As the web has evolved, and we have evolved with it, we have started to see that “one size fits all” doesn’t apply to graphing our personal connections online, and more particularly it does not apply when hosting different types of user behaviors.  This is why we manage and engage with our business connections on Linkedin and not typically on Facebook, to give one example.   Considering that social media is still a very young medium, it is safe to expect that more platforms will emerge hosting different connection types and user behaviors.

In the past several years, the Internet has turned the news and greater media industry on its head – everything from content creation to distribution has completely changed.  This has created problems for both consumers and publishers.  For consumers, discovering and accessing the news that is most valuable to us has become overwhelming.  For publishers, developing a strong community and converting that community into hard dollars has become incredibly difficult.   At Pinyadda, we have designed our platform specifically focusing on the evolved news and media landscape, hosting what we call the “news graph“.

The individual parts of the news graph have existed for a long time (post about this coming soon).  With Pinyadda, we are focused on connecting these critical parts and providing more value to the different entities within the news ecosystem.  We have studied how our behavior as news consumers has changed and have provided simple tools for enabling each individual user to get the information they need from the sites they like, the topics they follow and from interesting people.  For publishers, we have focused on providing an open distribution platform aimed at extending publisher’s reach and exposure through automated distribution and organization.  This framework will provide the foundation to enable publishers to capture more critical data and eventually monetize the distribution of their content.

While we have experienced tremendous growth in the short time our platform has been open, we are still young and focused on making improvement to best serve our community of users and publishers.  Our intention for this post is to start of on-going discourse regarding the evolution of the news graph, which we invite you all to contribute to.  We believe the news graph is a critical component to ensuring that consumers have an effective way to access the best information available for their unique interests and needs, as well as enabling publishers to capitalize on providing quality content.

Coming soon: The Working Parts of the News Graph

Turns out this stuff is useful for people who are pirate-neutral, maybe even those with an aversion to pirates (I don’t understand you). I could sum it up  but you’re much better off checking out the presentation or watching a video of Dave giving the basic talk. But the gist is pretty simple: measure the stuff that matters, don’t measure the stuff that doesn’t. This might seem like an easy thing to do, but in reality it can be pretty easy to confuse getting a lot numbers with getting the right numbers.

We’ve measured a whole bunch of stuff over the course of our time at Pinyadda, and we’re still zeroing in on exactly what we need and what the best ways are to quantify those metrics. What works for our business almost certainly won’t work for yours or anyone else’s, and it takes time to figure out the magic concoction that can quickly and easily provide accurate insight into what’s really going on.

In our current phase, we’re focusing on two key aspects of the AARRR model – Activation and Retention. At the moment, these are the two most important things that we need to figure out: how and when are people getting to the ‘aha’ moment with Pinyadda, and what keeps them coming back? By drilling down and taking a really close look at these specific aspects of our product over the last month, we’ve been able to do a couple of key things that have kept us focused on making the right product iterations instead of spreading feature lists all over the whiteboards and then spinning around in tight circles:

1) We asked some really specific but straightforward questions about how people were using our product. These are things like “how many people does someone need to follow before they start Pinning articles consistently,” and “of the people who login most, do they follow more people, sites, or topics?” We’ve had this data all along but we’d always cast it in terms of feature use or product analysis. Spinning the questions this way, to make them centered on the people instead of the product, makes the information more useful, easier to understand and much more actionable.

2) We invested a small but invaluable amount of time in building some reporting features for ourselves. Raw data is wonderful and we have lots of it, but if it takes an hour harvest and organize it’s not really useful to us on the daily. Taking hours away from pure product development to work on this is a little hard to swallow, but sacrificing a few Friday nights to do it might save weeks of wasted effort later if you can avoid building a single doomed feature. Plus, it’s a good environment to mess around with some new toys (I used a lot of CSS3, which I don’t use much in production, and also got comfortable with a great visualization library called Flot). Here’s a sneak peak:

3) We set some tangible goals for user activity and retention. We’ve always done goal setting but narrowing the focus has helped everyone on the team look at their area of focus from a common perspective. When you’re as small as we are it can be hard not to get lost in your own little corner. Keeping our eyes on a small and focused goal set makes it easier to stay on the same page. The results have been great and it’s been awesome to feel the team catch its collective stride.

McClure’s language may be a bit blue, but the message should be taken to heart by small teams everywhere. It’s helped us not because we follow it to a T or take every word as truth, but because it just makes sense. Every business will have to find its own way, and what makes sense to measure will vary widely. But by thinking critically about metrics before spewing numbers all over the place, coloring the things you measure in terms of people and not faceless features, and keeping team members aligned toward small but focused tasks, you can channel the spirit of pirates and strive forward in the search for internet booty.

John Perry Barlow, co-founder of the Electronic Frontier Foundation, once stated that, “Relying on the government to protect your privacy is like asking a peeping tom to install your window blinds.” After Facebook CEO Mark Zuckerberg’s recent comments about the death of privacy, one has to wonder whether Barlow’s statement may be more relevant to the times if phrased: “Relying on the government to protect your privacy is like asking Facebook to respect the private information of its users.”

While there are plenty of smart people arguing the pros and cons of the effects of Facebook’s new privacy changes and Google Buzz’s auto-following model on users’ private information online, I am more interested in the business implications of these developments.  The industry powers like Facebook and Google seem to be in a mad dash to make more information public; however, I wonder if this push for extended network connectivity is smart for all networks.

A recent study conducted by Nielsen found that Twitter’s “heavy users” in the UK consist of 7% of the user population and make up 79% of the total amount of time spent on the site.  Facebook on the other hand sees in the UK 52% of its population as “heavy users” making up 98% of the time spent on site.  While this distinction between the distributions of user activity on the two sites could be attributed to a number of things (e.g. type of content hosted, product differences, etc.), I personally believe that the network designs with regards to privacy and the nature of users information have the largest effect on the user activity distributions.

When analyzing the value of social networks like Facebook and Twitter, much of the excitement comes from data that shows digital word-of-mouth as the most trusted marketing form.  Taking this into consideration, you would think that Facebook and Twitter would want to be very deliberate in making adjustments to privacy settings and product design that effects how information is shared throughout their networks, with a focus on optimizing the distribution of user activity in a way that would best support their business models.

The two networks are typically used for very different things – I think of Facebook as my “social life identity” and Twitter as my “broadcast identity“.  Inevitably, Twitter is a much more public platform than Facebook which would suggest the distribution of user activity will always be a bit more skewed. However, I think it is safe to assume those over at Twitter are probably thinking of ways to engage a larger portion of their user base.  From Facebook’s standpoint, I find the sneaky move to make user’s information more public by default is certainly questionable in terms of user trust, but also strange from a business standpoint.  Facebook’s biggest strength is how deeply people engage with on another on the site, by making such a change I feel they could be jeopardizing this.

I am interested to hear what others thing about this – do you think it is smart for Facebook, Twitter and Google Buzz all to be pushing consumers to share more information publicly?  Do you think it is smart for one and not the others?  Let me know in the comments.

I am also interested in hearing from any of you statistical nerds about what you think ideal user activity distributions would look like for the different networks.  I’ll write a follow up post with my opinions on this if there is any activity around the idea.

I think the API model is a great example for the newspaper industry. It allows them to stop worrying so much about their distribution problem and get back to doing what they do best – producing content. Let the rest of the developer community worry about finding ways to get the news to readers. But I’m not so sure the Times thinks about their API this way, and the announcement that they’ll be erecting a pay wall in the coming year seems to reinforce that doubt.

It seems like the Times sees this API as a way to establish itself as the definitive archive of all events past – the lens through which history is viewed and dissected. As such, it will be incredibly valuable, allowing historians and documentarians to uncover meta-trends and write fascinating feature pieces about them (who they’ll get to publish those pieces, well…). But when I think API, thanks to Twitter, I think “now.” I think about developers building great experiences around the wealth of content that belongs to the Times, about innovative new ways to organize and discover its content, about new solutions to the old media problem. The Times’ management, I fear, does not share my sentiments.

If the pay wall goes up – and I’m not entirely convinced it actually will – the API either becomes far less useful or far more useful, depending on the restrictions applied. I find it hard to believe that it will exist in its current form, with open access to all articles one hour after publication. I could be wrong. I hope I am.

The point of all this rambling, you ask? The point is that the Times seems like a two-headed monster to me. Half the time, they do everything right – the first to truly incorporate lots of multimedia, the first to successfully incorporate the blog form, the first to understand the web as an opportunity and not a threat. The the other half of the time, they seem trapped in the same delusional nostalgia that’s handicapping the rest of the industry – the display ad run-around, the formatting stalemate, and now the paywall. I suspect that there’s considerable internal tension between these two forces as well. And I’m not sure who will win.

Maybe the pay wall will work for the Times. But its life span, as far as I see, is inherently limited. No matter what we believe in, no matter how long it takes, the price of content will eventually reach zero. There’s just no way the generation that’s coming up behind us will swallow a monthly fee for access to a publication that holds no emotional or collective social value for them.

I give the Times credit for trying something – anything – to stop the revenue drain that’s been their standard operating procedure for the last few years. But they should keep looking for a long-term solution – one that’s closer to the API than the pay wall.