This post is part of the Social ROI Blog Carnival at Think Customers: the 1to1 Media blog. Visit the blog carnival post “Calculating the ROI of Social Media” to check out the full lists of posts from numerous well-known social media thought leaders.

In August, I published a research report entitled, “A Framework for Social Analytics,” written partially in response to The Single Most Terrifying Question In Business Today:

“What is the ROI of Social Media?” 

I’ve heard many people stumble over, punt and otherwise avoid this question for the past several years. But if you happen to ask Gary Vaynerchuk (@garyvee), he’ll shoot back with this little gem: “What’s the ROI of your mother?”

Yes, it’s a cocky, seemingly glib answer. But that doesn’t mean you shouldn’t take it seriously, because it acknowledges that relationships are priceless. And not priceless in the unicorns-and-rainbows sense; priceless in the sense that some things in life–family, friends, education, health–accrue many and complex benefits that we can barely comprehend. This is true of social media, which is also a relationship, albeit one between organizations and their (now empowered) communities.

But we live in the real world–a world in which “many and complex benefits that we can barely comprehend,” will get you kicked out of meetings. The ROI question is unavoidable. I would suggest, however, that we not confuse the tool (media) with the objective (better relationships with our customers and community) or the hoped-for outcome (driving business value). So if the ultimate goal of social media for business is to drive value, how do we know we’re being successful? It’s time to do the math.

The first thing to remember is that there is no magic bullet, no single way to quantify the business value of social media. This is partly because it has broad impact, and partly because different companies value different things. In “A Framework for Social Analytics,” I propose six primary use cases for social media measurement, (each of which has associated KPIs), as follows:

The essence of this approach is that it distills the amorphous term “business value” into more concrete, approachable components.  For example, how does DIRECTV identify and resolve potential service issues before they escalate? How does Best Buy reduce the frequency and length of certain types of customer service calls? How does Amex determine whether sponsoring concerts influences brand reputation and/or purchase intent? All of these examples accrue to top-and bottom-line value, though in different ways.

The good news is that social media can be measured in ways that resonate with the executive suite. The bad news is that these metrics–and the tools with which to measure them–are still very immature. The worse news is that immaturity of tools isn’t even the biggest issue; most organizations don’t yet have the structures, processes, resources and training to measure social media effectively, although those with a cross-functional social media “Center of Excellence” or “Community of Practice” are a step ahead of the game.

The ideal state–and one that companies should start planning for right now–is actually to build social media programs to ensure that they are measurable at the outset. That means a repeatable process informed by a deep understanding of how social media supports business strategy, an understanding of how that success will be evaluated by management, a clear and honest appraisal of the organizational impact and, yes, the tools and data required to make it all work.

The Ticketmaster example from the Facebook Apps for Timeline launch in my previous post provides a good illustration. If, for example, you consider engagement (using the app), consideration/intent (I want to go/RSVP), conversion (Find Tickets/Buy) and sharing (Invite/Recommend) to be key performance indicators, you can build those right into your measurement framework (and your app!) at the outset, creating a self-justifying program.

The goal of social media measurement, ultimately, is to get ahead of the ROI question before it finds you. Even better, architect your social media programs so that their value is so glaringly obvious that the question never gets asked.

On the face of it, it’s a fairly straightforward announcement–it’s no surprise that Timeline would become a major locus for development–but there are a few interesting implications for brands to think about, even at this early stage.

1. Building a richer experience for customers and community

Facebook says they are now approving any app that wants to integrate with Facebook and Timeline. The initial partner set is mostly composed of small companies, but note that Washington Post, USA Today and Ticketmaster are also launch partners. This should prompt brands to think about how and whether they should consider building a Timeline app as part of a holistic engagement strategy.

The point is not to create another push marketing vehicle, or spark another apps frenzy as we saw with smartphones and iPads, but to be brutally honest about how such an app could be of value to the user.  The best apps will make people smarter about what they and their friends are doing, aid in discovery of interests and new friends, and provide entertainment and informational value.

It goes without saying (yes I’m saying it anyway) that new types of interactions carry the potential for unforeseen privacy implications, so companies must be scrupulous to build in appropriate controls at the outset.

2. Engaging based on the interest graph and the social graph

I love my friends, but I don’t always share their interests in fashion, music and travel. But there are plenty of people–friends, or friends of friends–whose interests I share, and I learn about new bands, books, dishes to try, places to visit and tons of other things from them.

Adding apps to Timeline makes it easier for brands to host communities of people with similar interests, leveraging not only the social graph but also the interest graph, which is by definition more targeted. The implication is that an interest graph grants you access to like-minded people, not just friends, and data about who influences whom. This could be the seed of advocacy and influencer programs of the future.

3. Insight into the impact of  social engagement on your business

One of the most intriguing implications of OpenGraph has been the idea that Facebook can now move beyond the ubiquitous (and not very meaningful) “Like” button to a more granular view of attitudes and actions. The impact to brands is that more granular action buttons yield more granular data, so they can start to better understand just how people interact with them in the social sphere. For this reason, one of the most interesting apps I saw at the launch was by Ticketmaster, which lets users share their event-related plans, invitations, recommendations, and even purchase tickets from within the app.

What’s useful for social analytics wonks is that the action buttons correspond cleanly not only to points in the traditional marketing funnel (after all, “I want to go” correlates with consideration/intent), but that people can also invite, recommend or buy tickets (i.e., convert) from there.

This is critically important for businesses who are becoming frustrated with the difficulty of correlating social media activity with direct revenue generation. True, revenue should not be the primary (short-term) objective of social media, and not every brand will lend itself to such a clear and clean use case, but that is part of what companies need to learn if we are to integrate social media successfully into business strategy and measure it effectively.

For that reason, I would recommend that organizations approach Timeline as a way to test and learn about how people behave and interact, whether they’re consumables, luxury, nonprofit or even B2B brands.  This may be frustrating initially, but learning more about how people interact with you across platforms, channels and media is ultimately of tremendous value–even if you end up discovering something very different from what you had originally intended.

And then there’s measurement. What, if anything, is the relationship between social media listening and measurement?

Most of the companies that Altimeter Group speaks and works with are global 1000 businesses which, for the most part, have formalized or advanced social media programs in place. As Jeremiah Owyang stated in his most recent research report on social media proliferation, these companies have an average of 178 social media accounts. They’re no longer dabbling; this is a significant resource investment that must first be rationalized, then justified.

I often find that whenever we start talking about listening, somehow the conversation inevitably turns to measurement: how do we know that what we’re doing is being effective? This question, in my view, is a symptom of where we are in the social media adoption lifecycle. We’re seeing social media programs mature, moving from the earlier “toe in the water” stage to, in the most advanced cases, an integrated component of business strategy.  Some contend that listening is somehow passé, a remnant of an earlier, more naive time in social media, and that we have to get “serious” about social media by starting to measure it.

I disagree with the first statement and agree with the second. Here’s why.

When you factor out the froth and hype of social media, the fact remains that it has dramatically empowered the customer, because she now has a voice and a megaphone.  This is a historic shift. So companies who want to survive this shift must realize that they are now in a much different relationship with their customers and communities.

To better understand the relationship between listening and measurement, we need to look at the ways listening is being used within organizations. Altimeter has popularized the “Learn-Dialog-Support-Advocate-Innovate” model, which defines the major objectives of social media (more detail on this in Charlene Li’s Open Leadership). But with regard to listening specifically, I would propose a slightly different view.

1. Insight and Learning. Insight gleaned from social media
2. Engagement. Engaging with customers, community, detractors, advocates
3. Customer Support. Serving customers via social platforms
4. Decision Support. Input for making business decisions
5. Performance Management. Determining the success of programs and individuals

When viewed in this context, listening and measurement become deeply interrelated; listening becomes a critical data source for the business. In fact, if you took the framework above and substituted “web analytics” or “CRM” or any other enterprise touchpoint for “listening,” you’d quickly find–perhaps with the exception of “engagement”–that it can be used in much the same way.

Today listening is business-critical for the social enterprise.

All of this demonstrates that we still struggle to fit social media into the realities of the business, but that we also struggle to fit business into the realities of social media. The challenge is to accept–and work with–the dynamic tension between these two imperatives.

Lately, we’ve been seeing more interest in how companies are organizing for social media analytics. What are the roles? How many people? From what parts of the organization? With what budgets and accountability? Here are a few examples of what I’m seeing:

The (Big) Data-Aware Organization. I’d be remiss if I didn’t acknowledge what should be at the top of this list; the integrated measurement organization that looks not only at social data but at data in aggregate across the business. This organization–which by the way does not yet actually exist–will collect, analyze and interpret social, sales, operational, supply chain, industry and other enterprise data and use it to sense, respond to and even anticipate changes in the business. This is not to discount the need for nailing an organizational model for social analytics; it’s simply to acknowledge that social is only one dimension of the truly data-aware business.

The Social Media Command Center. This is still a relatively rare breed, but the most well-known examples are Dell’s Social Media Listening Command Center and Gatorade’s (PepsiCo’s) Mission Control.  Both these centers are state-of-the-art, required significant corporate commitment and investment and were conceived for a range of functions, from listening to customer response and support. Gatorade’s Mission Control has the additional, explicit charter to measure the performance of campaigns and social media initiatives. They demonstrate commitment to ongoing dialog with customers and community, as well as to organizational learning, but it’s not yet clear whether this will remain a noble experiment, become a widely adopted model, or morph into something else entirely.

The Center of Excellence. Next we see dedicated, usually cross-functional teams–whether they are part of a community of practice (CoP), center of excellence (COE) or simply an empowered social media team–that act as a clearing house for social media measurement and as a resource to other groups throughout the organization. Often, these groups are highly matrixed and their members have social media responsibility in addition to their “regular” job function. The leader of this team is usually responsible for the following set of functions:

• Drive company listening strategy
• Design workflow process
• Allocate/share/manage resources
• Liaison with stakeholders in other departments/business units
• Collects stakeholder requirements
• Leads tool selection process as needed
• Identifies education needed
• Prioritizes reports and topics
• Manages budget for above

The Cross-Functional Team. Not quite empowered (generally meaning funded) at a comparable level as a CoP or COE, the cross-functional team is usually the first step toward creating a more holistic social media measurement capability. Typically, this team is comprised of marketers, social media specialists, market research and web analytics team members, as well as representatives from other lines of business (sometimes even vendors and agencies). To reach the next level (CoP or COE), this team must effectively construct a business case for further investment that demonstrates the insights and value they’ve been able to deliver, and the benefits of chartering them as an “official” function within the business.

The grassroots measurement evangelist(s). This is typically one or a few folks who see the need for a more holistic approach to social analytics, and are intent on (sometimes even fanatical about) demonstrating the need for this function to management, peers and anyone else who will listen. I know a number of people who fall into this category because they deeply understand the need for a holistic approach to social analytics and are therefore ready and willing to build their business case for more investment so they can operationalize the practice of social media measurement throughout the business.

In the coming months, I’ll be conducting deeper research on this topic, and would welcome your insights. What are you seeing as emerging best practices and evidence of the evolution of social analytics within your business? Please feel free to post your thoughts (and of course any additional examples) in the comments.

Why do I believe we’re in a new phase? Because, even with the frothiness of this past year, I am starting to see more and more heat around measurement, and more companies coming to us with measurement, analytics and ROI at the top of their lists. They’ve invested, and now it’s time to look at the returns. Here, as they say on the BBC, are the main points:

Market View

• Enterprise integration will become a priority for social media measurement: SMMS, web analytics, CRM, BI, ERP, CMS; social data is coming from all sides now.
• There is already increasing demand for/progress toward more actionable, and ultimately predictive, analytics to improve decision making and reduce the resource pressure on individuals and teams. That means real-time alerting, benchmarking and beginning to deeply understand the digital “new normal.”
• Expect more differentiation, especially between “social natives,” “enterprise natives” and “data natives,” as companies begin to clarify exactly how they intend to use social media analytics tools.

Organizational View

• Analytical expertise will become (is becoming) a highly sought-after skill. There’s no lack of data; integration and interpretation is the biggest bottleneck.
• Social media measurement will place an increasingly significant strain on people, resources and organizations.
• Social analytics will force the issue of what organizations value, which social strategies and initiatives are performing, and which are not.

What I’m seeing–even in the past few months since the report was published–is that while the technology continues to evolve, the human impact is actually shaping up to be the biggest disruption–and opportunity–for the measurement of social media.

Why is this? No matter how much data, resource or expertise you have, social media measurement is hard. And when you do it effectively, it shines an equally bright spotlight on successes and on failures.

• For enterprise users accustomed to more mature insight tools like web analytics and market research, social measurement tools are still a work in progress
• For analysts, marketers and social media strategists, sentiment analysis is (and will always remain) flawed, and samples are (and will remain) a moving target.
• For management, there is a steep learning curve as they strive to undertand how to think about the data in the context of other enterprise data–and make decisions based upon it.
• For employees, social data analysis requires education, time, resources, trial and error and deep immersion to be truly useful.
• For everyone, the data required to tell a cohesive story is scattered and requires tremendous resource and silo-bashing to view in context.

Finally, social media measurement requires a certain suspension of disbelief and a willingness to embrace a discipline that, today, is anything but disciplined. That means challenging comfort levels, resources, fear of the unknown, and voting with your feet on what is important to your organization.

2012: The Year of Digging Deep

It’s a thousand times easier to take tried-and true metrics such as impressions, for example, and mutate them to serve social media goals. But that strategy ignores the fact that social media is fundamentally different from traditional media: it needs its own measurement playbook.

In 2012, the companies who succeed in deriving value from social media and, more importantly, from their relationships with their communities will have these characteristics in common:

• They will understand that social media–and measurement–is fundamentally a change management issue.
• They’ll need to approach social media and measurement with an open mind, even as they insist on accountability.
• They’ll take the time to understand the data and begin to establish benchmarks.
• They’ll be willing to dig deep, be realistic about and plan for the organizational impact.
• They’ll draw boundaries around, but learn to accept, the pitfalls and imperfections of social data and incorporate these learnings into their strategies.
• They’ll need to be willing to face–and stand up for–the hard truths about what is and isn’t successful for their business.

As I said in my last post, the social media honeymoon is over. In 2012, we’ll face the challenge–at a corporate level–of making these new two-way relationships work.

This is the first of a two part wrap-up of 2011 and look into 2012. In this post, I’ll lay out the top social analytics trends in 2011, and in the next I’ll make predictions for the new year. I’d love your input, in the comments or elsewhere. – SE

In evolutionary terms, we are still at the very earliest stages of social analytics, but we’re starting to see evidence of development and adaptation as the industry begins to mature. With that, here are the key trends I saw in the market this year.

#1: Everybody Into the Pool!

This was a big year for claim-staking as regards social media measurement. Some of the highlights include:

1. Mergers & Acquisitions: Salesforce acquires Radian6.
2. Partnerships: SAP and NetBase partner to deliver SAP Social Media Analytics by NetBase. Other new relationships: Comscore and Buddy Media; Visible Technologies and Symphony/IRI and Oracle.
3. Product and service extensions by web analytics solutions into social media measurement. Coremetrics/IBM, Adobe/Omniture, Webtrends all announce or step up their social offerings.
4. Product/service extensions by social media service and product companies into analytics: Dachis Group’s Social Business Index, Buddy Media’s C-Rank.

In aggregate, these moves point to an increased desire to measure the business impact of social media, but a lack of consensus on how to approach it as an enterprise-wide discipline. It’s telling that the companies involved come from such different backgrounds. Some have their roots in the web, some in social, some in marketing, some in CRM and some in research. And they’re partnering with and being acquired by enterprise technology companies as each seeks credibility in the other’s domain.

Yet the true implications of these very new relationships won’t be known for some time. In Facebook parlance, “It’s complicated.”

Here’s a look at the different provenances of social media monitoring and measurement solutions, as well as caveats to keep in mind when considering them.

# 2: If Everybody is a Customer…

There is still quite a bit of of “trying-to-be-all-things-to-all-people” syndrome; a marker of young companies in an emerging market. I consistently hear waffling from vendors when it comes to the clarifying question of who’s the customer. Is it marketers? Customer service? Market research? E-Commerce? Strategic planners? Social strategists? The C-suite?

The answer, generally, is yes. Why? Because in this early stage, everyone is watching to see where everyone else places their bets. And thus we have deferred decisions on positioning and a lack of clarity as regards appropriate uses cases, let alone differentiation. This leads to trend #3…

#3: Nobody’s the Customer

What I hear from social analytics customers lately is a growing confusion and sense of frustration about who exactly does what on the vendor side, and who the customers and users are from the business side. The challenge is that businesses generally want to consolidate and optimize their technology mix, but in a fast market with low visibility.

Likewise, there are tough decisions to make for vendors, who need to be more transparent about who the customer is, who the user is, and who they really serve today in reality versus potentially in the future. Those are different conversations, and confusing pragmatism and the need to fulfill immediate needs with vision and hypothetical futures does a disservice to both parties.

The table below illustrates this shift, which brings us to trend #4…

#4: Organizations in Flux

Companies that have moved beyond a focus on tools to mining the potential of social data are discovering very quickly that social analytics disrupts much more than marketing, as groups who never before had a need to collaborate come to the table to discuss the implications of the customer’s voice.

Companies like Dell are making it a corporate imperative to integrate listening deep into the organization, and for a variety of purposes across the enteprise. We’re also seeing more interest in including social data as a point of reference for decision support in areas like market research.

Companies must develop repeatable processes and frameworks for how they will use social data, as the same tweet, post or comment can have relevance far beyond marketing to product development, strategic planning, risk management, brand management, customer service and beyond.

Right now, that is an extremely disruptive prospect–as organizational siloes, lack of data integration and perhaps most importantly, internal control and cultural barriers–prevent data access across many organizations.

#5: Early Indications of Social Data Integration

Just as enterprise customers start trying to simplify their tool sets, the uses of social data continue to expand. The answer, ultimately, is integration, but it still remains a speck on the horizon.

We talked social media measurement, how companies are exploring social media, who’s doing interesting things, what influence means (and doesn’t mean) and where it’s all (maybe) going.

Robert uses Flipzu on his iPhone for podcasting, which was great except for the fact that it tends to stop broadcasting when he gets a call, which, being Scoble, is pretty frequent. So the interview is in four parts. Here they are:

• Part 1
• Part 2
• Part 3
• Part 4

I’d love to continue the conversation here or here or even here. Thoughts? Questions? Disagreements? Send them my way!

“You know that kid Mikey? From the Life cereal commercial? I heard he ate Pop Rocks and drank Coke at the same time, and his head exploded.“ ”No way!” shouted another kid. “Way!” retorted another. And so on.

In those days, there was no Internet except the Internet of conversations shared on playgrounds, at slumber parties, in offices, classrooms, bars, busses and anywhere else people tended to congregate. Eventually, it moved to email, then to the Internet, where Snopes.com has been settling countless bar bets since 1995.

But with the social web, urban legends have the ability to morph instantly into memes, and flit around the globe in seconds. When you consider that social web traffic is highly “news” driven and that re-tweets can actually create a news cycle where one previously didn’t exist, you have the potential for flash-points of misinformation, which lead to confirmation bias, which essentially means that people have a tendency to believe things they’ve already heard or think to be true. The more you hear it, the more “true” it becomes.

(If you doubt this, ask Gene Simmons, Johnny Depp, George Clooney, Miley Cyrus or any of the other celebrities whose deaths are routinely–and prematurely–announced on social networks. Conversely, witness the extreme care taken by news outlets to seek official confirmation of the death of Steve Jobs, which had previously and erroneously circulated many times before.)

But misinformation isn’t confined to childish rumors and celebrity death-hoaxes; consider its power to topple political candidates, financial markets–even businesses and governments, when used with specific, malicious intent.

Craig Silverman of the Columbia Journalism Review recently posted an excellent article on the subject of misinformation in which he interviewed Professor Filippo Menczer of Indiana University on the work he is doing trying to understand the propagation of information, true and false, on the Internet.

While the article focuses primarily on the impact to consumers and the media industry, it’s a critical read for business as we start to envision how to realize the promise of predictive analytics. Because confirmation bias is so strong on the web and has such potentially enormous downstream consequences, Silverman and Menczer argue, “early detection is a must-have for any misinformation detection system.”

Think of it as an “information supply chain;” fallacies early in the chain can have disastrous consequences later on as they propagate and influence the decision-making process. This is even more critical as businesses become flatter, more networked, more real-time and more collaborative.

Given the complexities of human communication and the algorithmic acceleration of information on the web, Menczer’s research should be hotly anticipated by anyone planning to incorporate social data into decision support. To realize the dream of predictive analytics, we must have unshakable trust; if not in our data, then at least in our ability to interpret it.

We compared notes on topics such as how adoption, engagement and measurement differ from Japan to the US, and the impact of cultural differences on social media adoption. The conversation got me thinking about how social media will develop globally, and how much about our online experience we take for granted.

For example, we constantly complain (at least I do) that machine-based sentiment analysis is notoriously poor; most solutions can promise at best a 65% – 70% accuracy rate, while the more sophisticated text analytics solutions can get to perhaps 80% or slightly higher.

But Japan has multiple alphabets: Kanji, Hiragana and Katakana. And while we have 26 letters in our alphabet (not to mention punctuation and emoticons), Kanji extends to the thousands (with significant debate as to the exact number, if in fact there is one). To add to the complexity, Kanji are made up of multiple parts that each have meaning, so the technical challenges of sentiment analysis are intense. I heard estimates of accuracy in the range of 15% – 30% for sentiment analysis in Japanese, although there is a fair amount of development going on to improve those numbers. Given the importance of listening to any social strategy, this is a significant challenge.

Beyond listening and measurement, I found that everyone I met was curious about how social media can best be adapted to Japanese business and culture. They claim to be about two years behind us in terms of adoption, and wanted to know what convinced US executives to take the first steps to prove its business value. From the consumer point of view, I heard from many people that while many are generally not comfortable voicing opinions publicly, they are (again, generally) more likely to do so in smaller, more secure groups.

Japan’s superiority in mobile is a tremendous asset, and it’s not simply a matter of technology. The country is small, and populations dense, so living spaces tend to be small as well. People spend a lot of time outside and on the move, so mobile is the default communication platform.

But while it’s important to understand cultural differences and factor them into strategy, it’s dangerous to overemphasize them, as it has the potential to create false barriers. I returned from Japan more convinced than ever that there is no “silver bullet” for any of this; that social media will continue to wind its way through business and culture in an almost infinite number of ways, and that our task is to stay fresh and open to its lessons and opportunities.

That day has come for Facebook.

Facebook wants everything and everyone; specifically, every detail about us: our social graph, our preferences, our interests, history, tastes and activities.

This is the impetus of today’s announcements, Timeline and the opening of a more intelligent Open Graph to the development community. The essence of these changes is that, with Timeline, the Facebook profile becomes a kind of life story, a scrapbook on steroids, complete with posts, photos, videos, music played, books and newspapers read.

Timeline turns everyone into a curator, a media property and, at its most basic level, an activity stream. 

As part of this set of announcements, Facebook is also making its Open Graph available to all Facebook developers, which will enable developers to integrate their apps deeply into the Facebook experience.

With these moves, Facebook has taken a huge leap: of ambition–of faith and certainly of hubris–toward becoming the de facto information source for how we collectively and individually share, communicate and influence each other.  ”Pretty soon,” Robert Scoble commented, “Facebook is going to know everything about everyone.”

With Timeline, Facebook users will have to assimilate quite a bit of change: not only to the user interface but to the type and mode of sharing. Rather than the standard status update or check-in, Timeline facilitates “passive sharing,” in which the act of reading an article, listening to a piece of music or sharing a movie review becomes a status update in and of itself. Will everyone like it? Certainly not at first. (As a matter of fact, I was somewhat surprised to see that I was automatically checked in to F8 today, a fact that I learned when a friend “Liked” my check-in, updating my notification stream. Was I nonplussed? Yes, a little.)

While consumers resist or accommodate themselves to these changes, brands will face a data bonanza the likes of which they have never seen. In addition to the changes announced today, Facebook users will be able to move beyond the “Like” button to indicate whether they have “Read” a book or article,”Listened” to a song or radio show, ”Watched” a show or movie or even “Bought” a sweater or “Cooked” a recipe. And with Open Graph, there is no limit to the verbs that can be used to indicate preference and behavior.

Of course, with great power comes great responsibility, not only on the level of privacy and data gathering but also of data analysis. While “Like” could mean any number of things (for example, I like Tom Waits, The True Colors Fund and my friend Kristen’s pear bread recipe, though all in different ways), app developers and by extension marketers will be able to track preference and activity at a new level of granularity.  As a result, the onus will be on the brand to interpret the meaning of these behaviors and appropriately personalize content so that consumers feel they are being heard, rather than just crudely targeted.

Here’s a hypothetical example: I happen to be a big fan of the Food Network series “Chopped,” in which chefs compete to cook the best meal possible out of a range of often bizarre ingredients. Imagine that I “Watch” the show, and, intrigued, decide to “Buy” a cookbook recently published by one of the judges.  A week later, I “Cook” one of the recipes.

In the past, I may have “Liked” the show, but in most circumstances that wouldn’t tell Food Network anything about whether I acted on my affection by buying a related cookbook or by actually making one of the recipes. They know I like them, but they don’t know whether I “like them like them,” as we used to say in middle school.

Now I have given Food Network three specific data points, as opposed to the rather blunt instrument of “Like.” I’ve told them I’m a fan, I’m a consumer, a cook and perhaps even an advocate. And, because it’s Facebook, they also know my age, that I’m married and that I like Tom Waits and pear bread. Imagine the possibilities.

This is of course just an amuse-bouche for what is to come, both with sharing and with social data, so I’ll start to break it down in future posts. In the meantime, I welcome your thoughts about Timeline, Open Graph and the rapidly-shifting challenges and opportunities of social analytics.

• For a deep dive into the implications of today’s news, check out Brian Solis’ post, entitled “The New Facebook: A Timeline for Personal Discovery and Storytelling.”
• For a look at the future of sharing, please read Charlene Li’s post, “Facebook Timeline Reveals the Future of Sharing.”