you spot these mistakes and make sure that your plan remains realistic. For example, I've included the number of paying customers which each support agent needs to take care of. If that number gets too high you need to allow for more support staff.

Avoiding Parkinson's Law of Triviality in your financial plan

In the last few years I've seen a lot of financial plans, and since we started Point Nine in the middle of last year that volume has been skyrocketing. I've seen everything from just a few numbers in an email to extremely sophisticated Excel spreadsheets with dozens of tabs and tens of thousands of cells, and I thought I'd offer some advice on what I think a good financial plan looks like.

To begin with, among the worst financial plans are those that you get if you take a template from a business plan competition or a bank in Germany and don't customize it to your particular business. These templates are usually very detailed on the costs side, listing everything from magazine subscriptions to stationary and postage, but the revenue projection is just one line – a pure estimate that is coming out of nowhere. Parkinson's Law of Triviality comes to mind!

The best financial plans of early-stage Internet startups in my opinion:

• are relatively simple – just one Excel tab or a few at most (a later-stage company will often require a more complex plan but in the beginning you can keep it simple)
• are based on the key drivers of your business (your conversion funnel, your projected ARPU, churn etc.)
• make your assumptions transparent and easy to change
• contain very few hard-coded numbers which would make the plan hard to revise (an exception to this are historic numbers, of course)
• avoid Parkinson's Law of Triviality – spend more effort on what really matters and lump together stuff like tiny expense categories
• contain a few extra lines for sanity checks (anyone who will seriously review your plan will perform them anyway, so why not make their lives a little easier?)

If anyone is interested in further details, please let me know in the comments section, email me or send me a tweet and I can add some more color and post an example.

"Launching a web startup became 10x cheaper..."

The conventional wisdom is that starting a web business is (at least) 10x less expensive today than it was 10-15 years ago. It’s said that a decade ago, you needed millions of venture capital in order to launch an Internet startup whereas today, thanks to open-source software, cheap hardware and new ways to acquire users for free (in particular virally via Facebook/Twitter and with SEO via Google), you can do the same with a small fraction of that. And that, while great for entrepreneurs, makes it difficult for large VC funds with many hundred million dollars under management, to deploy their capital because startups ask for less money.

I’ve heard it dozens of times, from VCs, founders, bloggers and others. It’s almost like a mantra, part of the Web 2.0 creation myth, which everyone believes without challenging it. I always wondered if that theory is true, because it didn’t cost Christopher Muenchhoff and me more than about $100 to build and launch DealPilot.com in 1997. That, approximately, was the cost of one month of shared hosting, and in the second month, revenues paid for the hosting costs already. The first “big” investment was our own server, around $3000 as far as I remember. We did raise some money to expand the business later, but that was much later – around nine months after launching the service. So it clearly was possible to launch a state-of-the-art web service back then with little to no investment. DealPilot.com wasn't the only one, of course, I'm just using it as an example.

When I say “state-of-the-art”, I mean state-of-the-art based on 1997/1998 standards, of course. That's what was needed to be competitive. We of course wouldn’t have been able to build a video streaming site à la YouTube for $100 (hardware and bandwidth was too expensive), and launching an online shop would have been more expensive too (Magento didn’t exist yet). That’s logical, but trivial, and not what the theory wants to say, right?

In other words, I think the theory surely is that “starting a web startup in 2011 that is competitive in 2011 costs 10x less than it cost to build a web startup in 1998 that was competitive by 1998 standards”, right? (If the theory was “starting a web startup in 2011 that is competitive in 2011 costs 10x less than it cost to build a web startup in 1998 that was competitive by 2011 standards” that would of course be true, but I think it wouldn’t mean anything. Being competitive by 2011 standards (often) means that you need an iPhone app. In 1998 there was no iPhone. Get the point?)

And that is what I’m questioning.

Now, if the theory is wrong and it wasn’t that much more expensive to build a web business back then, why did startups raise so much VC at the end of the 1990s? One possible answer is simply “because they could” (and because everyone else did, and you didn’t want to be overtaken by better-funded, faster-growing competitors). Fuelled by a crazy IPO market, there simply was an incredible amount of venture capital available. Maybe that’s the real reason, or at least part of it, why it now appears that launching a web startup was so expensive in the 90s. What do you think?

Paul Graham on Enterprise Software

A link in today's TechCrunch posting about Y Combinator's "Request for Startups" idea brought me to an earlier "Startups ideas we'd like to fund" list, published by Paul Graham about a year ago. It's a terrific list of ideas, and I applaud Paul for sharing them (execution is everything!). If you're toying with the idea of founding an Internet startup and you're not sure what kind of business you're going to start, I highly recommend going through the list. I'm sure you'll find lots of inspiration.

One thing that I'd like to quote from the original article is the paragraph on Enterprise Software:

Enterprise software companies sell bad software for huge amounts of money. They get away with it for a variety of reasons that link together to form a sort of protective wall. But the software world is changing. I suspect that if you study different parts of the enterprise software business (not just what the software does, but more importantly, how it's sold) you'll find parts that could be picked off by startups.

One way to start is to make things for smaller companies, because they can't afford the overpriced stuff made for big ones. They're also easier to sell to.

Brilliant.

A nice way for your beta site to say "Feedback please"

Have a look at the screenshots below:







What do these otherwise completely unrelated Web 2.0 sites have in common? Instead of the good old "Send Feedback" link in the page footer, all three of them prominently feature a large, red, eye-catchy "beta feedback" badge.

If you click on the badge, a window that contains the feedback submission form pops up; usually instantly, without a full page reload, so you can type in your feedback right away. Often the background of the page is greyed out, producing a lightbox effect which puts the feedback form into full focus.

I think this is a smart advancement of the notorious Web 2.0 beta badge. If you’re featuring the "Send feedback" link so prominently, firstly and obviously more people will notice it and provide you with valuable comments, bug reports and suggestions. Secondly, you show your audience that you really care about what your users think. Consider using this emerging UI pattern - at least as long as you’re in public beta (which you might be forever).

Pagebull - your visual Internet search engine

A few days ago, Pagebull went from stealth mode into public beta. Pagebull is the latest brainchild of my good friend and long-term business partner Christopher Münchhoff. It's a new search engine that provides a radically new user interface: Instead of a text-based list of the sites that match your search query, it shows you a grid of large screenshots of those sites.

The idea behind Pagebull's approach is that when you go to a site, you'll often know after a second if the site has what your looking for or not - and an inappropriate amount of time is wasted going back and forth between Google and the "target" sites. Pagebull now lets you glance over nine or more screenshots at a time, saving you the effort of clicking from one target site to the next.

What's interesting is that Pagebull benefits from two important industry trends: More bandwidth and larger screens. Using Pageflakes on a 30" screen and a super-fast cable connection must be fun!

It would be interesting to conduct a study to find out how much time Pagebull saves an average Internet user who spends, say, an hour per week on Google. Then just extrapolate that to all American office workers, and the US economy can probably save a few billion worth of productivity per year. ;-)

Seriously: Pagebull will not drive Google out of business any time soon, but it's an extremely impressive, innovate approach to improve the search engine user experience on the Web.

Try it!

Ugenie unlocks hidden savings

TechCrunch today profiled a new comparison shopping site called Ugenie. What makes Ugenie different from most (all?) other similar sites is that the service not only finds the best price on a single item but also the best total price on any bundle of books, CDs, DVDs or games that you happen to be interested in.

Ugenie finds the best bottom-line prices for you, taking into account shipping costs, taxes and discounts. What's more, the service also takes into account that sometimes it's cheaper to pay all items from one merchant but in other cases it's cheaper to spread an order across several shops. If you think about the number of possible combinations to buy, say, five items from 35 shops, that's quickly becoming pretty complicated. And remember that in addition to the plain item prices, Ugenie also needs to take into account shipping costs, which can depend on various factors like the number of items, the order price and the order weight, or a combination thereof. The fact that taxes can depend on the location of the shop as well as the location of the customer doesn't make it easier.

Why am I writing about Ugenie? Because I really like the feature described above, because it's a cool service and because I remain interested in the comparison shopping space ever since co-founding comparison shopping site DealPilot.com (formerly called Acses) in 1997. But also because I couldn't resist telling the world that we invented the "best price for a bundle of items" feature back in 1998. ;-)

Here's the proof:



What you're seeing here is the "Comparison Shopping Cart" (that's how we coined it) of a user who's looking for a book, a movie (no, not a DVD, a VHS cassette!) and a CD. If the user scrolls down he'd see a list of all offers, taking into account all those factors described above.

Don't worry guys, we didn't patent it. Good luck with Ugenie!

The Hottest Web 2.0 Betas

The "Museum of Modern Betas", a site that is dedicated to keeping track of all those new Web 2.0 apps that are popping up every day, added a great resource to its site: The hottest betas in the webosphere. The list is based on the number of bookmarks at del.icio.us added within the last 7 days, which is a really interesting parameter. Pretty interesting for everyone who tries to discover successful startups before everyone else does (VCs, journalists,...).

FON + Skype + Netgear = Trouble for BigTelco

Skype announced that it invests in FON, the P2P WiFi company I blogged about earlier. Add to this new PC-less Skype phones from Netgear, Creative and others (see a posting of Christian Leybold from BV Capital) and you have the ingredients for some major trouble for the traditional telco business.

Of course, this is not new. Skype alone is an incredibly disruptive force. But the flood of new products and services centered around Skype shows just how strong the creative destruction is which Skype has triggered. I'm not saying that the big telcos are doomed. But they must find new cash cows - selling long-distance minutes at high prices will become increasingly difficult.

Pandora's Box

Most readers probably know Pandora, but maybe there are still some who don't. Pandora is a wonderful music service that lets you listen to a music selection tailored to your taste. You start by entering the name of a band or a title that you like. Pandora then starts playing songs of a similar style. You can rate any song you hear to educate Pandora about your taste, so over the time the selection becomes better and better.

You can read a little bit about the underlying magic here. I assume in addition to the results from The Music Genome Project they utilize collaborative filtering (like Amazon's "if you like this book, you may also like these books" feature) so that the service will automatically become better as more users use it. I still don't know exactly how it works, but it seems to work pretty well. I like the majority of the songs suggested by Pandora and stumbled on great music by bands I never heard of before. So either it works, or I'm such a philistine that you could play any song to me and I'll like it.

In any case you should try it. Amazingly, it's even free.

The Best Web 2.0 Software of 2005

Dion Hinchcliffe put together a great list of the best Web 2.0 applications released in 2005. Interestingly, only one of about 30 applications has been developed by a big corporation (Microsoft's Start.com) while the rest has been developed by start-ups - some of them tiny one- or two-person companies. As far as Web 2.0 is concerned, the greatest innovations still come from start-ups (although the GYM is close, as demonstrated with software like Google Earth and the new Yahoo! Mail).

So far, two from the list have been acquired by one of the big boys: Flickr and Del.icio.us. I'm sure that in a year from now, a couple of others from the list will have been snapped up. My best guesses are Writely and Netvibes.

Congrats to Sam (Writely), Tariq (Netvibes), Ian (Openomy), Jason (Writeboard and Ta-Da-List) and to everyone else who's working on the next generation of Internet software.

Last but not least some sites I'd suggest to add:

• CalendarHub (how about adding a "calendars" category, Dion?)
• TailRank (Blog Filters)
• Reddit (Peer Production)
• NumSum (maybe add a Web Excel category?)

BookBurro - tough times ahead for Amazon.com?

BookBurro is a smart Firefox plug-in created by Jesse Andrews that lets you find the best book deals while you shop. When you're looking at a book page on a site like Amazon.com or Barnesandnoble.com, a little window magically appears and tells you the prices for that particular book from about 10 online bookstores. Comparing book prices doesn't get much easier or more convenient than this!

At first sight, one could think that a tool like this must cause considerable headaches to Amazon.com. After all it allows customers to use Amazon.com's unbeaten site for browsing but proceed to another retailer to make the purchase with literally one mouse click. While comparison shopping sites like Shopping.com and Shopzilla are very popular and while I think they do contribute to limiting the pricing power of brand name online shops, the value of Amazon.com's brand shouldn't be underestimated.

During the first wave of comparison shopping engines from 1998-1999, some analysts predicted that online retailers would never be able to make a decent profit because the radical removement of friction would effectively turn online shopping into a commodity market. They underestimated people's deep desire for convenience and the level of trust associated with Amazon.com.

As far as BookBurro is concerned, it's interesting to note that the concept of on-the-fly price comparison has been around for years but never really took off. I know what I'm talking about, as my startup DealPilot.com launched a similar product, a browser companion toolbar called DealPilot Express, back in 1999. It never became as successful as the website, so Shopping.com (which acquired DealPilot.com) buried it after a while. RUSure, ClickTheButton and all other competitors of us from that time met the same fate.

BookBurro is easy to install, unobtrusive and seems to work very well. It's definitely better than the first breed of such tools. It'll be interesting to see if they have success.

Thanks to Library Stuff for the pointer.

P2P WiFi

Via Roland Tanglao: FON allows users to share their WiFi networks with other users. They're launching in Spain, but according to Joi Ito they plan to push out worldwide.

The idea is interesting: If you have DSL, most of the time you're using only a tiny fraction of your available bandwidth. Why not give some of your extra bandwidth to that guy sitting in the café next door who is going online via an expensive UMTS connection? If you think of VoIP (read: Skype) via WLAN, it's getting even more interesting.

In Germany, sofanetworks is trying the same. They have a slightly different focus though, as they also target to neighbours who want to share their Internet connection using a WLAN. So they not only want to save you costs while you're on the road, they even want to let you save your home DSL connection.

Will FON and/or sofanetworks succeed? I'm still skeptical. One reason is security. What if the people who I share my Internet connection with will download illegal content from the Web? I'm sure both companies address this concern. But will users take on the hassle of learning more about the security situation or will they just stay away from the offer? The upside, after all, is rather limited: A share of the revenues generated with the user's WiFi (which I assume will be a few bucks per month in most cases), plus the promise of being part of a movement which kicks the big telcos in their pants.

Another reason why I'm not convinced yet is that they need a large critical mass of customers in order to successfully match connection sharers with connection users. At least, FON's founder Martin Varsavsky has experience with that: Before founding FON, he founded telephone company Jazztel and Internet portal Ya.com in Spain, both of which became large companies.

BTW, are you a "Bill" or a "Linus"? At FON, you can decide if you want to become a "Bill" or a "Linus". Bills get 50% of the revenues generated through their WiFis. Linuses, on the other hand, don't get the revenue share but in exchange they get free roaming among the FON network.

Openomy - building the file system for Web 2.0

Openomy wants to become for the Web what FAT was for MS-DOS and NTFS is for Windows. No idea what I'm talking of? (I don't know the nerd ratio of my readership.) Then here's a better description, taken from Openomy's site:

Openomy is an online file system. You can store files on Openomy and access them from any computer. Openomy organizes files and users via tags (as opposed to folders). You can choose to keep your files guarded by Openomy, or allow certain outside applications (of your choice) to do new and interesting things with your data.

In case you're still not sure why this is a great idea, consider this: At the moment, your Writely files are stored on Writely's servers, your Num Sum files are stored on Num Sum's servers and your Basecamp files are stored on Basecamp's servers. (If you're not using any of these applications, please read this posting again in two years. Chances are you'll be using one of these services, or a similar one, by then. BTW, why not send yourself a reminder in two years to see if my fortune-telling is right?)

So, do you have a separate hard drive for Word, Excel and Powerpoint? No? Then I'm not sure if it makes sense to have a separate file system and storage server for each Web-based application.

I think Openomy is a really, really smart idea. I also think a viable business can be built around it. To enter the market I think they should build one really cool application that is closely tied with Openomy and give it away for free or for as little money as possible. The most obvious application, of course, is to address the terribly underserved market for online storage and remote backup. And while not offering a perfect solution for that need yet, they're already beginning to do just that.

10 Companies Michael Arrington would like to profile (but don't exist)

Michael Arrington from TechCrunch published a terrific list of 10 companies he'd like to profile but don't exist. Usually when you find a list of business ideas somewhere it's either "get rich quick" spam or a suggestion to start your own pizza delivery service. This one is different.

Every single one of these ideas is highly interesting. Some of them have the potential to become huge businesses (e.g. "Online File Storage" and "Open Source Yellow Pages"). Some of them are smaller but are easier to build and could still support a very viable and profitable business. "Blog/website Email Lists" is one of those.

This is one of the most insightful and valuable blog postings I read in a while - thanks, Michael.

Check it out. If you're building one of these businesses, feel free to drop me a line to see if I can help you in any way.

Meetro - location-aware IM

Meetro is a location-aware social networking service with instant messenger integration. From their website:

Technically speaking, Meetro is radius and proximity based software. Untechnically speaking, it finds like-minded people around you instantly. Wherever you are. So whether you’re in-town or out of town, Meetro gets you on the town with old friends or new acquaintances.

Via Tipmonkies.