A Social Network Visualisation Graph for a Local Business

Thanks to a couple of weeks of trying, and some major digging into APIs and other coding options... I have gathered enough data to put together a rudimentary network of FB relationships of users interacting with Lawrence Companies (LC). I've got some feedback on what that looks like, and some decisions that can be taken now that the data can be put in one place for review. I offer up a couple of options of what can be done with these types of data... after all, you never offer up just one option to a client... or potential client.

To recap, I gathered all the reaction data to LC's FB page since 2011, as well as comments, counts of shares, and mentions. I chose, for the purpose of this graph, to focus on the reactions. There were 3 times as many reactions as shares, mentions, and comments combined, and I've yet to find a way to track shares to individual accounts.

The resulting pull of friends data resulted in 18,940 data points. I forced reciprocal relationships in the data, as FB doesn't make a clear distinction between following and friends. For the purpose of this graph, the assumption is that if you show up on someone's friends list, that you have a reciprocal relationship. Additionally, this graph represents only relationships, and not conversations. I've chosen to identify relationships among those who reacted to posts from LC's FB page.

On to the data. I chose to filter based on a degree range of 6, and removed outliers (of which there were 6) with no connections to the central group. I've anonimised the graph data, because nobody wants to see their friends on FB made public. You will note there are 35 data points, but that the number 7 shows up twice. The repetition is deliberate and not an error. Employees are noted with green nodes, and non-employees with red.

The key question I had was how robust the networks of those reacting were. As stated in the previous post on this topic, approximately 20% of the volume of reactions came from employees. It's also no surprise to me that the most robust networks are employees (1,5,6,7,8,12, and 16). The selection bias of the reactions is most likely the cause... but please note 1,5,7, and 8 have very central positions in this graph... hence a lot of strong connections. The duplication of 7 as an employee and a non-employee results because of that node having multiple FB accounts, and identifying with multiple employers. Had the reactions come from larger non-employee populations, we might have seen other robust networks represented.

So... that's a lot of gobbledy-gook, telling me virtually nothing. What do I do with this thing?

You ask yourself what the objectives of your social outreach is.

I mentioned in a previous post that there are articles discussing truck driver shortages. If increasing driver applications, or increasing incoming owner-operator applications is a key measure, then perhaps working with node 8, a maintenance worker with several truck driver friends may be a good target for beginning outreach. By leveraging experience of node 16, an IT employee, LC should be able to create podcast content that can be gathered from that node's driver friends and shared through LC's main content sites. And good old node 7... that driver has a robust list of other truck driver friends that should have content directed to them. Not on this graph, but also of importance, are the three interns from LC who have reacted to posts and have a group of friends including drivers.

How that content is distributed is another conversation for another post. Let's hold off until the next post for that.

A Social Digital Idea for a Local Business

I've spent so much time in Big Pharma that I'm worried that I've gotten pigeon-holed... Okay, let's be honest, my twitter name is @bradatpharma, so I've kinda done it to myself. I think @bradateverything, though... that's a little too egotistical.

What I want to do, most of all, is find a way that I can describe how what I've worked on doing in a regulated industry for the last 25 years is transferable to other industries. This time, and probably the next couple of times, I'd like to show some of my thoughts around the transportation industry and the use of social digital media. If you've got a Facebook page, a Twitter account, or run ads on Google, what do I know that can be of any help? How can The Lawrence Companies (Lawrence) of Roanoke, VA do anything of value in the social digital space? What is Lawrence doing now that seems problematic... or at least worth a discussion? Can I make any recommendations as to what I'd like to try with them to address problems I see in the transportation industry? Well, I'll do that, and end with a recommendation of what to do with one of their social digital platforms.

Transportation and trucking... admittedly, an industry of which I know only a little, professionally. Let's start with what I know.

When I was a kid, I watched "BJ and the Bear". It's a tv show about a trucker and his chimpanzee... Bear... I know, right, it's a chimpanzee, but it's named "Bear". What's up with that? Since I was that tv-watching tot, I've wanted to drive an 18 wheeler cross-country... and have a chimpanzee. Therefore, it should come as little surprise that I've gathered, at least, a few facts at my fingertips.

• You need a CDL to drive a truck. "Shocking," you may say. But, seriously, this means that you have to undergo a regular certification process for driving a whole other type of vehicle. A process requiring written and practical skills. You have to be dedicated to do this to begin with, usually to the tune of about 3,500 USD, and have to keep up your skills. 18 wheelers on the road are driven by some amazingly adept humans.
• Trucks get things to where they need to be. You may silently, or not so silently, curse that truck driver during your commute, but how do you think the beans for your latte, the gas for your car, the clothes on your back, or the paper in your office printer got to where they are? Trucking, trans-shipping, or local delivery takes trucks and truckers.
• Trucking can often be a one person business. In addition to the skills of just driving your truck, a trucker may have multiple other concerns. Truckers can only do their job 14 hours a day. This means, if somebody took 6 rather than 2 hours to load your truck... you've lost a lot of good hours just sitting around, not making money by being on the road. If you own and operate (o/o) your truck, you're constantly doing the math on depreciation of your tires, how much fuel you're managing, or whether or not you're dead-heading a leg of this trip. They're like trading ship captains.
• Truckers are aging out, and there's not enough talent backfilling. How many times do you hear a child saying, "I want to be a trucker when I grow up," and then hear encouragement for that dream. "No, Jane, you want to go to college and become an accountant." Well, trucking is one more blue collar industry where there are not enough replacements filling the aging workforce. See point 2 for why this may be a problem.

So, I know just enough to be mildly annoying on the topic. But what does that mean from a social digital strategy perspective?

Let's dig into The Lawrence Companies (Lawrence) and a couple of their social digital properties. The company describes itself as being involved in commercial and residential moving, equipment rental, data and records management, and truck repair.

First, I did the obvious... brute force searching in Google. How do those keywords stack up against their Google results? NOTE: Do try this at home, because your results may vary. In my results, I've chosen to see 100 returns on every page. In 12 searches relating to their own company description, Lawrence doesn't show up.

So, I took to Twitter... because that's my preferred platform... and they don't show up in 4 searches related to looking for drivers or the topic of transportation... Honestly, though, that's my fault for doing the search, because they haven't posted in more than a year.

Next, to Facebook. I don't like to start there because data acquisition can be such a mess. They've got 544 posts (your mileage may vary if you check today) since they started the account. Based on the post volume, I'm gonna say they started the account in 2013. We've got 235 comments, 3,464 reactions, and 1,026 shares. Pretty good for come local content.

Once you take out the typical words you'd expect from the posts, you see:

The focus on the page is on employee recognition, concerns for their drivers (i.e. tiptuesday), promoting their services, and a lot of recommendation on residential moving.

The comments that come back tend to be focused a little differently:

From this one you see those dates, and those are answers to trivia questions related to photos. There's additionally a lot of "attaboy" type comments that are tied to the employee recognition.

Of the information I see here, there are few links directly to hiring Lawrence for any of their services. There is no consistent call to action. Nor do there seem to be calls-to-action tied to specific themes.

An additional piece of information that I didn't find until I dug into the posts is that Lawrence is affiliated with United Van Lines... Okay. So, those searches previously mentioned *do* tend to mention United Van Lines, generally in the ad portion. I didn't field test any phone calls to see if I got transferred to Lawrence... maybe I should do that next.

One of my most favorite little insights actually comes from tracking those who *reacted* to posts. So, we've got those 3,464 reactions, and when you pull them and sort them by user, you see that approximately 20% of them come from current and former employees. So, you've got an account executive from North Carolina, another Lawrence executive, a few office staff, as well as a few drivers. A nice crowd, but very little consistent reach outside of corporate environs.

I'm working on a network visualization... but I'm amazed how difficult it is to gather any relationship data from FB.

Ultimately, If I take what I know about the transportation industry, I really only see about 1 and a half of those 4 points I know anything about being dealt with in the FB feed.

So, let me offer my first idea that I would love to see Lawrence try out.

It is awesome when you call out drivers for awards and performance. Keep that up. I'd love to see two calls to action on each of those posts.

1. Ask people to add their best wishes to the driver being recognized. Ask them to share it with their friends in the industry. See if you can get a wider audience to see the drivers who are really good at their job.
2. Include a call to action for prospective driver candidates to apply to drive for Lawrence.

I've got some more ideas in the bag... but I'm gonna let those brew in my noggin to see how they shake out.

"we want health care for people not just for feeding shareholder value"

I had an interesting exchange with @stales recently. Her posit was that you couldn't mine or analyse all the data associated with a patient, so how do you improve patient journey analysis?

Tons of data is generated, but we can't possible analyze and mine it all = what are we missing? #patientjourneys

— Alicia C. Staley (@stales) June 12, 2017

You get lots of data to a system that can analyse it and then you find a trusted broker to put all that data together and figure out how to work with the appropriate parties, like Big Pharma and insurance companies.

To begin, I responded that I'm sure we can analyse it all... that's what machine learning is for. Of course, machine learning has hit some bumps with @ibmwatson lately. In my humble opinion, the issue with Watson hasn't been with the learning, but with the predicting. Machine learning is fairly standardised at this point.

A quick tutorial from a novice... feel free to skip this or correct me...

Machine learning takes samples known cases. So, let's say I want to analyse a journey of a breast cancer patient. I may want to pick data from @stales and review her:

• search terms and search agents
• social activity in twitter and facebook
• blog posts
• medical billing records
• electronic health records (EHR)
• prescription purchases

before, during, and after her diagnosis. Then I'll also pick about 50-100 or or so other breast cancer patients' data and feed it all into the program. The machine learning tool develops patterns of search terms, social posts, physician visits, prescriptions... the whole ball of wax. Then, and this is where the data gets to be useful, we take other patients who might not yet have been diagnosed, and pop their search data, their posts, their medical data into the program. As the machine learning tool identifies similarities to the baseline, the system will flag them for review. "Here's a potential match..." That sort of thing. Where this all gets dicey is if the system tries to predict what will happen next... "Well, you've done a, b, and c... so d-z may be logical next steps."

If this all sounds like I'm some fiend from insert your favourite evil technology movie here... I'm sorry. The point of data is to analyse it. WHAT WE DO WITH THE ANALYSIS IS WHAT MARKS US OUT AS HUMAN/ EVIL FIEND.

One of my other points in my conversation with @stales was that we need to have trust from patients and honesty from Big Pharma. You see, I'm assuming that Big Pharma will use the data to develop therapies which can help stem the progression of disorders, prevent disorders from occurring, or help manage the disorder until a cure can be discovered. This kind of agreement, this tit for tat, assumes that patients give up an immense amount of privacy and Big Pharma gains a metric buttload of data that helps these patients and those coming after them.

The potential legal conundra emanating from this are legion. If a bulk of unblinded health data exists, what happens when insurance get their hands on it? If predictive analysis becomes the standard, what happens when decisions are taken for continuing coverage based on the analytics? When Big Pharma can microtarget patients, what does that advertising look like? HIPAA? Will governmental agencies exclude immigrants based on health history?

Of course, I mention those things because they're already happening. Insurance companies spend a lot of money to have the most robust actuarial tables for inclusion/ exclusion criteria. Big Pharma already combs through blinded EHR data to identify markets for clinical trials or drug development. HIPAA sometimes feels like a cruel joke intended to make it harder for my data to be used by multiple physicians. I'll leave the last one alone... but google your own examples.

So, there's no clear reason to assume that Big Pharma or the insurance industry can be trusted. Unless you have a monopoly on the research, development, approval, manufacture, distribution, and payment for treatments though, there's no other game in town.

An honest, intermediate broker though... that has some legs.

If we look at the example of the Cystic Fibrosis Foundation (CFF), and their development of Kalydeco, we may have the best example of what happens when an honest broker gets involved in the patient journey.

By establishing a "Venture Philanthropy" model, the CFF was able to solicit funding which then went to targeted research clinicians who developed a drug approved by the FDA... which then went on to be marketed by a company for 300,000USD per year...

But the model exists. It's there. It got the job done... right up until that last part. So, we can modify the working model. It's what you do. You don't say, "Well, that didn't work... looks like we have to find some completely other new way to do it." You say, "Well, that *almost* worked... what failed? Let's fix that."

To that end, the trusted broker is probably going to have to come from each disease constituency. CFF showed that a dedicated group can get shit done. So, the National Multiple Sclerosis Society, American Diabetes Association, Short Bowel Syndrome Foundation, American Cancer Society, Sjogrens Syndrome Foundation, American Heart Association, Crohn's & Colitis Foundation, National Organization for Rare Disorders, and the multitude others can act as data repositories for the journey of their patients. You can guarantee that each group is staffed with a Chief Data Officer or Technology Officer or other job. Those staffers needs to lead the charge to get the data resources for their analyses.

Of course, data analysis is a back-office task. It's not pretty. It's viewed as a bunch of data-loving nerds crunching numbers, building statistical models, producing charts... like patient journeys... for other people to never read in white papers.

If we want the data for patient journeys, we have to gather and analyse the data for patient journeys. And we have to find people who love healthcare data specifically to do these analyses. You *do* fall into a flow that may make you seem like Dr. Evil while you're doing your analysis... but those of us who love healthcare data love it because we know if we find a new data point that helps identify patients early, or finds a new influencer with a new point of view, or tease out that one lab test that seems to be helping identify patients more commonly than others, or help develop appropriate pricing models... we want health care for people not just for feeding shareholder value.

Getting to "Big Insights" requires a little infrastructure first

At the risk of offending the world of analytics, I would posit that most of the world does not need to worry about "Big Data"... and thus has no cause to worry about "Big Insights" either. Most companies have no idea what data they've got, let alone if it's Big, or not. The other problem I've seen is companies who have data, and have decided to declare it Big... without knowing what other data they need or already have access to.

This does not mean that a mom & pop can't have Big Insights from Small Data. This also does not mean that a multi-national can only get Small Insights from Big Data.

What it does mean is that trying to claim you have Big or Small anything is kind of pointless.

Okay, fine... you have to put a stake in the sand at some point. That stake, though, is for your current decision. "Analysis Paralysis" does not mean "Analysis Stagnation".

Let's see... that six cliches in three paragraphs... that's enough.

Let's take a practical application.

I'm a mid-sized company, with a sales force, a moderately aggressive direct marketing campaign, purchases of radio and television time in several top markets, banner ad buys, as well as a social media advertising tactical approach.

My sales team has decided that my representatives will be making the classic 8 calls a day. I will send out 3 direct mailers every quarter. I'm running cable ad buys, talk radio hour mid-day ads, as well as intermittent satellite radio ads. I buy Facebook ads targeted at my demographic and run promoted Twitter ads.

If you take what I've seen most companies use as a typical approach, that's anywhere from 4-6 different campaigns with different KPIs, with different budget line items, with different objectives, and with different data stores.

My sales targets are now being subjected to multiple touches, and those 4-6 categories each count this as their max number of touches.

Meanwhile, my customer has grown tired of being touched so many $*&^&%@# times.

An insight here, of some non-identified size, is that it would be nice if I knew how many times my whole company was touching a customer. I can't begin to do this unless I have some kind of coordinated data infrastructure.

All that money I spend on 8 calls a day? Well, maybe it should be 6 times a day, with pull-through of mailers, ads, and social tactics instead...

All that money I spend on 3 mailers a quarter? Maybe it should be 1 because I've got sales representatives in the office and my clients are all touchable via media buys, as well social media outreach.

If I don't coordinate my data sources, and don't have a unified data infrastructure, I could be wasting budget line items that could be better used elsewhere... or I could be missing opportunities because I need to be spending more money everywhere.

Now imagine what you can do if you integrate social data with sales data... or your key opinion leaders with social activity related to nearby teaching centers... or how you could efficiently promote that new contract win through your partner's social channels and your press release contacts...

Your data needs to be as coordinated as it can be. You need to make a decision. You need to act. Then you need to look at your data sources again, so that your next decision is as coordinated as it can be.

14 April NOTE: I'm looking for a new gig, so feel free to reach out to me if this kind of thing is a problem you've got in your organisation and you'd like me to come talk to you about how we can work together to bring your coordination and integration into your next set of decisions.

Thinking about why I work in Pharma...

People I encountered used to get this look on their faces when I told them that I worked for Pharma. Almost as though I was some previously unseen - but often theorised - species of giant, hissing, talking cockroach. You know that look... it's also the one you get on your own face when you find fresh dog shit on the bottom of your shoe. I suppose it was because of the negative rap given to Pharma in general... much like this graph:

I once described that graph out loud in a meeting when I was employed by a Big Pharma company, and my boss warned me to "never... do... that... again...".

This graph and that warning came back to me again when I was listening to a PodCast from Freakonomics, called "Do Boycotts Work?". As part of the PodCast, a theory was posited that boycotts cast negative shadows over a company, often creating negative reputational impacts. This was challenged by one of the interviewees who is a researcher involved in plant science and plant geneticsg. His point was that while he agreed politically with almost every point of other liberals, their anti-GMO and anti-Monsanto opinions didn't resonate with him. They didn't resonate to such a degree that he took a job with Monstanto because they were doing cutting edge work in his field. He does admit that he does not lead with, "Hi, I work for Monsanto..." because of the public negativity toward his current employer, but he is happy in his work.

What I found most interesting in his interview was when he stated, "... I don't think the company is doing anything evil. It's a large company that makes the same decisions any other large company would... The company's values are the values of a successful, large company, and they are not, uh, what the public perception might have you believe that they're out to rip off and destroy agriculture and farmers."

I am pretty sure that what follows, my statement of what Big Pharma can do, may be viewed as some to be the repetitions of some kind of cult member, or some kind of apologist... but honestly, chances are if you've read my work, or met me before, you're not putting me in that bucket... unless you're my brother-in-law... a Vegan...

That last statement of the interviewee, really resonated with me. When I work in, or with, Big Pharma employees, I find that almost all of them are good people... almost all of us are good people. We go to work for the specific purpose of earning a living by helping others. We're about four steps away from the actual patient, but we try to keep the fact that we're helping people in the forefront of our minds. I'm not speaking about CEOs, or others in the C-Suite. Even in that group, I've found more than half are dedicated to helping patients. Heck, some CEOs are even former drug researchers... former science nerds. This eye toward helping people is what still gets me up and running.

I scan social media data so that I can help my Big Pharma clients understand:

• what patients have to say about their lives
• what patients say about their treatment options
• when and how patients seek information about their disease and treatment
• how physicians behave in sharing information in social media channels
• what a physician's network looks like so we understand more about who that physician is
• what content can resonate in a patient or physician conversation
• where caregivers go to seek solace or a break from working with their loved ones
• what represents hope for patients, physicians, advocacy groups, or caregivers

A key objective of all of this work is to help my Big Pharma clients act like a contributor, and not like a loud huckster. And being a contributor includes being a trusted, reliable, less-biased, and "good actor" in their social media efforts.

Ultimately, Big Pharma will do whatever Big Pharma needs to do to generate the profits demanded by the financial markets. I'm not imagining a future when a company spends millions or billions to just give things away. Remember, "The company's values are the values of a successful, large company...". The hope that I have, yes I still am somewhat idealistic, is that as Big Pharma gets closer to patients, a little bit of understanding can be passed back and forth.

And maybe... just maybe... one day, Big Pharma will move above The Mafia.

Add these to your 2016 To Do List... No, Really...

Thanks to my amazing colleague, Eric Shenfield, for pointing out this article from DRG, "New Year's Resolutions for Pharma Marketers". It's worth a read... go... check it out... I'll wait.

Pretty good, huh?

Where have I seen those recommendations before? I know I've seen them somewhere...

Oh, right. It's what we've been telling Big Pharma to do for about three years now. When I say, WE, I mean all of the people I know who are involved in digital and mobile recommendations for Big Pharma... yes, it's missing people... no, it's not just the agency I work for... and not just me...

Let's review the DRG/ everybody involved in digital pharma recommendations. Because, there are some extremely actionable steps that Big Pharma can do, and if you'll excuse my presumption, fall within FDA Draft Guidance.

Help Patients Help Themselves:

e-Patient Dave de Bronkhart, Kerri Sparling, Natasha Tracy, WeGo Health... to name a few, are the kinds of people and groups focused on specifically supporting patients in their respective disease states. How do I know these people? I've been around. How can Big Pharma get to know these people? By listening, and investing in comprehensive influencer identification... not just Klout score, or twitter followers... but really investigating the content these influencers share, determine their primary connections, understanding how Big Pharma can provide unbiased content that can be sources of education and support for their followers needs. By the way, that list includes, like, three things W2O does with Analytics, and a couple we do with virtual boots on the ground, thanks to Eileen O'Brien and Greg Matthews.

Support Telemedicine, Electronic Health Records, and appropriate use of ICD10:

Wait a second, didn't we already cover supporting patients? Yes... yes, we did...

But this section can also be covered by helping physicians provide actionable data to patients. This means working with influencers to identify content that will support patients in a specific disease state community... let's say Crohn's... providing the influencers with content to share via any of the social networks (staying fully regulatorily compliant) and then ALSO providing that to specialists in diagnosing/ treating/ caring for patients in that community so they can share it via electronic health records that provide patients with understandable information. Not, Crohn's for Dummies language, but Crohn's language for people who will then take the language and google it and then find the influencers discussing the topic, and have access to other patient support materials, and influencers who provide relevant and appropriate types of recommendations to memebers of their community.

This does not mean that you take a shiny marketing piece and format it for a different environment... because chances are that the language in that marketing piece amounts to "New, Improved, Better for You..." when patients are discussing quality of life topics, or everyday hiccups in their world because of their conditions, or wondering how to tell their friends and family what's going on with them, or finding other people to talk to because their family thinks they're annoying...

This does not mean that you write a biased puff piece that talks about how awesome your drug is... because chances are that the language in that puff piece will be transparent as self-serving marketing. Again, understanding what issues are facing parents and how Big Pharma's research and in-depth understanding of the disease space (which any pharma should have before entering into research, anyway) can then help patients is key.

You don't want to be the guy who shows up to the potluck with no hot dish and then stands in the corner shouting about how awesome he is. Social media is like a party where you get to be an active, engaged participant in a conversation. Be a narcissist and the people you're working so hard to impress will walk away.

Redefine your sales staff:

All this digital stuff is pretty darned cool. I live it. I really enjoy it.

This does not mean, however, that a field force is now just an electronic detail aid away from making your drug the next blockbuster.

It does, IMHO, mean that your sales staff should now include anybody in your organisation that interacts with your customer. If your Customer Relationship Management software is still only counting field force touches on a physician/ payor/ advocacy group/ formulary group/ accountability care organization/ pharmaceutical benefit manager/ group practice (I think you get the idea) as a touch... then I think you may be underestimating your impact on a customer's time.

Expand your thinking for what a touch is, and quite frankly how you incentivize your expanded sales staff... here at W2O, specifically in Greg Matthew's and my brains, we've got some pilots we've engineered that may make your head spin just a LOT... but that's not for the blogosphere.


Track, Track, Track:

Okay, your privacy officers may now want to reach through the computer screen and smack the heck out of me, but I can take it. There is a wide swath of unactivated, non-personalised data that I think you're all missing. AND, I think it's data that your privacy officers have already approved for use. Let me not assume to understand the brain of the privacy officer, though.

Let's use an example, though... Are you creating unique short, trackable URLs for your various social media campaigns which lead to co-pay cards or physician locators or regional advocacy chapters, tying them back to internal marketing codes, then matching them to geographic data based on rolled-up IP addresses matched to your DMA and field force data because you want to know if your coordinated campaign had impact on your final scrip volume? Every step of that track might have required some privacy officer to review the tracked and transferred data... so you've probably even got most of the approvals you need.

Okay... that one may need more than an elevator pitch of two sentences, so you should probably call us so we can walk you through what's going on in our brains about that one.

Oh, and yes, in several states, it's illegal for your sales staff to even have access to that data... Fine. Don't give it to them. Creating an active physician score based on multiple measures, including social impact is something they are probably allowed to have... aaaaaaaaaaand that's something else we can help you build.


Good grief, this is sounding more and more like a pitch email, and less like me dumping my brain on the page.

How do we sum this up.

Okay, how's this.

The thoughts expressed here are intended to stir conversation, let you know what's going on in my head, what I think is possible.

There are multiple agencies who can do this... and multiple ways to do them.

I just happen to think I work for somebody who encourages me to let my brain run free on topics like this, and is best positioned to actually execute on these types of ideas.So, maybe it's a pitch, but it's a pitch based on the least biased information I can provide.

Call us, eh.

And if you're not gonna call us... Call somebody, because if you don't do these things, one of your competitors will, and you'll not only miss out, you're gonna fall behind.

Coordinated Social Engagement by a Traditional Media Giant

I review data... I visualise data... it's my job.

To that end, I keep an eye on who is publishing what and how. So, when I see a weird trend, I stop and ask to see if it's as weird as I think it is.

The Wall Street Journal recently published an online article from Jeanne Whalen, "Why the U.S. Pays More Than Other Countries for Drugs", and it kinda went ballistic. If you look at the page, you see 5,523 shares from Facebook.

OMG!

Not really.

This is a huge topic, right now. Of course an article on this will get a lot of shares.

What struck me as odd, then?

I want to know who shared this article.

Part of what my agency does is track social profiles for a lot of different categories. It's kind of our thing. It's proprietary, and it's awesome. It's called MDigital Life. We started with physicians, and have expanded into other areas, such as media outlets and journalists.

Which is why I can tell you with authority that there were at least 25 of our identified journalist influencers who shared this article.

"Yawn..."

But wait, there's more.

Of those 25, 17 of them were from WSJ.

17 of 25.

Who organises that well? Apparently, WSJ.

At first, I'm thinking, "Okay, it's mostly their health desk."

Nope.

To name a few, I've got a page one editor, an EMEA markets editor, a relationship columnist, and a housing and mortgage market reporter. I also have the Asia, Canada, and Infographics desks sharing the article.

Colour me impressed if WSJ got their teams together to put in a concerted effort for blowing this article up.

If not, colour me wicked surprised that such a huge, unlikely coincidence occured and gave them an unexpected windfall.