Marshall Sponder’s Social Media Analytics – “Numbers Lie! Engaged Communities Drive Value.” ~Robert Lavigne

Chapter Five – Friends, Fans, and Followers

Chapter 5 of Social Media Analytics deals with one of my favourite Social Media topics “What is the Value of a Fan?”

What is the value of a “Facebook fan”? Is it $0.00 per Augie Ray of Forrester Research, $136.38 per Syncapse, $3.60 per Vitrue, or $259.82 per McDonald’s.

What is the value of a Twitter follower, a Google Plus follower, a WordPress subscriber, a YouTube subscriber, a Facebook Friend, or a Real Friend?

These are questions that every marketing focussed entity must ask and answer in justifying the ROI model of their Social Media Campaign.

Calculating the ROI of a Social Media Campaign is very much an actionable equation given specific parameters that are valued, formulated, encapsulated, calculated, and evaluated.

However, the real answer is hidden well behind the numbers that get generated from the multitude of platform providers, who will gladly outsource a solution to “solve” your dilemma.

You see, Numbers LIE!  Yes you read that right, NUMBERS LIE!

We are living in a world where you can acquire, yes acquire, the numbers to match any and all targets your “follower-based” marketing campaign wishes to generate.

Don’t believe me, Google “Buy Followers”, or better yet Let Me Google That For You.

The honest truth is that the numbers are insignificant unless you put them into the context of the specific outcomes you wish to measure and evaluate.

You can come up with every possible equation to answer the question of  what is the value of a click, visitor, fan, follower, subscriber, or friend.

To determine the value of a “fan” is a fallacy, that in my opinion throws to the wind the very principle behind social media.

We are unique human beings with our own behaviour patterns, our own circle of influence, our own power of amplification, and above all else, our own model of determining whether we value what should be the most important factor to your campaign.


So the real question should be “what is the power of engagement, and how can your organization generate a positive return of value that can be measured on the bottom line of your spreadsheet?”

Marshall Sponder formulates that the value of a fan is equated using five factors:

  • Spending
  • Loyalty
  • Recommendations
  • Earned Media Value
  • Cost Offset of Fan Acquisition

Marshall goes on to elaborate on the meaning of each of these measures. However, the key theme that seems to exist across all of them is participation (i.e. engagement).  Once a fan is acquired, their level of participation both as an individual and as an influencer of their tribe dictates the true outcome of the value equation.

How a corporation “collaborates with its clients” (or fans) truly dictates the earned value of that particular follower. This by nature is an extension of the engagement process.  Without first engaging with your potential client, you will fail at collaborating with them.

In the world of sales and marketing, engagement represents influence and collaboration represents a call to action. To simply expect a call to action purely based on an individual liking your page, is the biggest misconception that plagues most ventures in social media.

 A year ago (almost to the date), I was the guest of The Customer Experience Show. To this date, that episode still ranks as their top downloaded episode.

It was during this interview that I publicly stated that “Media fundamentally is all about Exposure, Influence and a Call to Action.” I went on to further state that “Social Media scales the level of Call to Action  to the Three Degrees of Connectivity.

Where analytics play a large part in calculating the “value of a fan” is entirely based on the consistency of the measurement across campaigns. Only by comparing actions and reactions of those campaigns against previous “consistent” measurement, can we truly get value out of systems that provide a formula and model of calculating earned value.

This model of “consistent” measurement versus accurate representation has been around for decades.

In radio, television, print and other traditional media, we have been paying samplers to equate for us the “reach” of our campaigns in those mediums. The sad truth is that those numbers are based on a similar flawed model. You simply cannot determine the true reach and level of engagement by sampling 0.00222222222 of the population.

Similarly, you cannot expect measurements to be treated with respect if the algorithms are modified from campaign to campaign.

Recently Klout made some drastic changes to their algorithms. Were the old algorithms flawed? Are the new algorithms better? Who knows? What people will always remember is that Klout failed to provide a consistent measurement of “online influence”. As such, it will take numerous new campaigns using the new algorithm to determine the “new value” of a Klout number across campaigns.

Marshall Sponder took a page out of Scott Stratten’s mantra, when he outlines the fundamental model to drive fan engagement. I am speaking of course of “awesomeness”. It is the awesome that gets talked about and shared.

The major advantage of Social Media over Traditional Media is the transparency of Peer Pressure. As your friends see what you like, they are more likely to like it as well. Remember “Social Media (2000^2000) Provides an Exponential Reach that Traditional Media (2^2) cannot.

So to “fully leverage peer pressure” you first need to acquire the fans and then provide them something that they will want to engage in. Upon engagement, you can then focus on collaborating with them towards a call to action.

Marshall provides some insight as to how best engage your fans on various platforms based on a study by ExactTarget and CoTweet. To best pass on this knowledge, I have opted to quote directly from page 89 of Social Media Analytics.

“Twitter followers are most interested in getting information about a brand or future updates on a brand product. Twitter followers are also more likely to purchase or recommend a brand than e-mail subscribers or Facebook fans. Meanwhile, Facebook fans are motivated more strongly by discounts and promotions than by any other factor. Given these findings, it is tempting to think that form follows function, that the medium profoundly affects the message. As users interact with information differently on each platform, their interests, behavior, and motivations vary.”

I will leave you with two more quotes from Marshall Sponder that illustrates where Analytics play a large role in determining “fan value”. The key as he highlights is business integration, as numbers by themselves mean nothing as NUMBERS LIE!

When working from the business goal out, a convention is needed that shows which data are needed to track ROI information.

The caveat, or gotcha, is that the metric(s) may still not be truly useful or accurate, because consensus is lacking from standards bodies such as IAB, WAA, and CIPR.

Click to Read my Review of

Chapter Four – Online Social Intelligence

7 thoughts on “Marshall Sponder’s Social Media Analytics – “Numbers Lie! Engaged Communities Drive Value.” ~Robert Lavigne

  1. It is not sampling 0.00222222222 of the population which is the issue. The required sample size to estimate a parameter is a function of the desired precision of the estimate (bound on the associated error) as well as the estimated variance of the population. In the variance term, there is a term (N-n)/N where N is the population and n is the sample size. For large populations, that terms is essentially 1. As a such, as a rule of thumb, once populations are greater than 50,000, there is no longer a relationship between sample size and popultion.

    Where the issue lies is when we are trying to sample “rare” events. Traditional sample survey designs capture well the “mainstream”. Programs, magazines, etc with reaches of say 10% or more are captured well (all within the context of what you are capturing – exposure? engagement?). When we are sampling to estimate media with a very low penetration rate, say a reach of 0.1%, traditional statistics start to fall apart. Reach essentially follows a binomial distribution, you are either exposed (or actively viewed/listened depending on what is being measured and the measurement device) or you are not. A simple outcome of 0 or 1. Modern market research approximates the binomial distribution with the normal distribution. This is fine since the Central Limit Theorem applies even with sample sizes less than 30. Where this falls apart is when the probability of reach lies close to 0 or 1. The Normal approximation is no longer appropriate and we start to see poor estimates of error upon the actual reach estimate.

    The rule of thumb is generally that np > 5 AND n(1-p) > 5. As long as those criteria as met, you should be okay. This of course, is not withstanding some of the further work on interval estimation for binomial proportions. Brown, Cai and DasGupta (2001) wrote a very interesting paper on the subject.

    • First off, thanks for commenting Derrick. Your background in statistics is obviously well known by me and I appreciate your input on this tricky subject.

      My primary question regarding your comment is in regards to the 0.1%. Are you implying that Social Media has yet to break the 0.1% barrier. Because if that is the statement, clearly I have a concern with the accuracy of that statement. We are now living in an age where “Netflix Users Stream 3,000 Lifetimes Worth of Video in 3 Months” per a recent Mashable article. That is “2 Billion Streaming Hours” that are competing with traditional broadcast television.

      In addition the massive rise in tablets and mobile has made it that more content is consumed on those mediums then most devices out there. More and more people are listening to podcasts during their commutes. More and more people are opting for video games as a form of entertainment then movies. As Gary Vaynerchuk would say even when people are watching television, there is a high likelyhood that they are multi-tasking on a secondary device and are not actually engaging in the traditional medium even though the device is on.

      So it goes back to my main question, how truly accurate is the traditional sample when a growing (if not massive) percentage of the audience is not even tuned in. While we can use those statistics to model those that are tuned in, the reality is that to scale that out to the entire population is no longer an accurate assessment of national viewership.

      As in the past, I love these dialogues between us on the subject and hope to engage more with you on this topic.

      “5 years free of traditional media” said in best AA voice

      • As a further comment. As the recent acquisition of Maple Leaf Entertainment by both Bell and Rogers proves, it is clear to me that the only place where accuracy remains in traditional media is on live broadcasts. There is way to many competing elements at play on taped broadcasts to validate old viewing mindsets. But once again that is my option 😉

        As a additional comment. As recent as today, reports have been made that “One in five U.S. residents say they have either cut the Cable cord or are thinking about doing it.” If only a fraction of that report is accurate, we can assess that at least 10-20% of the population that was once scaled out by the .002 is no longer applicable or valid.

      • My statement with regards to 0.1% was a more general one and not specific to social media or the like. More so as a product of the increasing fragmentation in media as well as the variety in delivery platforms. Many want to measure each fragment by platform which brings problems with measurement.

        Now of course, you bring another good point with multi-tasking. This is a subject of great debate. What is more important, exposure or actual engagement? If you are casually exposed often enough to the same message is it the same as being engaged to it once? How do we move to measuring engagement? This is no different than the debate of program ratings versus commercial ratings.

        It is a challenging world, and by far, the best approach is to leverage many sources of data and as many tools are you can to recognize the strength of your brand. No one source is the golden solution, but rather, a properly executed multiple approach stream.

        • Thanks for clarifying that Derrick. I think you hit the nail on the head when you talked about the increased fragmentation in media (let alone the exponential nature of multi-tasking). For me at the end of the day, we are seeing more and more of a shift towards valuing engagement vs. exposure. You do need to start with exposure to initiate an engaging environment. However, the real value at the end of the day is the call to action and that comes after a solid engagement. What I am finding is that most metrics out there still focus on exposure and do nothing to deal with the real return on exposure which is the engagement factor.

          Finally I think you are spot on when you indicate the growing need for a “properly executed multiple approach stream”. And I think that is where the main point of my commentary is focused. To many traditional campaigns and “follower-based” campaigns tend to focus just on that, the numbers, the reach, the exposure. Those numbers are no longer as valuable in determining the real impact of a campaign in this social economy.

          Thanks for engaging 😉


  2. Pingback: How the Brantford Library understands “The Social Media Business Equation” by Eve Mayer Orsburn | Life@42: A Leadership Social Novel

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