The Sisqokid

Somebody that I used to know

I am SO late to this party (47 MILLION views as of this posting), but this has got to be the best music video (music + visual) that I’ve seen in ages. 

Discovered via @mauerbach804

Gotye - Somebody That I Used To Know

And if you want to really have your mind blown, watch this remake (32 MILLION views so far) by Walk Off The Earth.

Productize your data

I have the opportunity to see many companies doing fascinating things with data at my day job. One truism that needs to be recognized is that generating interesting data is not nearly enough, but rather entrepreneurs need to be laser focused on productizing data. I’ve seen many entrepreneurs miss this point, often times creating an interesting mousetrap for generating, collecting or aggregating data, but stopping there instead of going the distance by productizing the data. 

So what does it mean to productize data?

Most generally, there are two types of data-related products:

1. Data-driven product. A standalone product that is informed and enhanced by data (ex. Amazon’s recommendation engine)
2. Data product. The product is data itself (ex. AP newsfeed)

Let’s look into each of these types of products more closely.

Data-driven products

The concept of productizing data is quite intuitive with respect to data-driven products. In these cases a feedback loop is created where some standalone product improves by collecting and effectively utilizing data. Zynga exemplifies the power of data-driven productization by capturing, storing and analyzing almost every interaction users have with their games, and then uses this data to improve game play and optimize monetization. As described in a recent WSJ piece: 

To understand why Zynga Inc. is among the tech industry’s hottest companies, consider how it gets people to buy a bunch of things that don’t exist. Last year, Zynga product managers for a videogame called “FishVille” discovered something intriguing while sifting data that Zynga collects when people play its online games. Players bought a translucent anglerfish at six times the rate of other sea creatures, using an imaginary currency people get by playing the game. The “FishVille” managers had artists whip up a set of similar imaginary sea creatures with translucent fins and other distinctive features, says Roger Dickey, a former Zynga general manager who left the San Francisco company recently. This time, they charged real money for the virtual fish, and players snapped them up at $3 to $4 each, says Mr. Dickey.

’We’re an analytics company masquerading as a games company,’ said Ken Rudin, a Zynga vice president in charge of its data-analysis team.

Companies that are able to leverage data to improve products benefit from what we at IA describe as Data Economies of Scale. You can think of Data Economies of Scale as a virtuous spiral in which strong products attract users who generate invaluable data through their usage. Insight gleaned from user generated data is then fed back into product development which helps evolve and improve the product, thus enabling it to attract more users who contribute more data which then feeds into further product improvements, more users and more data, etc. etc. etc.

Data Economies of Scale is an extremely powerful competitive barrier enabling a product to move further and further ahead of new competitive entrants who have yet to achieve enough scale to benefit from a data-driven product feedback loop.   

Data products

In contrast to data-driven products, it is somewhat less intuitive to understand the concept of productizing data for a product that is essentially, in and of itself, pure data.

Before diving into productization strategies, let’s spend a moment first clarifying the concept of a company whose product is essentially data. Using an example to demonstrate the concept, let’s look at the New York Stock Exchange (NYSE). As the exchange through which stock transactions occur, the NYSE generates an extremely valuable proprietary data asset - market tick data. NYSE then sells this market tick data to banks, hedge funds and media outlets that use it in a variety of productive and profitable ways. Thought of in this light, NYSE is most fundamentally a mousetrap for generating and capturing data and its core salable product is data itself.  

Contrary to what you might think at first blush, selling raw data is rarely a ‘product’. The problem with raw data is that it is difficult for end users to consume and it requires users to start from scratch trying to figure out what to do with it. (That said, sometimes users - particularly those who are highly technical and quantitative - want the exploratory flexibility that comes with having the unfettered raw data; but this is the exception, not the rule.) 

Instead, data almost always require some sort of ‘packaging’ to become a product. Though I am sure there are more, here are three types of effective packaging for productizing data:

1. Structuring data for a particular use cases and ease of consumption, often in the form of an API. A great example of an API product company is The Echo Nest whose entire product suite is a set of highly structured developer APIs that provide powerful access to music data. Another good example of a structured data product is Yipit Data from our portfolio company Yipit. Yipit Data aggregates and structures all relevant daily deal data in an easily understandable and consumable manner specifically tailored for their primary target market of financial analysts.
2. Visualizing data in the form of a highly interactive, dynamic and insightful dashboard. Great analytic dashboards allow users to both explore data and be pushed actionable insight. Our portfolio company Next Big Sound does a killer job of taking raw social, event and transactional music data and turning it into easily understandable graphs, charts and visualizations enabling sophisticated exploration of the data and highlighting important actionable insight.
3. Creating an experience around data. Sometimes packaging is as straightforward as creating a nice interface and simple interaction tools. For example, Twitter’s product is most fundamentally data (tweets) wrapped in a clean interactive interface that allows users to create, consume and engage with the data. (Interestingly, Twitter initially allowed third parties to create competitive packaging but later strongly discouraged and eventually prevented third parties from creating their own experiences. This strategic move is very much in line with the spirit of the framework I have laid out here – Twitter recognized that a fundamental part of the Twitter ‘product’ is the packaged experience around the data, and as such, they felt it imperative not to outsource this critical element of productization.)

I had a chance to meet with an impressive entrepreneur last week who exemplifies the theme of productizing data. The entrepreneur’s fundamental asset is TV related social engagement data, but his products include 1) multiple well defined structured APIs, 2) an interactive analytics dashboard, and 3) stand-alone applications build on top of the data. It was awesome to see an entrepreneur with such strong product sensibility exemplifying the powerful offerings that emerge when you productize your data. 

Dominating Freemium - Spotify case study

Like my good friend elsiguy, I’ve fallen in love with Spotify. Over the weekend I decided to take my relationship with it to the next level by upgrading to the premium service for $10/month. For the uninitiated, Spotify’s basic service is free, on-demand desktop music streaming supported by advertising. There are two premium offerings:

1. $5/month removes all ads
2. $10/month removes all ads, offers mobile access to the entire music library, and allows users to sync songs and playlists to devices for offline listening

Spotify is not the first music service to offer a vast music library, on-demand streaming and mobile access. So why has Spotify emerged as the leader of the pack in on-demand streaming when others (Rhapsody, Napster, etc.) have failed to gain serious market traction.

I believe the answer is rooted in Spotify’s implementation of the freemium business model.

Let’s step back for a moment. A freemium model is one in which some basic product or service is given away for free and premium features are offered at a price. 

Freemium models need to satisfy two conditions to be viable:

1. the basic free service needs to be strong enough to attract lots of users
2. the premium offering needs to be compelling enough to incentivize some meaningful subsection of users to pay

Spotify nails freemium. Let’s take a closer look at some of the specific factors that make it so compelling.

Free basic service

Spotify’s free service is an awesome standalone offering. Some factors that contribute to its awesomeness: 

• Library.  Spotify’s music library is vast with licensing deals with all major record labels. You won’t find everything (Metallica, The Beatles, Pink Floyd, Led Zeppelin - absent do to asinine and shortsighted thinking), but you’ll find almost everything. 

• On-demand. On-demand means the user has the flexibility to listen to any song at any time and in any order (and until recently, only music owned/locally stored afforded users this flexibility). Historically, free online music offerings have been constrained by the economics of music licensing and have been unable to combine ‘free’ with ‘on-demand’  (on-demand royalty payments are much higher than those for ‘radio’/non-on-demand streaming). And while the the jury is still out with respect to the economic viability of the Spotify model, the fact that there is a framework that allows free on-demand music streaming is HUGE. Together with mobile access and offline syncing, on-demand streaming is fundamental to move to a more attractive cloud-based streaming universe where there is no need to ever own and locally store music.

• Social. A fundamental part of Spotify’s experience is the innate social integration. For most people the Facebok integration is not only a wonderful tool for music discovery, but also serves to create massive stickiness on the platform. The fact that I can share and benefit from shared playlists creates a strong incentive to be on the same platform as friends. In effect, Spotify is leveraging Facebook to bootstrap the creation of it’s own ‘music social graph’ and will benefit immensely from powerful network effects that emerge from owning it. (Note: Spotify is not the first to integrate social with music listening, but they do it relatively well and make it core to the fabric of the experience. I have a full blog post brewing on this topic…stay tuned.)

• Ad supported. The fact that the free service is ad supported is important, but not all that interesting in and of itself. However, what is important and interesting is Spotify’s specific and unique implementation of ads within the service. First, Spotify does a great job walking the tight rope of making ads intrusive and annoying enough to incentivize users to seriously consider upgrading, but not so much so that it completely interferes with usage of the basic offering. Spotify uses some interesting tricks to walk this line, the most interesting to me is that they constantly rotate the ad unit interface - sometimes vertical, sometimes horizontal, sometimes audio, and sometimes there are no ads at all. Some find this annoying. I find that it actually makes the ads more effective (i.e. I notice them a lot more) and I’m satisfied knowing the ad will shortly move. Second, the quality of Spotify’s audio ad unit is quite impressive. Despite the fact that audio ads cut into the listening experience, Spotify seems to intelligently serve units that are contextually relevant to the user and their listening tastes - making the ads more bearable and less obnoxious. It also serves these ads in a relatively well integrated manner so the audio experience is not jarring to the ear.   

Premium offering

The premium offering is sufficiently differentiated from the free service and offers clear and demonstrable value - a compelling mouse trap to attract users to upgrade and pay. 

• Mobile. A massive amount of music is consumed outside the home and on the go, and as noted above, offering mobile access is a key condition to evolve away from owned/locally stored music to cloud streaming. Having on-demand access to the entire Spotify music library at my fingertips at all times makes my local music collection seem puny and pathetic. 

• Offline. The world is moving towards ubiquitous connectivity, but until we get there offline sync is necessary to replace the owned music paradigm. With offline sync, I have unfettered offline access to all songs, albums and playlists that I have selected to sync locally to my devices. In fact, I’m benefiting from offline sync at this very moment listening to Bon Iver 30,000 feet above the ground while writing this blog post. 

• Ad free. Nuff said.

———-

Spotify is not the only music streaming service making waves right now - Rdio has a very compelling differentiated service as well (similar to Spotify in many ways and even better in some). The emerging model for these new and hopefully viable music services is to create a killer freemium offering that attracts masses of free users while offering enough premium value to incentivize users to upgrade to the paid subscription. As a die-hard music fan, I’m rooting hard for these guys to make it work.  

Fundraising ‡ business development

I recently had a fundraising discussion with the head of BD at company looking to raise capital. He is a good guy and the company is doing cool stuff. But a word to the wise - fundraising is not business development and your BD lead should not run your fundraising process. Fundraising is fundamentally the responsibility of the CEO and cannot be delegated to other members of the team.

I get the rationale for having the head of BD run the fundraising process; business development professionals are deal people - they are articulate, know how to sell and are skilled negotiators. Their job is to ‘do the deal.’

And this is where some companies get tripped up. Despite the fact that it looks like a duck, walks luck a duck and talks like a duck, your discussion with a VC is *not* a ‘deal’ in the traditional BD sense. It is not a temporal alignment of strategic interests. 

Your engagement with a VC is a marriage. It is a fundamental, nearly irrevocable, company-life-long partnership. 

From the investor’s perspective, the single most important determinant of whether or not to enter into the partnership is the people. Don’t get me wrong, everyone on the team is important, but there is no avoiding the reality that the CEO is the one driving the ship - the overall strategy, the product vision, the key sales initiatives, the hiring of lieutenants, and so much more. The CEO is the final decision maker and ultimately bears responsibility for the success of failure of the company. The buck stops at the CEO.

When the CEO is not leading the fundraising discussion, rightly or wrongly, that in and of itself sends a strong negative signal - is he incapable of describing the vision? Does he have a problem inspiring others to believe in the opportunity? Is he unable to sell? Will he be steam-rolled in a negotiation? 

Conversely, having the CEO run the process puts the CEO’s capacities as a leader, visionary and salesperson on display to inspire investor confidence. Furthermore, it enables the irreplaceable opportunity for the CEO to develop a relationship the investor. Remember, a venture investment is more akin to a marriage than a ‘deal’, and it only works if there is a strong relationship built upon mutual trust and respect. The CEO is the primary point of contact between the company and the investor, and it is the CEO who needs to play point building that relationship on behalf of the company.  

To be clear - the CEO is not the only important team member and is often times not even the smartest or most capable (the best CEOs hire people who are smarter and more capable than themselves!). All the team members are important. But for the reasons described above, fundraising is fundamentally a CEO-level responsibility and should not be delegated. 

Consumerization of Enterprise

Amongst the many buzzy internet themes popular these days, one that particularly intrigues me is the theme of consumerization of enterprise. Broadly speaking consumerization of enterprise refers to the evolution of enterprise software. As anyone who has worked in a big corporation can attest, enterprise software is generally stogy, complex, bland and antiquated. In stark contrast, successful modern consumer applications are clean, simple, engaging and fresh.

Over the past year, my colleagues at IA Ventures and I have developed a simple framework for thinking about this theme. To us, consumerization of enterprise means three things:

1. UI/UX. Incorporating design and interaction best practices refined over the past decade in the consumer web for clean, simple and engaging user experience and user interface. 
2. Social. Building social into the foundational fabric of the application either by enabling social interaction and connectivity through the application and/or leveraging graph data (social, interest, professional or other) to optimize the experience and performance of the software.
3. Mobile. Building applications with a mobile-centric design philosophy. In other words, building applications from the ground up optimized for usage on mobile phones and tablet devices. 

We have made two investments at IA specifically around this theme - Banksimple and Coursekit. Both companies exist to disrupt massive incumbents (Banksimple :: online banking portals from traditional brick and mortar banks / Coursekit :: Blackboard learning management system) and both specifically replace antiquated enterprise offerings with applications designed from the ground up with UI/UX, Social and Mobile best practices incorporated. 

The exciting thing is that the world of enterprise software is ginormous and industries across the board are ripe for disruption. The application of consumer web best practices will be one of the defining drivers of innovation and evolution in the world of enterprise software and we are just now beginning to see the promise of consumerization of enterprise become reality. 

Business of Big Data slides_v2

My colleague Brad Gillespie and I led another Business of Big Data discussion at General Assembly last night. Our revised slide deck below.

The Business of Big Data (IA Ventures) View more presentations from Ben Siscovick.