Whether you have a single toe dipped in the waters of social media analytics or are fully submerged and drowning, you’ve almost certainly grappled with “engagement.” This post isn’t going to answer the question “Is engagement ROI?” Nor is it going to answer the question, “How do I make the link from engagement to ROI?” (although it’s doable, in my mind, through some causal modeling that gets validated over time…but that’s fancy talk, and I’m not going to get into it now).

This post is just going to share something that I picked up in a discussion with Anna O’Brien of Sprinklr earlier this week. 48 hours after the chat, my mind keeps coming back to it, so it seemed worth publicly noting!

One thing I often struggle with is capturing the full spectrum of “engagements.” A Facebook like takes no more than a click of a button — it’s low effort and, consequently, a lighter engagement than, say, a comment on a post. Viewing a photo is an “engagement,” too, although it’s not a “story-generating” one (for that matter, liking a post is a SINO engagement — Story-generating In Name Only). Start listing the different types of engagements across the many different social platforms, and things get overwhelming in a hurry: likes (Facebook, Instagram, Pinterest), shares (Facebook or YouTube), comments (Facebook, Instagram, or Tumblr), replies (Twitter), mentions (Facebook or Twitter), retweets, reblogs (Tumblr), Favorites (YouTube or Tumblr), user posts (Facebook), link clicks (Facebook, Twitter, Pinterest), photo views (Facebook), video plays (Facebook or YouTube), etc.

Yowza!

Here’s the framework Anna laid out for me. It’s platform agnostic, and I’m sure there’s a corner case or two where some sort of engagement doesn’t cleanly and obviously fit into one of these four buckets, but it’s damn solid:

• Proactive engagements — interactions where a consumer, unprompted, interacts with a brand. Think Twitter mentions, Facebook user posts, and (I think) general brand mentions/conversation (listening platform territory)
  
• Reactive engagements — interactions where a consumer is responding to a brand’s content. Think Twitter replies, retweets, and favorites; Facebook and YouTube likes, comments, and shares; Instagram likes and comments; etc.
• Private engagements — interactions directly between a consumer and the brand. Think Twitter direct messages and Facebook messages (which I don’t think can occur between a Facebook page and a consumer)
• Consumptions — tubercular connotations aside, these are engagements where the consumer, well, consumes brand content. Think Twitter link clicks and Facebook photo views, video plays, and link clicks (and “other post clicks”…whatever the hell THOSE actually are!).

All of these are legitimate engagements. They’re all behavioral proof of at least a momentary “top of mind” status for the brand. But, they’re not all created equally. And, yes, when it comes to reactive engagements, a “like” is not equal to a “comment.” That’s true, but, from an overall framing, they are both reactions to a piece of content, and it’s useful to group them separately from the other types of engagements.

As an analyst, my job is to provide meaningful information that can be effectively consumed and acted upon. A clear, high-level organization for engagements helps with that.

What do you think? Is this a useful way to think about the myriad types of actions and interactions that can occur in social media?

Photo courtesy of David Shankbone

A new report debuted last week on CEO.com from the creators of DOMO, which citied findings about the social participation of Fortune 500 CEO’s. The report showcased the fact that only 7.6% of big company CEO’s are on Facebook; only 1.8% actually use Twitter; and that 70% of global CEO’s have no social media presence at all. To these numbers, I say…FANTASTIC!

Now, don’t get me wrong…I’m a huge proponent of social media and of measuring it methodically…I even wrote a book on this topic. Further, I corroborate the statements that social media has become a transformative force that’s changed the way individuals and businesses communicate. Of course, without a doubt! Yet, when CEO’s are called to task for not individually participating in social channels…well I for one think that they should be spending their time focusing on fiscal responsibility, shareholder value, and customer satisfaction with their products and services. These CEO’s should be lauded for focusing on what matters and for delegating a social presence to others within their organizations who are hired to interact with consumers and to keep touch with the pulse of their marketplace.

The downloadable report is accompanied by a slick video and jazzy infographic…that basically tell us that most CEO’s aren’t Twittering all day (Ummm…that’s good, right?).

While this report certainly doesn’t shed light on what CEO’s actually do spend their days doing, it proves that they aren’t looking to social media as an output channel. And thank goodness for that. While social media is undeniably valuable for communicating to consumers, marketing to them, and interacting in meaningful ways…last time I checked, that’s not the job of an officer in chief. Do they need to be aware of it…? ABSOLUTELY! Do they need to be open to consumer and employee interactions? Why Yes! But do they need to be a first-line responder? I think not. There are lots of ways for executives to stay informed and to communicate. Yet, bolstering a social media presence only to abandon it shortly thereafter, or allow it to die a slow unused death doesn’t help anyone’s credibility.

Maybe I’m alone, but in my opinion the underlying premise of this research missed the mark by a long-shot. Fortune 100 CEO’s shouldn’t be pandering to consumers on social media. Let’s allow the executives in chief the opportunity to focus on business and save the Twittering and Facebooking for the marketers.

Oh, Facebook.

Facebook, Facebook, Facebook.

Ours is a tumultuous relationship of unrequited frustration, is it not? I am an analyst, therefore (apparently), you scorn me. And, by “scorn,” I mean “ignore.”

You never responded to my letter last year. You don’t return my calls. (Well, that’s not entirely true: you put salespeople on my calls whose general response to any question is, “Buy Facebook media.” I get it. That’s their job, but they act like they’ve parachuted straight out of Mad Men and are pushing traditional mass-blast advertising. Ironic, no?)

Facebook, I’ve dug into the data. Your own documentation states:

Posting regularly with engaging content gets more people to talk about your business with their friends. As a result, you end up reaching more people overall.

Yet, the data you provide us tells a very different story. We debunked this particular claim — that getting people to talk about your content leads to greater reach — a month ago.

So, What Can We Debunk This Month?

Lately, I’ve been digging into a more basic mystery: you claim that, the more someone engages with a page’s content, the more likely that person is to get presented with more of that page’s content in the future. That seems pretty reasonable. Of course, you hedge at the same time:

No matter how engaging your Page posts are, not all of your fans will see them in their News Feed. In order to make sure that more of your fans see your posts, you should create a Page Post Ad

Can we quantify that “not all of your fans…” statement? AllFacebook.com did just that when they published a pretty alarming article last week based on Edgerank Checker data. Their study showed that, on average, across 4,000 pages, only 17% of total fans were being reached per individual post by the brand. “Zoiks!” were the cries that echoed through the halls of community managers the world over!

To be fair, not everyone is on Facebook all the time, and, while that number matches data we’re seeing overall, it also leaves out the fact that these don’t appear to be the same 17% day in and day out. When it comes to looking at the 28-Day Total Reach from Page Posts measure you provide, we see numbers that are more in the neighborhood of half of a page’s Lifetime Total Likes (when there is no Facebook media running — it’s much higher than that if that exposure is being purchased from Facebook).

Is 17% really all brands can expect, or is it all they can expect if they’re doing a lousy job posting content?

Are Brands Simply Not Publishing Engaging Content?

We’ve been working pretty hard to learn what kind of content our clients’ fans like, as well as how often and when to post. That put us in a good position to dig into the data to see how we were doing, especially in light of the drop we felt we were seeing in the Reach of posts across a range of our clients’ pages.

We looked at data from a half-dozen pages. These pages were all devoted to major consumer brands, had Lifetime Total Likes ranging from the low 100,000s to multiple millions, and cut across a range of different verticals. Is “6 pages” on the order of the “4,000 pages” from the Allfacebook.com study? Well, no, but we were working with over 600 status updates, and it quickly became apparent that we’d dug in enough to draw some pretty sound conclusions..

For the chart below, we removed the handful of posts that were clearly data anomalies (skewing both wildly high and wildly low) and then, for each post, took the Lifetime Engaged Users for the post (the number of unique people who clicked anywhere in the post within 28 days of it being posted, regardless of whether the click generated a story or not) and divided it by the Total Reach for the post.

It’s not the cleanest of graphs, but it seems pretty clear that, if anything, these pages are, overall, making some headway when it comes to producing more engaging content.

The idea here is that the only people a post has a chance of engaging are people that it reaches. So, we have Total Reach as the denominator. This is similar to the Post Virality calculation that you, Facebook, generate for me…but we’re looking at a lower level of engagement than “generated a story” — just looking to see if fans are interacting with the post in any way. Because, in theory, if they are, then you will be more likely to present them with subsequent posts from the same page.

So, Engagement Isn’t Dropping. Presumably, Reach Isn’t, Either?

In the post engagement chart, there’s nothing all that shocking. What does get alarming, though, is when we look at the average Organic Reach (unique users who saw the post directly as a result of the page posting it — not because a friend talked about it, and not because the brand ran paid media to extend the reach of the post). We divided that organic reach by the Lifetime Total Likes for the page to see what % of the total fans were reached by the post organically.

Again, outliers (high and low) were removed (this included locally-targeted posts, where the reach, obviously, was very low relative to the total likes for the page). Each point on the chart represents all of the status updates on that day from our sample:

Wow. I’m not a data scientist, so the above doesn’t have any true statistical rigor applied to it. Rather, it is an exercise in what a stats professor once preached to me: “Start off by plotting the data! That’s going to tell you a lot!”

It’s pretty conclusive, I think, that a Facebook algorithm change (and related UI changes — but the algorithms drove what content appears anywhere for a user, regardless of the UI) in late September gave brands a temporary ability to reach a higher proportion of their fans. That, undoubtedly, led to any number of community managers thinking they had been listening and learning and publishing more engaging content.

Then, (alas!) November arrived. And, suddenly, Reach plummeted.

WTF?

It’s not that I’m opposed to paying you for reach, Facebook. I’m totally okay with paid media being part of my social media mix. But, if I have to pay you each time I want to reach someone, the numbers start to get hard to justify. If someone likes my page, and then they engage with my content, why don’t they keep getting my content for some period of time?

Here’s what I think happened (and, frankly, I’d respect you a bit more in the morning if you just came out and admitted it):

1. You put some sharp people in a room and told them to come up with a good EdgeRank/GraphRank algorithm
2. While you have “a lot of data,” that algorithm still was largely driven by that team’s instincts around what weighting should be given to different factors
3. There was a fair amount of teeth-gnashing, and the team even tried to do some testing of the algorithm before rolling it out. But, that’s a taller order than it sounds.
4. The algorithm got rolled out.
5. You had no idea what was going to happen. What looked good on paper looked, well, different in practice.
6. For various reasons — none of which have been openly stated — the algorithm has been quietly tweaked a couple of times. In one case, it was related to the Timeline rollout, but, by this time, the algorithm had become the red-headed stepchild of Palo Alto. No one really wants to own it, because no one can really figure out what will make it “work.” After all…the algorithm-heads are all just down the street in Mountain View! (zing!)

How close am I with the above speculation? I don’t have inside knowledge (as noted earlier, you don’t call, you don’t write), but I’m not sure what other explanation makes sense.

Know that you’re killing us — the analysts who are trying to drive learning and optimization! At least set up some sort of open dialogue. We don’t need to see the full formula. But, we need to have useful information about how to do things better. And we need to know when you’re tinkering with the algorithm and what the likely result of that tinkering will be. Otherwise, we can’t trust the data, which means we can’t learn from it. Without data we can use, it’s hard to justify investment and action.

This is the last post in an informal 3-part series covering what Mike Amer, a fellow analyst at Resource Interactive, and I have arrived at when it comes to understanding and using the latest release of Facebook Insights. In this post, I’ll cover what metrics we’re generally gravitating towards as effective ways to measure the performance of a Facebook page.

As many, many, many people pointed out before the latest update to Facebook Insights, Page Likes (or “fan count”), while easy to measure, is not a particularly meaningful metric. As John Lovett would say, it is simply a “counting metric.”

Below are the metrics I’m gravitating to these days as KPIs for a page:

• Reach and Impressions – pick one or the other, but, if one of your goals for Facebook is to gain exposure for your brand, these are much better measures of exposure than Page Likes. If you’re running Facebook media, you may want to use Organic Reach (or Impressions) to measure the exposure you’re generating through non-paid means while the ads or Sponsored Stories are running (this will undercount the overall exposure slightly, as some of your viral reach is from non-paid activity, but there simply is no way to really tease that out)
• Engaged Users – if one of your goals for Facebook is to foster dialogue with users, then engaged users is a good measure, because it is a measure of how many people took any actual action related to your page (regardless of whether it “generated a story”); again, if you’re running paid media, you may want to adjust this metric by subtracting out New Page Likes from Ads.
• Average Post Engagement Rate – this is a second potential KPI for the goal of fostering dialogue with users; you have to get this from the post-level data, but it is simply a matter of dividing the number of engaged users by the total reach of the post and then averaging this for all posts in the reporting period.  This metric does not need to be “adjusted” when paid media is running. It is also a metric for which a page owner really can take direct action to affect by analyzing the virality of the individual posts in the reporting period and developing hypotheses as to what made the posts with the highest/lowest engagement rates different from each other (type of post, time of day, day of week, content, etc.). Those  hypotheses can then be tested with subsequent posts to see if they are validated.
• People Talking About or Stories Generated – if you are aiming for your users to spread the word about your page through their social graph, then these are KPIs to consider. Keep in mind that a person who generates a story by liking your page is producing a much broader reaching “story” than a person who simply comments on a page post. And, as with Engaged Users, subtracting out New Page Likes from Ads when you’re running paid media will give you a better picture of the non-paid results from the page in the same time period (although there will still be some spillover impact that is not currently possible to eliminate).
• Average Post Virality – Facebook reports the “virality” of any single post as the number of people talking about the post divided by the reach of the post. It’s a good metric, if something of a misnomer, because “Virality” is really “potential virality but minimal real virality due to Facebook’s EdgeRank algorithms…unless the post is a Facebook Question.”

It’s pretty easy to engineer much more involved metrics by diving into the organic, viral, and paid breakouts…but then you wind up with metrics that are hard for the typical business user to understand.

That’s our take. What metrics are you finding most useful with the new Facebook Insights? What measures are you least able to get that you wish Facebook would add (for me, it’s the ability to break out “viral” metrics into “triggered by paid media” and “not triggered by paid media”)?

In my last post, I provided an update as to how to interpret the primary measures and dimensions (organic/paid/viral) that are available in the latest iteration of Facebook Insights. While digging into those dimensions, my fellow Resource Interactive analyst, Mike Amer, stumbled across some mild unpleasantries that don’t quite square with how Facebook talks about brand pages in their formal documentation.

On the one hand, Facebook would have us thinking that it’s all about virality. That’s one of the reasons they’ve made “Friends of Fans” such a prominent (if laughable) metric!

To recap, the viral reach of a page or a post is the number of unique people who were exposed to content as a result of another user generating a story (“talking about” the page or post – liking, sharing, commenting, etc.). This differs from organic reach, which is the number of unique people who visited the page or saw an item in their news feed or ticker as a direct result of the page posting the content.

Here are a couple of dirty little clarifications and secrets about virality, though:

• The most common type of viral reach is from someone liking your page – despite Facebook’s insinuations that getting people to like and comment on your page posts will tap into that ginormous “friends of fans” number…those user actions tend to go nowhere. When someone likes your page, though, that generates a story that has a meaningful viral reach (unfortunately, that is a one-time viral exposure — that same user may comment on 10 page posts over the next week and the viral reach generated from those actions will be virtually nil).
• A page’s virality is dramatically impacted by paid media – If a Facebook Ad for the page is run and a user is exposed to the ad, then that exposure counts as 1 person towards the page’s Paid Reach. If the person clicks the Like button, Facebook will record that as a Like Source of “ads” (why they don’t have that data field name capitalized bothers my OCD, FWIW). But, a good chunk of their friends are going to get an item in their ticker that the person liked the page. All of those friends being exposed get counted as viral reach and impressions.
• Oh…yeah…and Facebook Questions – Facebook Questions are the single type of Facebook page post that appear to drive meaningful viral reach (presumably, because the Ask friends action is more valued by Facebook than other actions such as standard likes, comments, and shares). Questions are good for that! Unfortunately, we’ve seen several cases over the last month across different pages where the Organic Reach of Facebook Questions was reported as dramatically lower than the typical reach for a status update on the page. It’s unclear whether those lower numbers reflect reality or whether they are simply a Facebook Insights glitch

All this is to say that viral reach is messy (…and don’t take what Facebook espouses at face value).

In my last post in this unofficial series, I’ll provide a list of the KPIs we’ve been gravitating towards with our clients and why.

When the latest Facebook Insights was released, I quickly put up a post that both tried to explain the new metrics that became available and proposed some probable KPIs.

Well, a few months have passed, Facebook has quietly rolled out some changes to Facebook Insights, and we’ve gotten a chance to actually dive into some of these metrics. This post and the next two are the result of some digging that Mike Amer and I have done on behalf of Resource Interactive and our clients.

Note: This is minimally a post about the web-based Facebook Insights interface. Rather, it is focused on the slightly deeper data that is available behind that interface, which is available by exporting page-level and post-level data or through the Facebook API.

Understanding the Basics – Reach, Talking About, Engaged Users, Consumers

I get a little depressed when I think about the number of times I have read and re-read the same one-line Facebook Insights definitions for various metrics, which have the illusion of being crystal clear on an initial reading, and then get increasingly confusing with each subsequent cycle of trying to actually interpret the data.

I continue to think that the best way to understand the main new metrics is via a Venn diagram. But, the page-level Venn diagram has evolved a bit since my initial post, as Facebook quietly added a page-level Engaged Users metric, which is the union of People Talking About and Consumers. I also think that Facebook changed the definition of Consumers to include clicks that generated a story, but I haven’t tracked down old printouts to fully confirm.

Below is an updated Venn diagram for page-level Facebook metrics.

And, below is an (unchanged) Venn diagram for post-level metrics:

What About Paid/Organic/Viral (especially Viral!)?

At both the page level and the post level, Facebook breaks down a number of metrics by “paid,” “organic,” and “viral” Here’s how I’ve been describing these when it comes to page-level reach:

• Organic – unique people who visited the page or saw an item published by the page in their news feed or ticker
• Viral – unique people who were exposed to content as a result of another user generating a story (“talking about” the page – liking the page, sharing a post, etc.)
• Paid – unique people who saw a Sponsored Story or Ad pointing to the page

A single user can be reached by multiple ways in a given time period (e.g., they saw a post from the page that they’re a fan of in their news feed – organic – and then saw that a friend of theirs responded to a question on the page in their ticker – viral – and then was exposed to a Facebook Ad – paid), so, when it comes to reach, the sum of organic reach plus viral reach plus paid reach is greater than the total reach. Reach measures are always de-duped to be a count of unique users.

When it comes to impressions, though, there is no de-duping, so the sum of the different types of impressions equals the total impressions.

In my next post, I’ll dig into “virality” a little deeper (it turns out to be a bit of a bugaboo metric, but it’s also one that turns out to reveal some sneaky little unpleasantries about Facebook’s EdgeRank algorithm).

This content originally posted on the ClickZ Marketing News & Expert Advice website on July 14, 2011.

In my experience, I’ve found that the vast majority of practitioners measuring social media currently rely on the wrong metrics. Metrics such as fans, followers, +1’s, shares, likes, and dislikes are easily captured and readily delivered by social networks, but they represent merely the low-hanging fruit of social analytics. These are the “counting metrics” of social media because using them typically equates to counting up digital trivia. Effective measurers of social media go beyond counting metrics to create outcome-based metrics and ultimately report on business value metrics to senior stakeholders across the enterprise. In this column, I’ll elaborate on the minutia of counting metrics and where they can add value to your social media operations, as well as how to take the next step of creating outcome and business value metrics to ratchet up your social analytics game to the next level.

Testing the Social Media Waters

The temptation for businesses to experiment with social media is practically irresistible. And in fact, you’d be foolish not to venture into new and emerging channels if your target audience leads you there. But experimentation and ongoing participation in social media must continually prove out the potential for business value. Often times, this potential is demonstrated in metrics that are indicative of volume and activity. Counting metrics do just that because they are measures that tell you how deep the social media pool really is. These counting metrics are typically the freebies offered by social media networks that quantify the basic observational statistics of participation. The stats include: number of users, number of fans, number of followers, number of posts, number of comments per post, number of check-ins, number of ratings, number of reviews…and so on. You quickly see that there’s numbers on top of numbers.

Yet, stopping at this point and using only counting metrics to measure and manage social media is not only just plain lazy, but also detrimental to your business. These metrics are important for gauging the health and activity of your social media operations, but they fail to tell you if you’re achieving your business goals. Counting metrics can offer insights into how many people are swimming and if the water is too cold, or just right. They can also tell you how many people you are reaching with your social media messages and if your content is worthy of passing on to their friends and followers. But, what counting metrics cannot tell you is who the lifeguards should be watching, and where management needs to focus their efforts. Thus, it’s imperative that you go beyond the counting metrics offered by social media platforms to formulate outcome metrics that constitute real measures of success.

Identifying Outcome Metrics for Social Media Measurement

Stepping away from the pool for a moment, I ask you to consider why you’re participating in social media in the first place. Are you working to build awareness for your new products or services? Do you want to initiate a dialogue with your customers to solicit their input on what you could be doing more effectively? Are you building goodwill with consumers by giving back through social media and encouraging philanthropy? Or, can you increase your profits by selling directly through social media platforms? The answers to these questions reveal the business outcomes that you should be working towards when participating in social media. It’s only when you have a clear understanding of what you’re trying to accomplish with your social media efforts that you can develop truly effective measures of success. If you can’t pinpoint why you’re participating in social media today, or if your answers are flimsy and won’t stand up to the scrutiny of executive leadership, I strongly advise that you stop everything and rethink your efforts.

However, if you have a strategic vision of what you’re trying to accomplish with social media, then developing your outcome metrics will become a much easier task. For example, if gaining exposure is the outcome that you are after, then metrics like reach, velocity, and share of voice will be extremely helpful in determining your progress toward this outcome. Similarly, if you’re working to foster a dialogue with customers, focus on metrics like audience engagement, key influencers, and trending topics. Or if cold hard cash is what you’re after, then metrics like social referral source, cost per acquisition, conversion rates, and average order value will illuminate progress toward your stated social media outcomes. Each of these metrics tells you how well you’re doing according to plan and reveals valuable business information.

Demonstrating Social Media Business Value

Now that you’re straight on using counting metrics for sizing up opportunities and outcome metrics for quantifying purpose, the next step is tying all this together to communicate your fabulous progress. To do this, you need to detach yourself from the metrics that you use everyday to manage your social operations and translate these granular metrics into more generalized business language. Think carefully about the things that matter to your organization and the stakeholders that oversee the business and communicate in ways that resonate with them. In most cases, this means aligning your business objectives with corporate goals. Demonstrate which social media channels are contributing to new customer acquisition, which are adding dollars to the corporate coffers, or which are elevating customer satisfaction. This takes some skill and corporate savvy to indoctrinate non-believers into the world of social media metrics, but it’s an entirely worthwhile endeavor that will pay dividends for your organization in the long run.

I’ve found that the most effective way to present a strategic plan and communicate your successes using metrics is to leverage a framework for social media measurement. The one I use includes an inside-out strategy that begins with corporate goals, then aligns business objectives, maps these to measures of success, and then extends out to operational tactics. Using this framework allows me to solicit feedback from stakeholders by actually including them in the planning process of developing social media programs. This encourages participation and gives everyone involved a vested interest in the success of social media endeavors. Ultimately, your social media metrics should build from the basic counting metrics to outcome-based objectives that wholly support your corporate goals. Once you have a solid plan and a strategic roadmap for how you’ll stitch this all together, then you’re ready to dive into the deep end of the social media pool.

I’ve been playing around a bit with scheduling my Tweets and thought that I’d share some of my findings with you. But first, I’ll riff a bit on the fragility of this nascent channel and Twitter’s amazing rise to prominence as the 3rd largest social network in this universe. The figure I’m using for scale is 145 million registered users, which came straight from the Twitter CEO, Evan Williams back in November, 2010. But, it wouldn’t surprise me one bit if another 55 million users joined in the past 5 months. That’s the number that’s being bandied about today.

With ad revenues estimated at $45 million and projections escalating at a 3x clip this year, Twitter is rocketing unequivocally skyward. The only problem with attaining massive growth with user populations rivaling the number of people residing in Brazil, is that Tweets are extremely perishable. If you aren’t watching, listening or searching for a Tweet, it’s highly likely that it will slip right past an entire country of users without ever being noticed. That’s a problem. It’s bad because it seriously erodes any value proposition of time or dollars invested in the channel. Thus, the argument for scheduling Tweets.

Researching Tweets

The best research I’m reading about Twitter is coming from Sysmos, where they continue to crank out valuable insights. Back in September, 2010, they found that the average lifespan of a Tweet is about an hour. Sysomos discovered that 92.4% of Retweets happen within one hour after publication and 96.9% of @replies occur within the first hour. This means if your Tweet isn’t circulated after 60 minutes, it’s likely a goner. Of course there are numerous tools that allow you to automate this process. And that’s what I’ve been exploring. Even the most pedestrian Twitter clients now allow you to schedule your 140 character missives for posting at a later time.

What are the drawbacks of scheduling Tweets?

Scheduling Tweets is a tenuous business. For the most part, you should be Tweeting to deliver good content, but also to initiate a dialogue with your followers. If you’re out on the golf course and your Tweets are generating a firestorm of activity, who’s going to respond? Be cognizant of this fact when scheduling Tweets, because if your Tweet gains velocity and lots of people hear it, you better be at the ready to engage. If not, you’ll quickly lose credence as a friendly human and instead come off looking like a bit of a bot yourself. For this reason alone, if you’re planning to schedule Tweets, do so with considered caution and release news or informative Tweets purely to gain exposure. You don’t want to provoke a dialogue when you’re not ready to interact.

Who offers Tweet scheduling?

This isn’t meant to be a full and comprehensive review of Tweet scheduling tools. These are just a few that I’ve used personally, and my observations of each. I look forward to hearing what you think about Tweet scheduling and which tools if any you use. I’ll commit to updating my list as you offer more…

Tweetdeck – Ahh…my first real Twitter client and a darn good one at that. It’s iconic black interface offers de facto functionality and does so with a fine polish. (I’ve tried to use the “light” interface but just can’t make the switch). Tweetdeck is lightning fast with Tweets posted in real-time. But more to the point, they allow users to schedule Tweets in the future by simply selecting the date and time of your desired launch.

Hootsuite – This little freemium gem is quickly becoming my go-to Twitter client. Despite their recent service outage (which wasn’t really their fault), It’s winning me over with the multi-tabbed interface, multi-user efficiency and slick stream views. Hootsuite allows users to pre-schedule Tweets as well, with the option to select the date and time and receive an email when your 140 character missive flies.

Crowdbooster – I gained access to this product only recently and have been intrigued since my first login. This beauty not only allows you to schedule Tweets, but also recommends the best times to give a shout out. I really like that they deliver an explanation of why specific times are best for Tweeting based on when my followers are active and when I’ve gained the greatest reach. Crowdbooster also has the best charting I’ve seen yet from a Tweet scheduling interface that reveals which Tweets attained reach…and RT’s and @replies as well. I’m having fun with this freemium tool and may even upgrade.

Timely.is – Here’s an interesting new app, that I learned about recently. It uses an algorithm to Tweet when your message is likely to reach the largest audience. Currently, they don’t provide any visibility into how they make this determination, but you can override it by forcing the Tweet to send within the next 30minutes. While they do offer a few cheesy “suggested” tweets, this tool is a product of Flowtown and I’ve been waiting to see what these guys bring out of their private beta. This is definitely one to watch.

Buffer – Buffer offers a slick user interface allowing users to schedule Tweets across a number of recommended times. It has links to the Bit.ly API, but requires premium access to utilize this function. Yet, the free version delivers solid capabilities and collaboration functions for adding additional team members. Perhaps the easiest function is the Chome browser extension that enables you to schedule a Tweet directly from a webpage. This makes scheduling convenient and will be helpful in getting to word out on those juicy bits you discover during non-peak times.

LaterBro – Yo, bro…I haven’t actually tried this one yet, but its interface is simple and clean. I trust it works just fine for planning ahead.

Since drafting this blog post has taken beyond my optimal Tweeting window, I’m signing off now. But before I do, here’s a few more Tweet schedulers that I haven’t tried yet. I’m sure there’s a whole lot more too.

• DynamicTweets
• FutureTweets
• Garious
• SocialOomph
• TwAitter
• Tweet-u-Later
• TwitResponse
• Twuffer

What do you use for scheduling Tweets and what do you like about it? Curious minds want to know.

I’ve noticed something recently that appears to be a burgeoning trend, and I don’t like it. Startups dangling the promise of exclusivity and early admission to their private beta parties in exchange for wielding your influence to “Spread the Word”. Pssst…”The more friends you invite, the sooner you’ll get access!” C’mon! If your product is good, people are going to use it and talk about it. Don’t patronize me with your bad Charlie Sheen references and generic html. This is lazy social media marketing in my opinion. And its a tactic that I won’t pander to.

However, it’s not nearly as bad as hitting submit on a digital form only to realize that the teeny-tiny checkbox in the bottom left hand corner, yeah…the one you didn’t UN-check?? Well, they opted you right into Tweeting to your entire following that you just signed up for the latest whatever on Twitter. These sneaky little broadcast methods are cheap trix and I say you marketers should be ashamed of yourselves.

I’ll keep this rant short, but influence is and will be a contributing factor in the success of many social marketing activities. Yet, as with all things social, leveraging influence must be genuine. Blatant solicitation of influence is only adding to the derision of influencer metrics and the narcissists who work to game the system. The real value of your influencers will pay dividends when they choose to talk about your products and services unprovoked. Doing it otherwise is a surefire way to usurp the power of the influencers you’re trying to enlist.

Did you come to this post via a #measure link on Twitter? If so, then fair warning: your arrival probably has more opportunity to benefit me than it does to benefit you – I’d love to get some tips in the comments section that help me evolve my own process!

Guy Kawasaki spoke at the San Francisco eMetrics this year, and one of his early statements that most people in the room seemed to agree with was, “If the first time you saw or used Twitter, you didn’t think, ‘This is the dumbest thing I’ve ever seen,’ you probably aren’t that bright.”

Anyone who actively uses Twitter has struggled to articulate how and why it brings value to their lives when discussing it with a non-user. Consistently, those of us who are active users wind up falling back on, “You really have to get in and try it out and stick with it for a couple of weeks before it will start making sense.”

This post is my attempt to provide a guide/process specifically for analysts who fall into that “skeptical non-user” camp to try to make that “try it out for a couple of weeks” as smooth and worthwhile as possible.

A second Guy Kawasaki reference: he wrote a post once where he articulated another absolute truism:

There is no right and wrong with Twitter. There’s only what works for you and what doesn’t, so telling people how to use Twitter is as laughable as telling people what kind of websites were acceptable in 1980.

I’m walking a fine line with this post then, am I not? What I’m laying out here has two critical caveats:

• It’s how I use Twitter – what I use it for and the tools I employ to use it effectively
• It’s how I use Twitter as of April 2011 – as the medium continues to evolve and shift, and as I pick up tips and tools from others (I’m hoping to get some such tips from comments to this post), my process evolves

I (like many others) disagree with a lot that Kawasaki has to say about Twitter, but I agree that there is no single “right” way to use it, and this post shouldn’t be taken as such. It’s how I use it — if you find a thought or two that you think would be useful, use it. If you find a thought or two that you think is inane, then don’t (but I’d like a comment on this post so I can evolve my own approach).

Let’s dive in, shall we?

What I Get Out of Twitter

As an analyst, I get a range of benefits from my use of Twitter. Trying to organize them into a list makes it seem like they fall into discrete buckets, when, in reality, they’re a bunch of fuzzy overlapping circles, but here goes, anyway:

• Breaking news in the industry – product launches, acquisitions, hot topics
• Useful thinking from members of the industry – blog posts with tips/tools/explanations/philosophies
• Relationship building – tweets can lead to emails, phone calls, and in-person meetings with both recognized industry leaders as well as analysts grappling with similar issues to me, and two minds are better than one almost all the time! I’ve also had relationships with vendors seeded through Twitter – several that have led to very real and very valuable partnerships
• Technical support…from the community – I regularly tap into the Twitterverse to confirm oddities (the disappearance of Google Analytics Benchmarking, the fact that GA shows Safari as the top mobile browser for Android devices, etc.), which is often a quick way to confirm that I’m not missing something obvious
• Technical support…from vendors – many vendors have a formal customer service presence (username) on Twitter or monitor references to their products and will respond promptly. I’ve gotten quick and helpful responses with very targeted queries to @OmnitureCare, @OmnitureFC, @Twitalyzer, and others

Even without all of these benefits, I would still value Twitter as a useful tool in my analyst workbelt. So, let’s get onto the actual process I use with Twitter.

But First! A Critical Understanding

If you’re new to Twitter, there is one key, key thing you absolutely must understand:

98%* of the content on Twitter that you could see and that might be of interest to you…you will miss…and that’s okay.

It’s easy to get sucked into your Twitter streams and find one useful link or reference after another. You then jump into some other work for a few hours (or days), and a little voice in the back of your head starts saying, “You’re missing valuable content!”

You are…and you aren’t. There is simply too much information out there to consume it all. Don’t try. Think about the information you get out of Twitter in terms of incremental bonus information on top of your existing resources rather than an entire body of information that you should be consuming as much of as possible, and you will be much more able to go to bed at night and rest peacefully. As it happens, my own Twitter usage has been pretty light for the past couple of weeks due to travel. It’s not keeping me up at night!

NOW…to the Brass Tacks of Using Twitter

There are three aspects (plus an optional bonus) to using Twitter:

• Twitter tools (clients)
• Filtering and categorizing content
• Contributing and engaging
• (Optional) Measurement and analysis

Twitter Tools

I use Hootsuite. It’s web-based, has all the functionality I need (the key one being the ability to show multiple “streams” of content at once), and has a mobile app that works fairly well. And, it’s got a nice bookmarklet (“hootlet”) that is a persistent button in my preferred browser, Google Chrome, so I can quickly tweet any link I find.

My setup at work and at home is to use an external monitor with my laptop. I use the monitor as my primary workspace, and my laptop off to the side with a browser maximized with Hootsuite running in it at all times. That way, I engage with the various streams I set up (discussed below), simply by glancing off to the side – where my laptop sits.

There are other clients, for sure. You can look at the tweets of people you follow (or ones you don’t follow) to see what clients they use.

‘nuf said. I’d be surprised if I was still using Hootsuite a year from now, but maybe not terribly surprised.

Filtering and Categorizing Content

One of the great things about the evolution of Twitter is that there is little harm in having a high count of people you are following. You may occasionally scan the timeline that intermingles all of their tweets, but, in practice, that’s going to be an unmanageable sea of information. I have the following “streams” that I set up to drastically filter and organize the content:

• Replies – I have a stream for people who reference me in a tweet; this is one of the more important ones, because anyone who says something to me or about me can reasonably expect a timely response or acknowledgement
• #measure hashtag – this is a search of “#measure,” basically, and it’s the widely adopted convention that web analysts (or, really, digital marketing analysts) use for tweets relevant to the field
• Other searches – during eMetrics, I also followed the #emetrics hashtag; if I were working exclusively with a single web analytics platform, I might follow a search for that tool’s name or the hashtag…but I don’t do that currently (and there are a finite number of streams that I can reasonably follow at once)
• Lists – I have several lists of people I follow; most notably, a “web analytics” list that I add people to when I see them tweet something of interest in #measure, a “Resource Interactive” list that contains current (and former) co-workers of the agency where I work, and even a private “client” list where I add employees of clients with whom I’ve had some interaction

I have a stream for Twitter direct messages…but I seldom look at it. I have DMs set up to send me a text message so that I’ll be more likely to get them even if I am away from my computer.

Contributing and Engaging

Some people use Twitter solely as a one-way communication vehicle – so-called “lurkers.” They use a combination of the techniques above, but they seldom actually tweet anything themselves. This really cuts down on the overall value that can be gained from the medium.

My personal strategy for contributing/engaging goes something like this:

• Using the various streams described above, I retweet information that I genuinely find valuable and try to include a few words as to what struck me about the tweet or link it referenced
• I get emails with interesting content – often people send me a note because they found content that they thought might be of interest to me, and, when I check it out, I feel like it’s actually content that might be of interest to the larger #measure community, so I tweet it (and credit the person who emailed it to me, if they’re on Twitter and I know their username).
• I reply to people when I’ve got something to contribute – either a humorous response that might make them chuckle, a helpful link that I remember/can track down, or actual information that answers a question they’re asking or furthers a conversation
• I have a list of “Measurement and Analytics” bloggers that I’ve built a feed for in Google Reader. This is my own version of something Stéphane Hamel (@immeria) set up years ago, and I used to use Yahoo! Pipes for, but which I recently cut over to Google Reader. I regularly add additional blogs to this feed, and I go beyond the pure “measurement” blogs that I find – pulling in both some data visualization and presentation tips blogs as well. This is an information resource for me in its own right, but, I start my day by scanning the new entries in that feed, and, if I see anything that might be of interest to the #measure community or to a specific person…I tweet it.

None of these are time-consuming activities for me. They’re either 5-10 seconds tacked on to whatever I’m already doing (to share the content), or they’re micro-interruptions throughout the day when I need to glance away from whatever work is currently at hand for a quick mental break.

(Optional) Measurement and Analysis

I wonder if it might be a bit controversial to say that measurement is optional. But, I don’t measure my e-mail use or my phone use, and, in many respects, all Twitter is is another channel along those lines.

Having said that, Twitter is also a key tool I use to build and evolve my personal brand. I use it to promote new blog posts I’ve written (this one, for instance, was auto-tweeted when it was published), as well as, I hope, to elevate awareness of who I am and what types of expertise I haven, and even some degree of my personality.

So, for me, it is important for me to measure whether my contributions and use of the platform are having a positive impact on @tgwilson as a Twitter presence. I use Twitalyzer for this…and you can read about how (in near-excruciating detail) in a post from a few months back.

Some Closing Thoughts

In the end, I try to hook into a few different dimensions of my social graph and engage with each of those dimensions. At times – fairly often, actually – I find content from one dimension of my social graph (say, my non-analyst co-workers) and port it over to share with the #measure community.

Both Twitter and various Twitter tools will continue to evolve. In a medium that is inherently micro and choppy, relatively small nuisances (being limited to 4 streams showing concurrently on my laptop screen, for instance) can really start to grate on my nerves over time. But, time and again, both Twitter and Twitter tool vendors continue to innovate and improve the user experience.

Looking back over the past 3 years, I realize that I’m now consuming and engaging much more, garnering more value, and spending the same or less actual time in the medium than I did when I started out. That’s partly from improvements in the tools, partly from the organic evolution of my personal process, and partly from…practice.

What Do You Think?

Chime in! What else do you do to efficiently leverage Twitter as an analyst? What frustrates you or is holding you back?

*Completely unsubstantiated, mostly defensible estimate.

I’m a little worried about us. At first I was really psyched to see a tweet about my friend and business partner Eric appearing the the WSJ for his not-so-small side project, Twitalyzer. I eagerly clicked through from Tweetdeck to read all about the great strides that Twitalyzer was making in the marketplace only to be massively disappointed by the article, Wannabe Cool Kids Aim to Game the Web’s New Social Scorekeepers. This article is all about gaming the social system to increase influence scores from services like Klout and Twitalyzer and to personally benefit from doing so. Is this what we’re training kids to aspire towards today?

Have you Googled yourself lately…?

Okay, just admit it. At one point of another you’ve typed your own name into to Google just to see what shows up. Or perhaps, if you’re like me you’ve even created a proactive alert that informs you every time you or your business is mentioned in media outlets? It’s not that I’m vain, but I want to know when something or someone publishes about me or about our brand. Isn’t this the cost of putting yourself out there today? Social media has accelerated this exponentially.

I don’t fault people like the ones described in the WSJ article for working to improve their social influence scores as long as they’re genuine. It’s smart to understand how rankings are formulated and how you can improve your scores. That makes the difference between individuals who are building their personal brands with an entrepreneurial drive and those who simply aren’t tuned in enough to know how. Done right, that’s commendable. But understanding the system and rigging it to your favor is potentially where we’re headed in this age of social media. It’s an environment where your potential employer will check your Facebook page prior to extending that job offer; and they definitely will follow your Tweets after that offer is extended; and you can bet on the fact that they’ll be watching your social escapades after you’re hired to ensure that you don’t misconstrue ideas that are yours alone with those of your employer. Or heaven forbid you’re passed over for a consulting job because of a low Twitalyzer score, like the story Shel Israel foretells. But, this is business today, I just wonder if we’re encouraging an unhealthy level of narcissism?

What’s your Social Media Credit Score…?

One of the topics I’ve been researching lately is Social Media Profile Management. This started with the whitepaper that I authored for Unica called, True Profiles: A Contemporary Method for Managing Customer Data (download the paper next week) where I explored what it takes to integrate data streams from disparate sources. Yet, while that’s happening on the business side, consumers are in desperate need of managing their own social profiles. Services like Rapleaf, PeerIndex, Klout and Twitalyzer all reinforce the need to know how you’re portrayed as an individual in social circles and how much personal information about you is floating around out there.

Brian Solis talks about this as well in his compelling Lift presentation where he describes the sociology and psychology behind what we do in social media. He mentions that debt collectors are now visiting individual’s Facebook pages to track them down and sometimes publicly humiliate them into paying their debts. That’s absolutely frightening! But it’s a reality of the world we live in.

Managing your social credit score is important and undoubtedly we’ll see a burgeoning slew of services like Identity Mixer and others that allow you to manage what appears in the databases of companies like Spokeo.com and whitepages.com for all to see. You’re already being indexed, ranked and reported on whether you like it or not. I just can’t help from wondering if the way we (or at least some people) operate with the aid social profile management technologies is disingenuous?

What Should You Recommend To Your Business…?

Those of you who know anything about Analytics Demystified recognize that we’re not ones to take data and simply gaze at it in wonderment. We use data to make recommendations. More importantly, we encourage you to do this as well. So for all the measurers of social media out there, take into deep consideration the value you place on influence. I do believe that it’s a meaningful metric and I am optimistic about < foreshadowing > new developments on the horizon from Social Analytics vendors in this area < /foreshadowing >, yet you have to understand what your metrics are made of and how they’re calculated.

That’s the thing that irked me most about the WSJ article was that it implied in the subtitle that all the vendors out there keep their influence rankings secret. Twitalyzer doesn’t do this, in fact they expose all of the factors that go into their calculated metrics for all to see. While some metrics within the Twitalyzer dashboard do rely on scores from other technologies like PeerIndex and Klout, they’re labeled as such with nothing secret about them. I’m not bringing this up to tout the greatness of Twitalyzer, but more so to call out the fact that transparency in the metrics you use and rely on is critically important.

Hopefully, most of you are migrating away from counting measures like fans and followers that offer little more than a measure from an uncalibrated yardstick and adopting business value metrics that actually mean something to your organization. If you are working toward this end — and if influence is a measure that will factor into your marketing efforts — then take the time to see through inflated scores and popularity hounds that are gaming the system. It’s likely that you don’t want these people doing your bidding anyhow. Instead, use measures of success like Impact to correlate influence to action. When you begin to look at your social marketing efforts in this way, you may just find that those with the most “popular” profiles aren’t actually good for your business.

Update: More Facebook Insights updates rolling out, and, so far, they are buggy: Facebook Quietly Updates Insights to Show Real-Time Data on Page Posts, Bugs Appear.

Dear Facebook,

I really want to stay your friend, you see, but I’m an analyst. I’m someone who daily gets asked by marketers: “How do I know if my Facebook investment is paying off?” They want to be your friend, too, but you sure don’t make it easy.

For starters, I couldn’t figure out where to send this note. And, honestly, I’ve never been able to figure out how to actually contact you. It seems kinda’ silly — you do a fantastic job of helping people interact with each other, and you do a lot to enable brands to engage with consumers. Yet, you don’t make it very easy for us data types to engage with you. It would be one thing if there were a handful of uber-analysts who had an “in” with you, and if those folk were out there chiming in to the myriad aborted threads of frustrated analysts trying to extract meaningful data from your systems, that would be one thing. But there aren’t.

Alas! This note is destined to be a bit of a pissy rant. You can accuse me of using social media in all the wrong ways, of launching a Festivus-style airing of grievances. All I can say is that I’ve been around long enough to know that I should not post in anger, but, rather, should pen this note and then let my heels cool overnight. I did. Over a couple of nights, actually. And it still seemed like the right thing to do.

You see, I’ve been doing this web analytics thing for a while now. I lived through the maturing of the industry from “counting hits” all the way to “measuring conversion, segmenting traffic, and testing and optimization experiences.” As an industry, we’ve learned a lot on that front, but, Facebook, you seem hell-bent on reinventing the wheel, and, so far, your wheel looks like a square drawn by a drunken monkey. I want to be able to cleanly measure who’s interacting with my brand within Facebook and how they are engaging with my content. I don’t want to know names and e-mail addresses, but I sure would like to know how first-timers with my brand engage with me as compared to long-time fans. I want to be able to segment my fans and analyze their behavior by segment. Each successive Facebook Insights rollout gets a lot of buzz, but that buzz tends to turn out to be a swarm of horseflies…circling a fresh cow pie. And that stinks.

I don’t know if you know this about me, Facebook, but I was a technical writer early in my career. That’s made me a few things: 1) a pretty fast typist, 2) a guy who occasionally does RTFM, and 3) someone who expects formal documentation to be pretty pristine and comprehensive. With that in mind, let me show you what happens when I go to Facebook Insights and click the Export button. This is the box that pops up:

Seperated? SepErated?!! Maybe you don’t have copy editors on your dev team, but that’s just embarrassing, and, it turns out, an indication of deeper issues. I killed several hours trying to get Excel 2010 + PowerPivot + OData working to “sync data with Excel,” and I overcame several hurdles before running into a brick wall a hundred feet from the finish line. One of these days, maybe I’ll fully crack the code and can write a nice guide on how to make that work — it would be a handy capability — but your single page of documentation simply blithely points to dead ends! Never mind that Excel 2010 is far from a mass-adopted tool (and let me point out that all major web analytics vendors, including, Google Analytics, which is every bit as free as Facebook, have Excel integrations that are well-documented and work with multiple versions of Excel). I’m an analyst — not a programmer. That means I’m reasonably technically savvy, I can generate, hack up, and even do a little debugging of VBA and Javascript here and there. But, I’m not really equipped to jump into a poorly documented API to start extracting data. I need a little help, and you simply do not provide it.

Let’s say I just export an Excel file manually, though. At least, finally, you provide daily data for a few more metrics so that I can do some roll-ups and trending. Now, mind you, I still can’t get trended data for individual custom tab traffic without jumping through a painful number of scroll-and-click hoops, and that’s a pretty run-of-the-mill need. But I digress. I’ve exported my Excel file and I’m checking out the Key Metrics tab. I’m not going to even bother to quibble with how on earth you could know what my key metrics are, or the fact that you provide 18 “key” metrics. Let’s put that aside and, instead, just take a close look at the first three columns of data and the metric names and descriptions provided:

• Daily Active Users — Daily 1 day, 7 day, and 30 day counts of users who have engaged with your Page, viewed your Page, or consumed content generated by your Page (Unique Users)
• Weekly Active Users — Weekly 1 day, 7 day, and 30 day counts of users who have engaged with your Page, viewed your Page, or consumed content generated by your Page (Unique Users)
• Monthly Active Users — Monthly 1 day, 7 day, and 30 day counts of users who have engaged with your Page, viewed your Page, or consumed content generated by your Page (Unique Users)

Wha…?!!! Keeping in mind that each of these metrics has a single column of data that has a value for the metric for each date…what the HECK is a “Monthly 1 day count of users?” I guess I can make an assumption that this was just some of the sloppiest bit of documentation ever written (maybe it was those drunken monkeys again?), and that Daily Active Users are, for each day, the number of unique users who “engaged with the Page” (more on that in a minute) on that one day; that Weekly Active Users are, for each day, the number of unique users who engaged with the page over the prior 7 days (so it’s a rolling 7-day count); and that Monthly Active Users, for each day, are the number of unique users who engaged with the Page over the prior 30 days (so it’s a rolling 30-day count).

Unfortunately, that’s not what the definitions say. What the definitions say is…gibberish.

But wait! There’s more! Let’s look at “…or consumed content generated by your Page.” That’s, like, three multi-syllable words put back to back, which, seemingly, indicates a coherent command of the language. Alas! It’s actually a pretty vague statement. Again, I have to make an assumption that this means, “any user who generated an impression by having a status update by the page render in their news feed.” If that’s what it means, then why not say so? And, if that’s what it means, should that really count as an “active” user? Sure, “engaging with your Page” (my assumption being that that is a Like of or a Comment on content from my page) is a sign of “Active,” as is visiting the page itself (“viewed your Page”), but an impression? Hardly. Unfortunately, I can’t carve that out and use a metric definition that makes sense for me.

The vagueness of the documentation points to a larger issue of transparency as to the mechanics of how you capture and report data. With Google Analytics, Sitecatalyst, Coremetrics, Webtrends, Twitalyzer, Localytics, Flurry, and other analytic tools, I can roll up my sleeves, dive into the documentation and the interwebtubes, do a little experimentation, and wind up with a fundamental understanding of how bits and bytes are flying around to capture the data. While these sorts of underlying mechanics aren’t something that the  business users I support need to understand, it’s critical for my ability to translate the business questions they ask into the interpretation of the reporting and analysis I do. If I had a nickel for every time I had to say, “Well, it’s pure guesswork as to how Facebook is actually capturing and counting that (video views is a biggie there),” I’d have a nice chunk o’ change that I could transfer to an offshore account and then buy a little piece of Facebook. I don’t have those nickels, though, so I’ll settle for just having you pull back the covers a bit and share your data capture mechanisms and data model.

That actually leads to a real head-scratcher on some data you don’t provide. Call me crazy if you must, but I actually care if people are spreading my content to their social graph. You know how they do that? Of course you do! You were instrumental in bringing the concept of “Share” into the mainstream! Yet, you provide no native reporting on share volume (much less segmentation of who shares, or any indication of the lifecycle of a share)! I can get basic content Share counts for content that I manage through Vitrue, but I’m not running Vitrue on all of the pages I work with.

Don’t even get me started on the random nonsensical holes in your data — “my page plummeted from hundreds of thousands of fans to zero fans for two days and then mysteriously returned to its pre-plunge levels!” — or the firm commitment you’ve made to have data available within 48 hours <choke!> of the activity occurring. 48 hours? It’s a real-time world, baby, and, even if “real-time” doesn’t truly need to mean absolute zero latency, 48 hours is ridiculous.

Now, a workaround that occurred to me back in late 2009 was to simply give up on Facebook when it came to getting the data I wanted and, instead, to just deploy web analytics code on my pages. But, you made it clear from the get-go that you had no interest in me bringing anyone else into this relationship, even if they could totally offer something that you’re not interested in providing. Javascript only runs in the narrowest of circumstances, your image caching stymies many workarounds to that limitation, and, even when I am successful, you manage to make me feel vaguely dirty about my success, like I’m doing something wrong. I’m not. I just want to understand how people are engaging with my pages!

I could go on and on. Unfortunately, I don’t have time to make this note shorter, and I do apologize for that. I’m going to go hang out with some Twitter data for a bit to calm down. Maybe, while I’m out, you could take a good hard look at the way you’ve been treating me? A few months ago, Brian Clifton predicted that, in order to survive, Webtrends needs to get acquired, and he suggested that Facebook would be be a good suitor. When I initially read that, I thought it was a pretty “out there” idea. I don’t think that any more. You need to get help. You need a friend, and having some seasoned web analysts and web analytics developers sharing their thoughts and ideas with you would really help your and my relationship with each other.

Facebook, as a user, I am your friend. And I’m loyal. You give me a lot. It’s as an analyst that I’m being forced to remain your friend, even though I soooo Unlike how you reciprocate.

Best regards,

Gilligan on Data

Hot off the presses! Ray Wang and Jeremiah Owyang of the Altimeter Group just released their newest report: Social CRM: The New Rules of Relationship Management. The opening tenor of the report adeptly characterizes the shift in control from brands to consumers and the frenetic scramble to understand this new paradigm. Yet, the experts at the Altimeter Group see a new shade of CRM technologies aiding in the quest to maintain customer relationships. They write in the report that Social CRM is not a displacement of traditional CRM solutions, but rather a value add function to deepen customer relationships through interaction.

As always the Altimeter Group takes a pragmatic approach by encouraging organizations to start slowly and choose Social CRM entry points based on business value. They list seven categories that tie to real business use cases such as: Social Customer Insights, Social Sales, Social Innovation and Customer Experience to illustrate their points. Yet the real meat of this report exists in the 18 case studies that exemplify tested use cases for Social CRM.

Each use case includes two key measures that enable readers to determine the importance of the activity to their business and the feasibility of putting the use case into action. The first measure is the Market Demand Index, which provides context for the urgency associated with each activity. High Market Demand means that adoption is likely within a short (i.e., 6 month) timeframe. The second measure is Tech Maturity Index that signifies either currently available technologies that are widely used or conceptual products that are still evolving.

This report is chock full of information that you can use to begin understanding your customers and their use of social media in an entirely new way. As one of the influencers listed on this report, I can attest to the fact that it is recommended reading for anyone who’s working in social media today.

Finally, this isn’t the last word on Social CRM. The Altimeter Group encourages readers to add to the conversation and engage in the dialog. To take part: Join your peers in the Google Group for Social CRM Pioneers at:
http://groups.google.com/group/social-crm-pioneers – or – Add the hashtag #scrmusecase to your tweets to join the conversation on Twitter.

Social Marketing Analytics is the process of measuring, analyzing and interpreting the results of interactions between brands and consumers and/or businesses across digital channels in the context of specific goals and objectives.

…At least that’s our working definition. Analytics Demystified and the Altimeter Group are collaborating on a white paper on the topic of Social Media Measurement and we need your help. Our goals for this endeavor are to offer a framework for quantifying the efforts of your social marketing activities and to provide some best practices in measuring social media. Our approach is to bring together social media strategy from the Altimeter Group and analytics discipline from Analytics Demystified to illustrate how organizations can truly justify social media marketing. This paper will be available in March 2010 to all at no cost as we believe that practitioners and organizations shouldn’t have to pay for quality research.

So, now that you know the backstory… While conducting research for this paper, we quickly realized that social media means so many different things to different people that a clear definition was necessary. Under the concept of open research, we’re looking to you to help us crowd source a definition for what we call Social Marketing Analytics. We offer a starting point for the definition here and challenge all you vendors, social media mavens, gurus, users, abusers and everyday practitioners to help us refine the definition.

As you help us shape this definition, please keep in mind the following:

• Social Marketing Analytics is a method for businesses to understand the results of their social marketing efforts – it’s not meant for consumers.

• The definition must include all social channels – those in existence today and ones that will exist in the future.

• We’re taking a big-picture approach by starting with a strategy for social marketing that isn’t dependent on specific channels or technologies.

So here’s our working definition. Please post your comments below or reach out to us via email or Twitter to help define a common starting point for measuring this incredibly important piece of our connected universe.

“Social Marketing Analytics is the process of measuring, analyzing and interpreting the results of interactions between brands and consumers and/or businesses across digital channels in the context of specific goals and objectives.”

Now make it yours… Please comment!