Entries Tagged 'strategy' ↓

A massive misallocation of online advertising dollars

In an earlier blog post, I talked about how sites that generate purchasing intent (mainly “content” sites) are being under-allocated advertising dollars versus sites that harvest purchasing intent (search engines, coupon sites, comparison shopping sites, etc).  As a result, most content sites are left haggling over CPM-based brand advertising instead of sponsored links for the bulk of their revenue.

But there is an additional problem:  even among sites that monetize via sponsored links there is a large overallocation of advertising spending on links that are near the “end of the purchasing process” (or “end of the funnel”). For example, an average camera buyer takes 30 days and clicks on approximately 3 sponsored links from the beginning of researching cameras to actually purchasing one.   Yet in most cases only the last click gets credit, by which I mean:  1) if it’s an affiliate (CPA) deal, it is literally usually the case that only the last affiliate (the site that drops the last cookie) gets paid, 2) if it’s a CPC or CPM deal, most advertisers don’t properly track the users across multiple site visits so simply attribute conversion to the most recent click, causing them to over-allocate to end-of-funnel links 3) if it’s a non-sponsored link (like Google natural search links) the advertiser might over-credit SEO when in fact the natural search click was just the final navigational step in a long process that involved sponsored links along the way.

What this means is there are two huge misallocations of advertising dollars online: the first from intent generators to intent harvesters; the second from intent harvesters that are at the beginning or middle of the purchasing process to those at the end of the purchasing process.  This is not just a problem for internet advertisers and businesses – it affects all internet users.  Where advertising dollars flow, money gets invested. It is well known that content sites are suffering, many are even on their way to dying. Additionally, product/service sites that started off focusing on research are forced to move more and more toward end-of-funnel activities.  Take a look at how sites like TripAdvisor and CNET have devoted increasing real estate to the final purchasing click instead of research.  For the most part, you don’t get paid for the actual research since it’s too high in the funnel.

As with all large problems, this misallocation of advertising dollars also presents a number of opportunities.  One opportunity is for advertisers to correctly attribute their spending by tracking users through the entire purchasing process (in the case of cameras, the full 30 days and multiple sponsored clicks).  Very likely, these sites are currently overpaying end-of-funnel sites (e.g. coupon sites) and underpaying top-of-funnel sites (e.g. research sites). There is also an opportunity for companies that provide technology to help track this better. Finally, if over time advertising dollars do indeed shift to being correctly allocated, this will allow research sites to be pure research sites, content sites to be pure content sites, etc instead of everyone trying to clutter their sites with repetitive, “last click” functionality.


Some thoughts on the “geo stack”

Significant new technologies often emerge as “stacks.” You can look at stacks through a technological (e.g. OSI stack) or business lens. Here I am using a business lens, thus dividing layers by function and including things that aren’t technologies but have economic value, e.g. relationships with customers and users.

Normally stacks are constructed from the bottom up and some layers turn out to be valuable and others do not (Christensen argues compellingly that stacks tend to alternate between commodity and non-commodity layers).

The PC is a famous stack.  In the 80’s and 90’s the most valuable layers were the processor (Intel won), OS (Microsoft won), and applications (Microsoft mostly won with Office). Assembly of desktops became a commodity which Dell exploited (you can still make profits on commodity layers, you just need to take a low-cost strategy). The PC demonstrates how hard it is to predict which layers will become valuable: otherwise IBM would never have allowed Microsoft to own the OS.

The internet is another famous stack. In the 90’s a ton of investment went into the infrastructure layer – switches, fiber, CDNs etc. Innovation on that layer continues (particularly in wireless), but mostly the action has moved up the stack to web apps.

An interesting new, emerging stack is the “geo stack.”  The first layer is latitude/longitude location detection. This is mainly provided by satellites and GPS chips which seem to be getting so affordable they will be in every mobile device soon.

The next layer is connecting lat/long to human-understandable locations. Google Maps, NAVTEQ etc. do this by connecting lat/long to roads. Location-based apps like Foursquare, Gowalla, and Yelp do this by connecting lat/long to “venues.” It seems Gowalla is building their own venue database.  I assume Yelp has built their own.  I don’t know how Foursquare gets theirs. I suspect venue databases will become mostly a commodity as they are fairly inexpensive to build and once built mostly interchangeable.

The next layer is the relationship with the user, particularly getting a user’s permission to track her location.  Apps like Foursquare require explicit check-ins at each venue. Other apps like Loopt automatically check in for you. Building this trust relationship with users could be very valuable.

The next layer is what I’ll call “recommendations”:  giving useful advice to users based on their location.  Maps do this by providing driving direction, traffic info etc. Foursquare is doing this with “tips.” I think recommendations will be critical for geo apps to appeal to Normals.  Geo apps are currently wooing early adopters with badges, games, and the idea that you might have a serendipitous meeting with your friends at a bar.  I suspect these incentives won’t work for the broader population, but recommendations could.  Recommendation data is hard to build and vast, hence could be a very valuable layer. (I am biased here as Hunch is working on this layer).

Social graphs could be a geo layer. It’s rumored that Facebook will be adding venue check ins soon.  Facebook has by far the largest (opt in) social graph.  As the recent Google Buzz debacle demonstrated, it’s not obvious that the people you email with are the same as the people you friend on Facebook.  Perhaps the people you want to share your location with are different than the people you friend on Facebook. If so, there could emerge valuable geo-specific social graphs.

Finally, monetization could be a very valuable layer.  There are (at least) two parts to monetizing location. Getting local businesses to embrace the internet has been very slow going. Companies that make money on local businesses today (Yelp, Yext, ReachLocal) use expensive outbound calling and other “push” techniques to sign up local businesses. There remains a huge opportunity to supplant the yellow pages as the default advertising platform in local business owners’ minds. If apps like Foursquare can build up enough marketing / PR momentum that every restaurant, dry cleaner etc feels like they need to “get on Foursquare” this could finally open the floodgates for local business advertising.

The second part of monetizing location is facilitating and tracking offline purchases. 90%+ of purchases are still offline, although for many of those transactions people do research and make their decisions online. The internet doesn’t get paid for these transactions.  Companies like Milo (disclosure: I’m an investor) are doing interesting things in this space and I expect we’ll see a lot more activity on this layer soon.

Should Apple be more open?

It is almost religious orthodoxy in the tech community that “open” is better than “closed.” For example, there have widespread complaints about Apple’s “closed” iPhone app approval process. People also argue Apple is making the same strategic mistake all over again versus Android that it made versus Windows*. The belief is that Android will eventually beat the iPhone OS with an “open” strategy (hardware-agnostic, no app approval process) just as Windows beat Apple’s OS in the 90’s.

With respect to requiring apps to be approved, consider the current state of the iPhone platform. There are over 100,000 apps and thus far not a single virus, worm, spyware app etc. (I don’t count utterly farfetched theoretical scenarios). As a would-be iPhone developer, I can report firsthand that the Apple approval process is a nightmare and should be overhauled. But what’s the alternative? Before the iPhone, getting your app on a phone meant doing complicated and expensive business development deals with wireless carriers. At the other end of the spectrum: If the iPhone OS were completely open, would we really have better apps?  What apps are we missing today besides viruses?

With respect to the strategic issue of tightly integrating the iPhone/iPad software and hardware, a strong case can be made that Apple’s “closed” strategy is smart. Clay Christensen has given us the only serious theory I know of to predict when it’s optimal for a company to adopt an open versus closed strategy for (among other things) operating systems. The basic idea is that every new tech product starts out undershooting customer needs and then – because technology gets better faster than customers needs go up - eventually “overshoots” them. (PC’s have overshot today – most people don’t care if the processors get faster or Windows adds new features). Once a product overshoots, the basis of competition shifts from things like features and performance to things like price.

The key difference today between desktop computers and mobile devices is that mobile devices still have a long way to go before customers don’t want more speed, more features, better battery life, smaller size, etc. Just look at all the complaints yesterday about the iPad - that it lacks multitasking, a camera, is too heavy, has poor battery life, etc. This despite the fact that Apple is now even building their own semiconductors (!) to squeeze every last bit of performance out of the iPad. Until mobile devices compete mainly on price (probably a decade from now), tight vertical integration will produce the best device and is likely the best strategy.

*It’s worth noting that Steve Jobs wasn’t the one who screwed up Apple. Jobs co-founded Apple in 1976. He was pushed out in in May 1985 when the company was valued at about $2.2B. He returned in 1996 when Apple was worth $3B. Today it is worth $187B.

Incumbents

Almost every startup has big companies (“incumbents”) that are at some point potential acquirers or competitors.  For internet startups that primarily means Google and Microsoft, and to a far lesser extent Yahoo and AOL.  (And likely more and more Apple, Facebook and even Twitter?).

The first thing to try to figure out is whether what you are building will eventually be on the incumbent’s product roadmap. The best way to do predict this is to figure out whether what you are doing is strategic for the company. (I try to outline what I think is strategic for Google here). Note that asking people who work at the incumbents isn’t very useful – even they don’t know what will be important to them in, say, two years.

If what you are doing is strategic for the incumbents, be prepared for them to enter the market at some point. This could be good for you if you build a great product, recruit a great team, and are happy with a “product sale” or “trade sale” – usually sub $50M. If you are going for this size outcome, you should plan your financing strategy appropriately. Trade sales are generally great for bootstrapped or seed-funded companies but bad if you have raised lots of VC money.

If your product is strategic for the incumbent and you’re shooting for a bigger outcome, you probably need to either 1) be far enough ahead of the curve that by the time the big guys get there you’re already entrenched, or 2) be doing something the big guys aren’t good at. Google has been good at a surprising number of things. One important area they haven’t been good at (yet) is software with a social component (Google Video vs YouTube, Orkut vs Facebook, Knol vs Wikipedia, etc).

The final question to ask is whether your product is disruptive or sustaining (in the Christensen sense).  If it’s disruptive, you most likely will go unnoticed by the incumbents for a long time (because it will look like a toy to them). If the your technology is sustaining and you get noticed early you probably want to try to sell (and if you can’t, pivot). My last company, SiteAdvisor, was very much a sustaining technology, and the big guys literally told us if we didn’t sell they’d build it. In that case, the gig is up and you gotta sell.

The next big thing will start out looking like a toy

One of the amazing things about the internet economy is how different the list of top internet properties today looks from the list ten years ago.  It wasn’t as if those former top companies were complacent – most of them acquired and built products like crazy to avoid being displaced.

The reason big new things sneak by incumbents is that the next big thing always starts out being dismissed as a “toy.”  This is one of the main insights of Clay Christensen’s “disruptive technology” theory. This theory starts with the observation that technologies tend to get better at a faster rate than users’ needs increase. From this simple insight follows all kinds of interesting conclusions about how markets and products change over time.

Disruptive technologies are dismissed as toys because when they are first launched they “undershoot” user needs. The first telephone could only carry voices a mile or two. The leading telco of the time, Western Union, passed on acquiring the phone because they didn’t see how it could possibly be useful to businesses and railroads – their primary customers. What they failed to anticipate was how rapidly telephone technology and infrastructure would improve (technology adoption is usually non-linear due to so-called complementary network effects). The same was true of how mainframe companies viewed the PC (microcomputer), and how modern telecom companies viewed Skype. (Christensen has many more examples in his books).

This does not mean every product that looks like a toy will turn out to be the next big thing. To distinguish toys that are disruptive from toys that will remain just toys, you need to look at products as processes. Obviously, products get better inasmuch as the designer adds features, but this is a relatively weak force. Much more powerful are external forces: microchips getting cheaper, bandwidth becoming ubiquitous, mobile devices getting smarter, etc. For a product to be disruptive it needs to be designed to ride these changes up the utility curve.

Social software is an interesting special case where the strongest forces of improvement are users’ actions. As Clay Shirky explains in his latest book, Wikipedia is literally a process – every day it is edited by spammers, vandals, wackos etc., yet every day the good guys make it better at a faster rate. If you had gone back to 2001 and analyzed Wikipedia as a static product it would have looked very much like a toy. The reason Wikipedia works so brilliantly are subtle design features that sculpt the torrent of user edits such that they yield a net improvement over time. Since users’ needs for encyclopedic information remains relatively steady, as long as Wikipedia got steadily better, it would eventually meet and surpass user needs.

A product doesn’t have to be disruptive to be valuable. There are plenty of products that are useful from day one and continue being useful long term. These are what Christensen calls sustaining technologies. When startups build useful sustaining technologies, they are often quickly acquired or copied by incumbents. If your timing and execution is right, you can create a very successful business on the back of a sustaining technology.

But startups with sustaining technologies are very unlikely to be the new ones we see on top lists in 2020. Those will be disruptive technologies – the ones that sneak by because people dismiss them as toys.

What’s strategic for Google?

Google seems to be releasing or acquiring new products almost daily. It’s one thing for a couple of programmers to hack together a side project. It’s another thing for Google to put gobs of time and money behind it. The best way to predict how committed Google will be to a given project is to figure out whether it is “strategic” or not.

Google makes 99% of their revenue selling text ads for things like airplane tickets, dvd players, and malpractice lawyers. A project is strategic for Google if it affects what sits between the person clicking on an ad and the company paying for the ad. Here is my rough breakdown of the “layers in the stack” between humans and the money:

Human - device – OS – browser – bandwidth –  websites - ads – ad tech – relationship to advertiser – $$$

At each layer, Google either wants to dominate it or commoditize it. (For more on the strategic move known as commoditizing the complement, see here, here and here). Here’s my a brief analysis of the more interesting layers:

Device: Desktop hardware already commoditized. Mobile hardware is not, hence Google Phone (Nexus One).

OS: Not commoditized, and dominated by archenemy (Microsoft)!!   Hence Android/Google Chrome OS is very strategic. Google also needs to remove main reasons people choose Windows. Main reasons (rational ones – ignoring sociological reasons, organizational momentum etc) are Office (hence Google Apps), Outlook (hence Gmail etc), gaming (look for Google to support cross-OS gaming frameworks), and the long tail of Windows-only apps (these are moving to the web anyways but Google is trying to accelerate the trend with programming tools).

Browser: Not commoditized, and dominated by arch enemy! Hence Chrome is strategic, as is alliance with Mozilla, as are strong cross-browser standards that maintain low switching costs.

Bandwidth:  Dominated by wireless carriers, cable operators and telcos. Very hard for Google to dominate without massive infrastructure investment, hence Google is currently trying to commoditize/weaken via 1) more competition (WiMAX via Clearwire, free public Wi-Fi) 2) regulation (net neutrality).

Websites/search (“ad inventory”): Search is obviously dominated by Google. Google’s syndicated ads (AdSense) are dominant because Google has the highest payouts since they have the most advertisers bidding. This in turn is due largely to their hugely valuable anchor property, Google.com. Acquired Youtube to be their anchor property for video/display ads, and DoubleClick to increase their publisher display footprint. On the emerging but fast growing mobile side, presumably they bought AdMob for their publisher relationships (versus advertiser relationships where Google is already dominant). The key risks on this layer are 1) people skip the ads altogether and go straight to, say, Amazon to buy things, 2) someone like Facebook or MS uses anchor property to aggressively compete in syndicated display market.

Relationships to advertisers:  Google is dominant in non-local direct-response ads, both SMB self serve and big company serviced accounts.  They are much weaker in display. Local advertisers (which historically is half of the total ad market) is still a very underdeveloped channel – hence (I presume) the interest in acquiring Yelp.

This doesn’t mean Google will always act strategically. Obviously the company is run by humans who are fallible, emotional, subject to whims, etc. But smart business should be practiced like smart chess: you should make moves that assume your opponents will respond by optimizing their interests.

Google should open source what actually matters: their search ranking algorithm

Websites live or die based on how a small group of programmers at Google decide their sites should rank in Google’s main search results.  As the “router” of the vast majority of traffic on the internet, Google’s secret ranking algorithm is probably is the most powerful piece of software code on the planet.

Google talks a lot about openness and their commitment to open source software. What they are really doing is practicing a classic business strategy known as “commoditizing the complement“*.

Google makes 99% of their revenue by selling text ads for things like plane tickets, dvd players and malpractice lawyers. Many of these ads are syndicated to non-Google properties. But the anchor that gives Google their best “inventory” is the main search engine at Google.com.  And the secret sauce behind Google.com is the algorithm for ranking search results. If Google is really committed to openness, it is this algorithm that they need to open source.

The alleged argument against doing so is that search spammers would be able to learn from the algorithm to improve their spamming methods. This form of argument is an old argument in the security community known as “security through obscurity.” Security through obscurity is a technique generally associated with companies like Microsoft and is generally opposed as ineffective and risky by security experts. When you open source something you give the bad guys more info, but you also enlist an army of good guys to help you fight them.

Until Google open sources what really matters – their search ranking algorithm – you should dismiss all their other open-source talk as empty posturing. And millions of websites will have to continue blindly relying on a small group of anonymous engineers in charge of the secret algorithm that determines their fate.

* You can understand a large portion of technology business strategy by understanding strategies around complements. One major point: companies generally try to reduce the price of their products complements (Joel Spolsky has an excellent discussion of the topic here). If you think of the consumer as having a willingness to pay a fixed N for product A plus complementary product B, then each side is fighting for a bigger piece of the pie. This is why, for example, cable companies and content companies are constantly battling. It is also why Google wants open source operating systems to win, and for broadband to be cheap and ubiquitous. [link to full post]

Why did Skype succeed and Joost fail?

Skype and Joost are interesting companies to compare – they are about as close as you can get to one of those sociological studies that track identical twins who are raised separately.  Skype was a spectacular success.   Joost never got traction and was shut down.  Both were started by Nicklas Zennstrom and Janus Friis, two of the great technology visionaries of our time.  Both were big ideas, trying to disrupt giant, slow-moving incumbents.

There are likely multiple reasons for their different outcomes.  Joost had day-to-day management that didn’t have much startup experience.  The P2P technology that required a download made sense for chat but not for video.  The companies were started at different times:  Skype when there was far less investment in – and therefore competition among – consumer internet products.

But the really important difference was that Joost’s product had a critical input that depended on a stubborn, backward-thinking industry – video content owners.  Whereas Skype could brazenly threaten the industry it sought to disrupt, Joost had to get their blessing.  Eventually the content companies licensed some content to Joost, but not nearly enough to make it competitive with cable TV or other new platforms like Hulu and iTunes.

Real life, non-techie users care almost exclusively about “content.”  They want to watch American Idol and listen to Jay-Z. They don’t really care how that content is delivered or what platform it’s on. Which is why Joost failed, and why so many video and music-related startups have struggled. Skype, on the other hand, didn’t have significant dependencies on other companies – its content, like its technology, was truly peer to peer.

Most popular posts

I’ve been trying to set up a “Popular Posts” widget on the sidebar of this blog but somehow repeatedly failed.  So instead I’ll just post them here:

The most important question to ask before taking seed money link

The challenge of creating a new category link

Man and superman link

The new economy link

Why content sites are getting ripped off link

Software patents should be abolished link

Climbing the wrong hill link

Google and newspapers: the false choice of opting out link

New York City is poised for a tech revival link

To make smarter systems, it’s all about the data link

The one number you should know about your equity grant link

Why you shouldn’t keep your startup idea secret link

Ideal first round funding terms link

The challenge of creating a new category

One of the hardest things to do as a startup is to create a new category.  Bloggers and press have a natural tendency to “pigeonhole” – to group startups into cleanly delineated categories, and then do side-by-side comparisons, comment on the “horserace” between them, and so forth.

At my last startup, SiteAdvisor, we were at first consistently pigeonholed as an anti-phishing toolbar, even though what we did was help search engine users avoid spyware, spam, and scams, which (for various technical reasons) had almost no functional overlap with anti-phishing toolbars. My co-founder at Hunch, Caterina Fake, had a similar experience at Flickr.  Early on, people compared Flickr to existing photo sharing websites – Shutterfly, Ofoto, SnapFish - and found Flickr lacking in features around buying prints, sending greeting cards, etc.

Pigeonholing is one reason startups should actually welcome direct competitors.   It was only once a direct competitor to SiteAdvisor appeared that people started treating “web safety” as its own category (Walt Mossberg was the first one to legitimize the category with this article).

At my current startup, Hunch, being pigeonholed as a so-called Answers site is one of our main marketing challenges.  Hunch is a user-generated website similar to Wikipedia except, instead of creating encyclopedia entries, contributors create decision trees that help other users make choices and decisions.  For example, about 50 computer enthusiasts came together to create this decision tree about computer laptops that helps users with less expertise find the right laptop.  Hunch gets smarter over time as more people contribute to it.  So far, about 10,000 users have made 115,000 contributions to the site.  Last month, our third month after launch, over 600,000 unique visitors used those contributions to make decisions.

Many of the initial reviews of Hunch accurately reflected that Hunch is trying to create a new category of website.  Nevertheless, the tendency to pigeonhole Hunch as an Answers site remains. Answers sites allow users to ask a question and get back direct answers from other people.  There are many Answer sites including Yahoo Answers, Mahalo Answers, Vark, Answerbag, and ChaCha. These are all excellent and useful services – but have as much to do with Hunch as Ofoto had to do with Flickr.

There is no easy solution to avoid being pigeonholed.  All you can do is consistently, straightforwardly describe what you do, and then keep beating that drum over and over until the message gets through.