“There is no fertilizer like the owner’s footprint in the fields.”

Regular inspection makes for fertile ground

My grandparents had a nice business raising cattle. The market for free-range beef drove growth in their business and they cleared more fields and shifted resources to produce the feed they needed for the larger herd over the winter.

The business soon required more work than two people could handle and they decided to hire permanent help to support the daily operations of the farm, maintain the fields and tend to the hay and corn production required for the winter.

The spring and summer went well with crops planted on time and the cattle remaining healthy under new management. Revenues were up and my grandparents thought they were getting what they expected.

They went to Florida.

Returning in March they noticed the herd seemed smaller. Inspecting the numbers, revenue was flat but revenue per head was down. When pressed, the farm manager said the cattle were not keeping weight like they had in the summer. Inspecting further, my grandparents found that the management team had only turned the hay field twice, instead of the three turns they used to achieve. Also, the professional crew had not used proper fertilizer reducing the yield in the corn crop. To make it through the winter feed was rationed and the cattle had lost weight. To meet revenue targets, the one well understood metric for the business, the number of cattle sold per month had been increased.

This was not sustainable. The need for more granular metrics was obvious.

My grandparents assumed that by inspecting revenue they could expect the other measurable aspects of the business to be managed properly. They did not think to set targets for turns of the hay fields, corn yields and total volume of feed projected based on weekly growth. They did not set targets for herd size or average weight per head and did not measure this key driver of revenue sustainability at regular times throughout the year.

In our world of technology start-ups someone once said

“You get what you inspect, not what you expect.”

As your business scales, farming your data can drive significant value. Set goals and measure success against the data that flows out of daily operations. A culture where metrics are transparent and everyone is empowered to take action based on the data is a culture that scales. When this works each team member leaves fertilizing footprints in the fields and, as a founder, you may get what you expect without being inspector and chief.

Defining the data to measure can be difficult, but there is a lot of guidance available. This piece from Josh on cohort analysis is great as is the SaaS metrics PDF published by Bessemer. No matter what your business, a data driven management approach can help you succeed. If you have specific metrics that you use to manage your business or other resources you feel are good sources of guidance I would love to discuss best practices in the comments.

This is an example of previum.

In a previum model, the customer gets the full experience for free in a limited way. In the freemium model they get a limited experience for free in an unlimited way. Both models leverage the power of free for customer acquisition. The critical difference is the previum model forces the user to cross back over the penny gap and become a customer or accept a tangibly limited experience. The freemium model is less effective because it asks the consumer to adopt a limited version of a product and then encourages them to cross back over the penny gap with the promise of a better experience.

Sony has filed for a patent in the video game space that includes a great graphic to illustrate this point. Ask yourself which is more convincing — the Freemium Model:

Freemium: Pay me and I promise to give you a bigger sword. Did I mention, it is WAY bigger!?!

or the Previum Model where you get to experience the big sword and see how much better it can be:

Previum: What's wrong, want the big powerful sword back? You can have it for the low price of...

In the previum model, the consumer gets to see everything you have to offer and to experience it in full, for free. After some period of time or number of uses, you ask them to pay for the services they are enjoying.

The hardest thing you can do in any business is close a sale. You basically have two dials you can turn to get someone to pay:

1. increasing the perceived value of the product (marketing)
2. decreasing the cost or of the product (pricing)

In the digital world we have taken this to the extreme with freemium and decreased the consumer cost of the initial offering to zero. The penny gap helps you acquire users, but when potential consumers experience your limited offering at no cost the power of free may work against you.

Consumers are educated by the tangible thing they experience as they engage with your service and it gets harder and harder to convince a consumer to cross back over the penny gap with the promise of value added services. Eventually, the free product defines your business and 90% of your consumers decide the free version is good enough without ever experiencing the full product.

In the non-digital world companies have used previum models to acquire customers for a long time. Auto-dealers will let you take a car home for the weekend and gas stations offer a free car wash with the purchase of a full tank of gas. Restaurants give away food at happy hour and at physical retail you can try an item on before purchase. In each example, the perceived value of the service you are buying is higher because you get the full experience before you buy.

I think more digital products/services should be sold with the previum model and hope to discuss it further in the comments.

Relative sizes of policies on privacy

The New York Times did a great job exposing the complexity of the new Facebook privacy policy. In the same week, they also covered the Diaspora project emerging out of NYU. In the confines of the discussion of privacy on Facebook, user control of data as described by The Times and the reported shift in consumer tolerance for “living in public” is a big deal.

Bottom line, the current online privacy environment is messy, lacks transparency and does not offer some consumers enough control. The black and white issue is not public vs. private at the network level but transparency and control at the individual user level.

Facebook is leading the way in rapidly adjusting  their privacy policies in response to new opportunities and as they do this, more opportunities for innovation are created — both leveraging consumer data and helping consumers control its use. Politicians also see opportunity, but the path towards regulation is often littered with abandoned innovative efforts.

Diaspora* is not alone in seeing an opportunity to serve consumers who want more transparency and control around their data. The private sector response to privacy concerns is not just about Facebook, it is much broader. In a recent announcement of the product vision for FireFox 4, Mike Beltzner describes one of the three key features as

“Empowering: putting users in full control of their browser, data, and Web experience.”

For me, this is proof of the efficiency of the private market and I hope Mr. Boucher and the rest of Washington take notice, give a friendly nod to the entrepreneurial community and get out of the way.

Facebook’s privacy policy and default sharing settings have evolved over time and the images below from Matt McKeon do a fantastic job illustrating this…

The "evolution" of Privacy on FaceBook

The comparison of the extended Facebook policy to the length to the US constitution is appropriately snarky. However, the draft of the Boucher bill (PDF) is 5448 words across 27 pages and my guess is the legislation will get longer in the process of becoming a law, not shorter. Worth noting, it is already just 400 words short of the new Facebook policy and shares the distinction of being longer than the US constitution by a good margin.

Both the Boucher bill and these private sector efforts are focused on providing consumers with control and transparency around the use of their data. The difference is the start-ups are innovating at a rapid pace and their goals can be described in 11 words and 1 word respectively.

The Boucher bill will not take effect until one year after it is enacted, the Diaspora* project and FireFox 4 will be available to everyone by the fall. The Boucher bill spends all 5,500 words describing what companies can’t do with consumer data. The entrepreneurs efficiently focus on what consumers want to do and will deliver a viable mechanism for transparency and control of data to the market. This is a case of regulation vs. creation and the winner is clear.

+1 for entrepreneurs.

Everyone else is just lean-washing. In my experience lean-washing and the abuse of the lean start-up approach is out of control. Mis-understood and mis-used, I see the “MVPs” coming out of the lean-washing movement as the Most Visible source of Pollution on the web.

The concept of iteration informed by consumer feedback and usage data is powerful and it has been utilized in product development for a long time. In physical products you are forced into step-changes because of long feedback loops. The web allows us to shorten the product cycles and smooth the curve of product improvement. In this environment we can iterate based on a constant stream of customer actions.

However, innovators from Henry Ford to Steve Jobs have offered their perspective on customer feedback and Seth Godin’s archives include advice on taking customers too literally. He reminds us

Letting your customers set your standards is a dangerous game, because the race to the bottom is pretty easy to win. Setting your own standards–and living up to them–is a better way to profit..

The biggest danger is the customer might actually like it – and then you get New Coke.

You can’t be a perfectionist but the first product should embarrass you only after you learn from customers and release a far better version, not before. If you are embarrassed prior to release, you could have done better with the time and resources available.

Lean-washing is not hard to detect and here are some symptoms you can look out for:

1. Product vision and refinement has been replaced by random test and repeat
2. Iteration does not answer a specific question
3. User feedback is general, conflicting and taken at face value
4. Consumer data is not studied or actionable
5. The team spends more time talking about lean start-up methodology and best practices than it takes to crank out an MVP at other companies

Customers (and the data they generate) are there to help us validate or disprove specific assumptions on the path toward a defined vision. Testing and learning without a specific direction is a waste of time. Keith Nowak recently wrote a very thoughtful post-mortem of Imercive and described the start-up development process as running down a series of dark alleys.

Getting through the dark alleys before it is too late requires concerted dedication to going through the process of attempting, learning, and correcting as quickly as possible.

A start-up is a race against the clock and the value of disciplined execution is supreme.

Based on my own experience building things that people will buy, I do not believe customers should be asked to teach what product development skill, marketing acumen, market insight and entrepreneurial gut already know. At best, customers can react to your product and tell you what they think they want, but it is the entrepreneur’s job to understand what they mean and execute fast enough to build what they need.

In every product development and marketing decision we make, the last question should be what does the consumer think of this and is this confirmed by their behavior data. The problem with lean-washing is you ask the consumer first and in many cases the vision is lost in the echo chamber of consumer queries, buzzwords and un-analyzed data.

I was out west this week for our E-commerce Summit and asked leaders from our portfolio how they manage strategic priorities. It was portfolio power in action and the thoughts below are the result.

When you dive down to the weeds, make sure you know how to get back up

Adjusting the focus from high-level corporate vision down to strategic initiative and on to project definition and then to tactical next action and back up as quickly as possible is something I wish I had been better at as an operator. Founders can get stuck firefighting and micro managing, for months on end because the company is an embodiment of something that has been in their heads for years. Speed and agility are critical to a start-up and the ability to switch altitudes fast can be the difference between failure and success.

We can force altitude switching with 6 questions and when done right, the quality of the decisions will skyrocket.

1. Why are we doing this?

Clarity of purpose and explicit alignment with the vision for the business are critical to these decisions. Try to imagine the initiative is a success in every way and then imagine what that means for the business as a whole. If you are happy with the impact, it is something to say “yes” to.

2. Why haven’t we done it before?

Once you decide to pursue something, asking why it hasn’t been done already is a great way to expose constraints and limitations. Breaking the initiative into components and evaluating the goals of each component will also help you see if the team is working on pieces of the problem already or, equally importantly, has decided not to pursue it. The need to re-prioritize existing efforts in order to push the new initiative forward is important to recognize and communicate.

3. How will we do it?

This is about creative thinking and generating as many ideas as you can. “Brainstorming” is a topic to itself, and everyone has different takes on the most effective ways to manage creative sessions. (IDEO has some great slides on this) In my experience the most important thing is to get away from “No, because…” The goal is to capture the details of what success will look like not evaluate barriers to achieving the success you envision. No judgment, most ideas wins.

4. What is the best way for us to get there?

Once you have a lot of good ideas, you need to organize them through a process that accounts for your current position, team strengths and areas of weakness. This is a curation process. No ego, best idea wins.

5. Have we left anything out?

Repeat the “create” and the “curate” process again (and maybe again).

6. What should we do first?

It is critical to prioritize the projects and next actions if you expect anything to get done. Decide what should be dropped if anything, and decide ownership and accountability for what remains – who is responsible for each project and next action, and who will play supporting roles (if any) on each.

Access to this advice would have helped me say “yes” to the best ideas and eliminate the rest more quickly in my former life. I hope you all find it helpful. Also, thanks to everyone in the portfolio who helped me with this and I look forward to suggestions for improvements and refinement of these six steps in the comments.

***A shout out to Eric Koger at ModCloth for pointing me to The Natural Planning Model as described by David Allen in Getting Things Done for additional reading. If you don’t want to read the whole book, there is a good summary on this MindZone wiki.***

There are so many ways to say it, but none of them are easy.

In the world of agile development and minimum viable product, teams of really smart people can build, test, learn and repeat un-constrained by technical or financial limitations with little to no funding. Powerful learning organizations are being built and the impact on the start-up community has been significant. However, once the corporate mission has been established, the success of any lean start-up depends on the CEO’s ability to say “NO” more than any other factor.

Recently I was working with a company in the First Round portfolio that has fully embraced the lean start-up process. The company has a fantastic team of experienced engineers who embrace the process and actively seek to discover both consumer problems as well as product solutions. They manage their product cycles in hours, not months. They test more hypotheses in shorter amounts of time and with less capital because of their approach, and the result has been extremely high quality product that consumers love. Their development process is a great example of The Lean Start-Up as described by Eric Ries.

Over the past week a competitor identified a new consumer problem and our team immediately saw a way to leverage our technology to create a solution. It was built and tested tested. Consumer response was mixed. After multiple iterations, the team had achieved product/market fit, and the new service showed meaningful user growth—more importantly, it was a major source of new customer acquisition.

But…it was also a major source of difficulty for the company because the CEO did not question the impact of these customers on the rest of the business. The product development team created an elegant solution to a real consumer problem that the other areas of the business depend on ignoring. It is the CEO’s job to protect the team from this type of effort by evaluating the hypotheses being tested and saying, “NO” if the possible answers do not move the business forward in alignment with the mission.

When I was managing product development teams, the challenges of an iterative problem solving process paled in comparison to the effort required to fend off the in-bound product suggestions and feature requests. As these companies grew I had an increasingly difficult role in saying no to the distractions created by new customers, new advisors and new competition. You should always listen to each of these sources, but they are data points to be interpreted. The entrepreneur is the only one who can layer in the complexity of strategic vision, corporate mission and values to the product development process. The more talented your team, the harder this is, but the most successful CEOs are able to filter the signal from the noise and say, “No” when they need to.

The resources required to build and test continue to shrink. While this allows more iterations, it also makes saying “No” harder because it gets easier to test than not to test and the cumulative effect on focus is harder to see. If you have effective strategies for filtering out the noise and maintaining focus in your product development cycles, it would be great to discuss it in the comments.

In the 200 milliseconds it takes you to draw your gun, my algorithmic gun slinger could make 39 stock trades and shoot you in the heart

I believe we are now seeing a change in data processing and decision-making that will be equally significant for investors and entrepreneurs.

Historically, data analysis and computation was done on log files and stored data pools.  In these types of businesses, the data decisioning was done “out of band” — or not in real-time.  However, we’ve now started to see a whole series of applications and businesses where data analysis and decisioning is happening “in band” on streams of data.  In these applications, milliseconds matter.  Massive data analysis and computation are being performed in real-time — and the user’s experience is affected by this analysis.

This is a fundamental change.  Humans do not operate in milliseconds. For the real time web to function, the human decisions have to occur before the clock starts. We need to focus on predictive analysis and algorithms that make rule based decisions for us informed by the data stream.

The Facebook Newsfeed (already has machine intervention) and the Twitter Stream are the most frequently noted “data streams”, but the auto-generated data created by every consumer action, ad impression and click are orders of magnitude larger.  Including the data streams generated by CDNs and ISP’s you can see the exponential nature of the decision requirements in this new streaming data world.

The first vertical to move to real-time is advertising (Spark Cpaital’s Mo Koyfman has a nice summary of the shift in on-line advertising on his blog). It is not surprising that advertising is the first industry to move in this direction. It is most similar to the financial markets and over the past ten years the percentage of equity trades on US exchanges driven by algorithms has grown to over 70%. This was the insight behind Appnexus and Invite Media and may explain why some of the first guys to envision a transparent market for display inventory and real-time bidding came out of a finance school.

In our portfolio I see the power of operating in stream. Ad insertion order compliance can now happen in real-time based on contextual data streams analyzed by Double Verify.  VigLink can identify un-affiliated links across the web and not only append the link with an affiliate code, but choose the profit maximizing link in each instance, in real-time. Knewton’s testing platform is able to provide each student with a customized and personalized test-prep experience, based on their real-time adaptive education platform.  Aggregate Knowledge automatically produces personalized and dynamic creative for advertisements by using real-time algorithms.  In milliseconds Monetate applies a specific set of merchandising rules to individual consumer data streams. The result is a unique shopping experience for each visitor to an e-commerce site.

As we move from a world of data pools to data streams and processing power is distributed to the edge, what other changes will take place now that milliseconds matter? Will infrastructure changes take place as well? Will the real-time web increase the value of a millisecond enough to force companies to co-locate their algorithms at the CDN site or even the end-point device level?

I would love to discuss it in the comments, @phineasb or phin@firstround.com

_____________________________________________________________________________________

I was taught to believe messaging matters and in my conversations with entrepreneurs, I always want to learn about their marketing strategy. A trending topic in my conversations about customer acquisition and loyalty is adding “game mechanics” to a consumer internet service. It reminds me of Josh’s post on viral marketing and the more recent article by Dave McClure encouraging start-ups and Vc’s to focus on marketing and design in consumer internet businesses.

Just like “viral” and “social” before it, GAMES ARE HARD TO BUILD and cannot be bolted on to the marketing strategy.

Well designed game mechanics are addictive

The ability to define value for the consumer with in-game rewards that motivate behavior that reveals consumer utility is the magic of game mechanics. Tony Adams makes my point with his list of business models available to Foursquare. Each of these models is dependent on the user’s willingness to expose their location to the system. If Dennis and Naveen had decided to ask users to click a button every time they went somewhere the utility of Foursquare would have never been discovered. They knew this and they built a game. You start out “playing” foursquare and you end up “using” it (as you might use crack).

The fitness game that I built in 2003 (now licensed to Ubisoft as YourShape) and my work with MTVGames taught me a lot about how to use game mechanics to motivate specific consumer behavior. We offered rewards within the game to support consumer engagement long enough for the player to discover the utility of the product. The combined effect of in-game rewards layered with real-world benefit was an incredibly sticky experience.

When I designed the fitness game, here are the three high-level things I focused on:

1. On-boarding: Give them the perception of managable choice, meaningful rewards and at least one clear/obvious path toward the next discovery item. Make the choices easy and include understandable consequences for every action

2. Capture: once the consumer enters, there have to be lots of reasons for them to keep going. Give them managable choice, meaningful rewards and at least one clear/obvious path toward the next discovery item

3. Deep engagement: Create emerging complexity with layers of simplicity that interact so as one is mastered, another is being discovered. Encourage experimentation by making it obvious that you can find your way back to a stable place (allow them to hit CTRL Z).

When you build these three elements into the design of the game from the beginning, the user floats between a sense of mastery (that could lead to boredom) and a sense of overwhelming complexity (that could lead to frustration). Done right, the optimal gaming experience looks like this:

A well designed game experience looks like this

If you are using game mechanics that help users discover the utility of a service or motivate a significant consumer behavior change let me know in the comments, @phineasb on twitter or by e-mail  Phin@firstround.com. I would love to talk.

Is more dangerous to dance with this guy or to sit out?

In Tim O’Reilly’s latest post, he says, “But perhaps most threatening of all are the natural monopolies created by Web 2.0 network effects.”

He is referencing the social web and its proclivity to spawn systems that are designed to increase in the value offered to each user as more users join the network – as more value is available more users will join…ending, of course, in a monopoly where everyone uses one system in a single, massive network. His fear arises from the prediction that the major players, Facebook, Google, Apple, must continue the push to own customers and the result will be a silo structured web – one where these large systems do not offer interoperability.

I think Tim’s fear is misplaced because of the power of the consumer and the ability for the consumer to drive innovation when they cannot find what they are looking for in the market. The bar is higher when large networks deliver experiences we can love, but when they don’t, innovation will occur and consumers will migrate.

The web 2.0 monopolies have allowed the smaller players to touch the consumer and to own elements of the consumer experience in ways the classic monopolies in the past did not.  It is true that,

“we’ve grown used to a world with one dominant search engine, one dominant online encyclopedia, one dominant online retailer, one dominant auction site, one dominant online classified site, and we’ve been readying ourselves for one dominant social network.” (I would say we are there on the social network dominance as well…)

As an investor and entrepreneur I view these business as infrastructure, not monopolies. There is tremendous opportunity to deliver new services on top of these platforms and to extend the consumer experience by listening and responding as only a start-up can.

The platforms have allowed the small service providers to own the consumer relationship and to deeply integrate into the user experience of the platform itself. We see this in auto updates to the major networks and the emerging dominance of the open API as two way street — both pushing “big data” out and pulling “small data” in. In many ways through this inclusion big businesses are increasingly dependent on the entrepreneurs to deliver the magic that builds customer loyalty, to deliver what consumers love through innovation. Owning the customer is the fastest path to accruing enterprise value and somewhere in the ecosystems of each of these platforms, the seed of the next big business that will dominate the world is growing.

As Chris Brogan said at web 2.0 expo in NYC today, “Gate jumping and making new paths is where the opportunities are.” If you are working on either side of this equation or about to jump a fence and strike out on a new path, let me know how you think about this issue in the comments.

You can't make lemonade with this kind of Lemon

Michael Arrington recently called out Offerpal and the like in his series of Scamville posts the most recent of which suggests a class action lawsuit may be in the works. This series is a great example of journalism and it focused our attention on a doomed market before the failure occurred, however, his focus on the end consumer as the victim only tells half the story.

The inevitable failure of this market and the companies that profit from it should have been obvious from the initial business plans – and not only because consumers would get fed up and stop signing up for offers but because the existence of dishonesty in the market will drive out the legitimate businesses. As an entrepreneur, understanding your ability to differentiate your service and the quality of your good from those of your un-ethical competition could be the difference between success and failure.

Here is why:

The economist George Akerlof wrote a paper in 1970 called “The Market for Lemons: Quality Uncertainty and the Market Mechanism” that describes the fundamental problem with the business model of Offerpal et al. In the paper Akerlof explains the inevitable “no trade” equilibrium in a market where:

a)    Inferior goods exist

b)   Buyers cannot determine the quality of the item prior to purchase

For Zynga and the other social gaming sites, the consumer lead is the good being traded and the value of each lead is dependent on the average revenue it brings to the buyer. They should know better than to head down this slippery slope and they should know the problem is the Lemons. (see Wikipedia for more here)

-Assume a market with 100 total leads where all leads are known to be the same to both the buyer and the seller and all leads generate marginally more than $10 to the buyer. This total market of 100 leads will clear at an average price of about $10 creating a total market of $1,000.

Hate them becuase they ruin markets...

-Now assume that some number of leads (for simplicity let’s say 50) are actually worth $0 in revenue to the buyer and that there is no way to tell the difference between a $0 lead and a $10 lead. If the buyer realizes that there is a 50/50 chance of getting a $10 lead and a $0 lead, the price they are willing to pay drops to the average value of the lead or $5 – 100 leads are still traded, but this shrinks the total market from $1,000 to $500.

-As the average price drops from $10 to $5, sellers with leads that are actually worth $10, with no ability to signal this value to the buyer, are forced to exit the market or sell their leads for less than they are worth.

-Over time, as sellers exit the market, the average price of a lead will continue to fall forcing more and more sellers to pull out. In the end, this process leaves 50 leads all worth $0 and a market in equilibrium with no value and nothing traded.

Akerlof warns us that “The cost of dishonesty, therefore, lies not only in the amount by which the purchaser is cheated; the cost also must include the loss incurred from driving legitimate business out of existence.”

The market for leads created by the OfferPals of the world fits this description exactly and if Zynga and others who monetize through offers (or profit from the advertising Zynga buys) want to stay in business, they should read Akerlof’s article and clean up their markets before they reach the point of “no trade.” It is the right thing to do for the consumer, but it is also the only thing to do for the business.

Equal but opposite

In many ways the power of the web has made physical location irrelevant. We can communicate, shop and consume information from anywhere we can find an Internet connection. While there are clearly links between the online and offline worlds of consumer behavior, the web has mostly existed as a parallel universe that influences, informs and often replaces actions in the physical world.

This online universe has created great efficiencies in consumption processes for information, goods and services and yet it still follows Newton’s third law in that for every action, there is an equal and opposite reaction. By navigating through the web and taking actions on a given page a consumer exposes valuable information that is used to draw them through the purchasing funnel. The simple act of consumption of information by a consumer generates an equal and opposite data consumption activity by advertisers, content publishers and online retailers. The capture of this data has allowed behavioral and contextual targeting to shift from an art practiced by merchandisers and sales people at physical retail locations to a science practiced by statisticians and computer science PhD’s.

The promise of location aware applications and hyper-local online services is the ability to apply contextual and behavior targeting techniques to consumption in the physical world. The challenge lies in the need to observe and record consumer activity in order to inform the targeting strategy and receive credit for transactions motivated by effective strategies. To accomplish this, a service must motivate consumers to reveal their location and thus their intent. Jennifer van Grove has a nice summary of the space on Mashable and makes an endorsement I agree with completely.

As a consumer moves through the traditional online purchasing funnel, the choice to abandon the process serves as a decent proxy for the decision to forego the consumption of the item, or at least to delay the decision to a later date. The relative efficiency of continuing through the online purchasing funnel versus transitioning to the physical retail environment underlies this assumption and allows the traditional online environment to be viewed as a closed system were Newton’s laws can be applied.

In the world of hyper-local services, the friction that used to hold the consumer in the online world is reduced and in the limit it reaches zero. This creates a massive problem for targeted advertising because there is no longer a simple way to capture, measure and record transactions. Consumers do not want to expose their location at all times and the closed system is blown apart. In the current environment of CPC and CPA dominance, ad revenue and lead generation fees are impossible to capture.

Coupons and other redemption schemes are suggested as mechanisms for transaction capture, but this feels like holding together a 747 with duct tape. Given current POS integration, the effort required by the consumer is far more costly than the savings offered by the coupon. Additionally, the experience of receiving spam SMS for 10% off my coffee as I walk down the street with a triple Americano does not seem overly appealing.

Spend some now to make more later

The recent buzz about Google buying Twitter has generated lots of conversation and opinions on what @ev and @biz will and should do. Clearly they know best and will do what is best for the company, their employees and investors, but I would encourage them to discuss buying not selling.  Specifically, I believe they should be paying attention to another conversation streaming across the web right now on the merits and capabilities of URL shortening services.

In 2006 I spoke at an innovation conference for American Express and my talk followed a panel that included Bradley Horowitz, then of Yahoo. He was discussing the keys to a successful Web 2.0 service and he emphasized the need to have “every act of content consumption serve as an equal act of content production.” He pointed to Flickr as an example of this balance in practice and I believe Twitter is close to achieving this web zen. However, while Flickr was able to achieve this content production and consumption balance around images within the service, Twitter is on the way to platform nirvana across the web as a whole. Retweets, #tags, @mentions, @replies and via@ all reference content created within the ecosystem but the tweets that include a link, via a shortened URL, expand the content production and consumption available to Twitter users to include the entire web and suggest the possibility of a new form of indexing and search. As Josh Kopelman pointed out in his recent post, the world may have called the search game over much too soon and while start-ups like OneRiot, Aardvark and Social Mention are working on real-time and social search. I hope Twitter does not participate exclusively in the plans of an incumbent because they have the ability to lead this evolution (as discussed here and here) with a defensible position and favorable network geometry.

The conversation platform is in place and the relationship with the consumer is strengthening by the day. The tools to enable the reach of content production and consumption to include the entire web and the monetization possibilities that lie in the indexing and surfacing of content based on the conversation can be built or acquired. A search interface is already being tested and with search comes sponsored links and monetization. As Om Malik points out here, we are witnessing “the complete disaggregation of the web in parallel with the slow decline of the destination web.” As this trend progresses, Twitter, with the addition of indexing and search tools, is capable of creating new temporal and social metrics that can deliver a re-imagined Pagerank optimized for the disaggregated web. This capability makes them an appealing target for any of the large players in the search space, but given their team and current traction, I would bet on their ability to execute and hope they choose to compete rather than participate in the strategic efforts of others.