While other private investors have offered to buy Facebook shares for valuations in the range of $4 billion to $6 billion, DST co-founder Yuri Milner expressed confidence in the company’s ability to make money on its Facebook stake. Although Facebook and other U.S.-based social networks have had a hard time making money from their growing number of users, Milner said the social networks he has invested in are making much more money per user than Facebook is now. Milner said Facebook would be able to generate more money from advertising and forms of e-commerce, such as micropayments for virtual gifts given to a person’s friends. “We see monetization patterns that will be very applicable to Facebook going forward,” he said. “For us it was almost a no-brainer.” Milner says he does not need to use only traditional metrics, such as price-to-earnings multiples, in valuing his Internet investments. “That’s not how we look at it,” said Milner. “We see things that others don’t see.”

 This raises some very important questions in my mind:

1. Why did FB get twice the valuation from DST than from any other investors?
2. Why is Linkedin valued at 1 Billion when it has a much better defined business model and a clear value proposition?
3. What were the metrics that Milner used to find value in FB that no one else seems to see?
4. Finally, why was Facebook drawn by DST’s expertise in developing business models that help social networks make money - considering DST is a 4 year old investment firm?

In my humble opinion, rather than trying to hold on to their exaggerated valuation, Zuckerberg and Co might be better served solving the problem of making advertising relevant in social settings. Until they do that, the odds of DST’s investment paying off look pretty bleak.

No matter how you try to spin it, Nielsen and comScore are at a disadvantage.  Both were born in a different media paradigm where sampling was really the only way that you could get good audience numbers.  For one thing the media were largely broadcast which meant that there was no technical way of identifying the exact amount of time an individual watched or listened to a given program or channel.  It was natural, however, that the industry came to accept standardized metrics when they were introduced because measurement both enables the capitalization on successful programming investments AND the ability to carefully plan development spending based on established market trends (or the appearance thereof).

Today however, advertisers and the established measurement firms are trying to apply these older measurement paradigms to a medium that in some ways defies standardized measurement (I have spoken about this at length in my recent lectures and hope to expand upon in the blog in due course).  But more importantly –  why would the advertising industry still rely on audience sampling as the primary means of measurement when most large websites now collect data on EVERY consumer of their content?  More and more online content creators are finding ways to identify patterns in online audience behavior that are based on comprehensive sampling.  This paragraph says it all:

While Nielsen reported 8.9 million visitors to Hulu in March, another measurement firm, comScore, counted 42 million.  Exacerbating the confusion, Nielsen’s numbers for April show Hulu losing audience while still managing to add video views, also know as streams.

At Socialesque, we have developed a straightforward video analytics tool that can not only tell you how many viewers there were, but also how far into the video they watched, how often they clicked on various buttons, and even at what points they clicked on a banner ad that is integrated into the program.

Surely Hulu has at least this sort of numbers (if not, somebody at Hulu should contact us directly, because it would make our day).  But this is perhaps not the point — instead, it might be more important to remember that at any given point in time it matters as much what is accepted as “truth” as what can be measured.

If they are wise, the big online content providers will start to push back against this piece-meal sampling by the established measurement firms.  If we have the capability to do comprehensive internal measurement, which we do, then the focus would better be spent on figuring out how to implement open standards on this measurement so that people can trust the numbers coming out of firms.  But I say sampling be damned, it is a tired remnant of an older media model that is no longer relevant.

The presenters put together a website for the talk that has lots of information about “Web 2.0″ strategies and examples, as well as their actual slides:  What’s Hot on Broadway?

Already the rave reviews are rolling in….

• More than 60 percent of Twitter users stopped using the free social networking site a month after joining, according to data from Nielsen Online, which measures Internet traffic.
• Twitter’s audience retention rate, or the percentage of a given month’s users who come back the following month, is currently about 40 percent.
• Twitter has languished below 30 percent retention for most of the past 12 months.
• A retention rate of 40 percent will limit a site’s growth to a 10 percent reach figure over the longer term and there simply aren’t enough new users to make up for the defecting ones after a certain point.
• Both Facebook and MySpace enjoyed retention rates that were twice as high when they first launched and those rates only rose when they went through their explosive growth phases.
• Each of the popular social networking sites currently show a 70 percent retention rate.

While these might seem compelling on first glance I dont think that Twitter can be evaluated just on the basis of DUV and time on site. In fact, it is unique enough that Twitter must have its own engagement metrics. I look at services such as http://tweetstats.com/trends and number #tags and the frequency of #tags searched is what is more relevant. This is a classic example of using old metrics to measure innovations and then misinterpreting the results because

if something has just been invented then how can the technique / metrics to measure its success already be established!?

Twitter offers a great way to get real time update on what’s on people’s mind. As more people see that the more people will embrace it. A compelling value proposition that solves a problem is what makes a company successful. Twitter has that - MySpace and Facebook dont!

The premise and big promise of online display advertising has been that it could ultimately free advertisers from the “blind spending” of traditional media. Online, the pitch went, and still goes, John Wanamaker’s paradox, the famous zen koan of traditional media — “I know that half my advertising works, but I don’t know which half” — could be answered definitely once and for all, in greater depth than Mr.Wanamaker could ever have imagined. For not only could marketers know “what” worked but when and where it worked (and didn’t), and who it worked for and who not.

Unfortunately in actual practice measurement and accountability often open up more questions than answers for marketers, and create more confusion than clarity. Therein lies the current quandary of online advertising, at least on the brand and display side.

Addressing this quandary is clearly going to be a pressing topic of the next few years, making the heretofore mostly esoteric topic of attribution analysis an increasingly hot-button one.

Most surveys on the topic show that while only a small minority of online marketers use attribution analysis regularly, focus on this class of tools — whether from ad servers, Web site analytics tools or custom dashboards — is increasing.

Both Atlas and Dart have been working for some time on “Engagement Mapping,” for instance. Nielsen has been talking at various conferences about moving attribution measurement from an impression-based to time-based standard, while numerous firms are working at quantifying everything from buzz to influence, and charting relationships between online ad exposure and offline behaviors.

Another tool in this increasingly populated space is Coremetrics’ Impression attribution, a tool for comparatively tracking all impression marketing initiatives including display ads, widgets, micro-sites, syndicated videos across the internet. Though consensus standards about attribution value metrics remains (and is likely to remain for some time) a work in progress, the days when any advertiser, publisher or agency could safely ignore the issue of how to quantify attribution beyond the “last click” are clearly over. Yet at this point most barely know where to start in thinking through the issue.

There is a lot of wasted effort and impressions most in all campaigns. Marketers are becoming aware that for all the data they’ve amassed and all the measurement capability they obviously have they are, they are reallyflying blind once you get outside the ‘last click’.

Online, more than any medium before it, is a multi-tactical environment. There are so many touchpoints and so many potential ways of leveraging each touch point, that for the marketer it’s both exhilarating and terrifying. There are so many potentially viable means at your disposal it’s possible both to achieve unprecedented efficiency, yes, but also to waste incredible resources.

Marketers have heard so many claims and pitches over the years. One of the first things that happens is they bear down hardest on identifying what doesn’t work, on performing radical surgery on the parts of budgets that lead to wasted impressions. Marketers remain very skeptical of the value of display, so the first impulse of many is just to cut it.

That, of course, is not the ultimate goal of attribution analysis. The goal is to optimize media spend by locating, first, what does work, and then how exactly it works in relation to every other channel, and how each piece in the mix works, from awareness building and influence to conversion.

While the first impact of widespread and better campaign optimization is likely to be leaner and meaner budgets for the display side, locating areas where targeted display truly improves overall metrics will ultimately expand budgets. A case in point would be a trend we saw about four years ago among some clients who decided because they were scoring so well in rankings on natural search, well, why not cut paid search. What they found in almost every case was that shutting off paid search hurt their performance so badly they went right back to it, and we never heard more about cutting out paid search again.

Improvements in attribution analysis will be particularly good news for behavioral targeting, especially behaviorally based retargeting. Very clearly the performance of behavioral targeting is increasingly coming into its own. Marketers have till recently seen BT as a great performer but too ‘labor intensive’ in that the scale didn’t justify the work. But in the past year we are also seeing better scaling. We’re seeing, for instance, marketers absolutely restructure their spending mix toward a bigger piece for behavioral display against paid search.

In this day and age of technology, what we seem to forget is that the human decision making process has not changed at all. And so, without a correlation between the intention of the prospect and their actions there can be no engagement and thats what leads to waste. While agree with the general thesis the real question to me is

Are clicks and impressions the right measurement metrics for attribution analysis to begin with?

 My sense is that they may not be, they are certainly not enough because there is no context of the prospects mindset.

• The number of American users frequenting online video destinations has climbed 339% since 2003
• Time spent on video sites has shot up almost 2,000% over the same period
• In the last year, unique viewers of online video grew 10%, the number of streams grew 41%, the streams per user grew 27% and the total minutes engaged with online video grew 71%
• There are 87% more online social media users now than in 2003, with 883% more time devoted to those sites.
• In the last year, time spent on social networking sites has surged 73%
• In February, social network usage exceeded Web-based e-mail usage for the first time.

Charles Buchwalter, SVP, Research and Analytics, Nielsen Online, says “The Internet remains a place of continuing innovation, with users finding new ways to integrate online usage into their daily lives… ”

Since 2003, interests of the average online user have shifted significantly from portal-oriented browsing sites such as Shopping Directories and Guides and Internet Tools/Web Services, to video and social networking sites that have moved to the forefront, becoming the two fastest growing categories in 2009.

With the global recession in full swing, says the report, online display advertising has plateaued at 20% of total online ad spend in the U.S.. Spending on online display advertising by financial services, automobile and retail companies has declined steeply. On the other hand, several key, heavy ad-spending industries such as healthcare, consumer products and telecommunications appear to be moving even more spending online.

The longer-term prospects for global online advertising continue to be brighter. Projecting, Nielsen reported:

• Led by social media, search and video, the Internet’s share of total ad spend will continue its steady upward trend as global economies emerge from the current recession
• Given the increased focus on digital marketing by leading packaged goods companies, the Internet’s share of commerce will continue to rise
• In the age of Twitter, feedback barriers have all but disappeared, creating a near friction-free environment for playing back brand experience, campaign reactions or brand events. Recent public cases show that marketers must be quick to react to these channels of instant feedback
• 30% of U.S. mobile subscribers recalled seeing some form of advertising while using their mobile phones, up from 18% one year prior

To download Nielsen’s full report on the global online landscape found on The Nielsen Wire, please visit here. This post was adapted from this post on MediaPost

Once we have a good model of the problem the customer is trying to solve and/or the behaviors that they are really interested in exploring, we turn to Instrumentation, or the task of identifying the numbers and metrics that we need to collect in order to enable this particular analysis. In some cases the customer already has an existing database, so Instrumentation becomes a processing of adapting their existing database schema to one that will be required for the later analysis and visualization.

In the Analysis stage, we begin to look at the numbers themselves in order to see if our initial assumptions were correct and/or if we’ll need to adjust the instrumentation in order to gain the desired insights.

Finally, we use the analysis in order to both improve our model of player behavior and to look for opportunities to tweak the application in order to enhance overall engagement — a step we call Refining. All four stages are important to extracting actionable insights from the system and putting them to work to make the content more engaging and improve a customer’s bottom-line.

Perhaps the secret weapon in all this, however, is the first step — modeling the problem space. In the AI community, it is well established that “having the right point of view,” “casting the problem in the right form,” and “conceptualizing a problem correctly” makes all the difference in efficient problem solving (See Saul Amarel’s article in IEEE Spectrum, v. 3, April 1966, pp. 112-114 for a good explanation).

For example, the classic “heuristic search” approach to problem solving involves an initial step of representing the problem mathematically or symbolically (a.k.a. ‘modeling’), followed by the cataloging of potential solution steps, followed by a search for the optimal (or sometimes just satisfactory) solution among all the possible options. In fact, Amarel (1966) argues that it is the selection of the model that demands the most creativity in this process of problem solving. This just makes sense; a bad formulation of the problem can lead to an endless (or fruitless) search.

So a key first step, it seems, would be the creation of an effective model. Scholars like Amarel suggest that powerful imagery, abstraction to appropriate spaces, flexible associations, and rich generation of analogies are the key elements of the creative process of Modeling. This type of skill isn’t gained overnight, however. It requires exposure to many different frameworks and models, as well as knowledge of previously successful or failed solutions; in short, it requires expertise with analyzing engagement.

So even if you have a robust system for logging, and a good visualization and querying toolkit, you might find yourself staring blankly at Pie Charts if you don’t begin with a good model. And the surest way to get there, is to talk to the experts at Socialesque.

1) Era of Social Relationships: People connect to others and share
2) Era of Social Functionality: Social networks become like operating system
3) Era of Social Colonization: Every experience can now be social
4) Era of Social Context: Personalized and accurate content
5) Era of Social Commerce: Communities define future products and services

• Don’t Hesitate: These changes are coming at a rapid pace, and we’re in three of these eras by end of year. Brands should prepare by factoring in these eras into their near term plans. Don’t be left behind and let competitors connect with your community before you do.
• Prepare For Transparency:  People will be able to surf the web with their friends, as a result you must have a plan.  Prepare for every webpage and product to be reviewed by your customers and seen by prospects –even if you choose not to participate.  
• Connect with Advocates: Focus on customer advocates, they will sway over prospects, and could defend against detractors. Their opinion is trusted more than yours, and when the power shifts to community, and they start to define what products should be, they become more important than ever.
• Evolve your Enterprise Systems: Your enterprise systems will need to connect to the social web. Social networks and their partners are quickly becoming a source of customer information and lead generation beyond your CRM system.  CMS systems will need to inherit social features –pressure your vendors to offer this, or find a community platform.
• Shatter your Corporate Website: In the most radical future, content will come to consumers –rather than them chasing it– prepare to fragment your corporate website and let it distribute to the social web. Let the most important information go and spread to communities where they exist; fish where the fish are.

The study, for industry body the Interactive Advertising Bureau, found that 31% of social networking website users disliked the barrage of notifications and requests to join various groups or try applications.

Research by the IAB also suggested that despite the rush by brands to tap into the potential of websites such as Facebook and MySpace, the reality is that users are turned off by marketing tactics.

Only 5% of those surveyed said they had signed up to a social networking profile set up or sponsored by a brand.

The report also found that 12% of those surveyed do not like the fact that other people can monitor online activity on websites such as MySpace and Facebook. The survey concluded that this suggested that users were not particularly aware of the privacy functions that can be set to limit what can be seen.

However, the survey, carried out by research firm Opinion Matters for the IAB, found that 28% of social networkers were happy to join a new group if it offered exclusive content. The IAB also found that the UK’s heaviest users of social networking sites were in Wales and the Midlands. Almost 60% of members of social networking websites in these areas log on at least once a day to their profile. This is followed by users in the north-east and north-west, where 52% of users log on at least once daily.

The study found that 58% of all UK internet users have a social networking profile. Of that group, 53% belong to one social networking website, 33% to two and 14% log on to three or more regularly.

In the over-55 age demographic, 13% of internet users have membership of three or more social networking websites.

This post has been adapted from here.