Sheena is a click farmer

image of The RamonesIn case you missed it, there’s been plenty of great articles and posts recently asking a very simple question about Facebook: How many Facebook accounts are bullshit due to fraud from click farms? A well-made video kicked off the recent spate of stories on the topic. Here’s a run down of what’s been in the news:


Veritasium on YouTube: Facebook Fraud 

Washington Post: This blogger paid Facebook to promote his page. He got 80,000 bogus Likes instead

Salon: Facebook’s black market problem revealed

USA Today: Want fans? Hire a social media ‘click farm’

This of course leads to the natural follow-up question that any marketer should ask: So how much bullshit am I paying for when I buy an ad on Facebook?

I really loved the “Facebook Fraud” video (the first link above, by real-life science geek Derek Muller). However, there are some very big caveats to his video which need to be mentioned. Muller starts off mentioning an experiment run by a BBC reporter back in 2012. The reporter set out to determine what a “Like” was worth by building a Facebook account for something called “Virtual Bagel.” Then, he used Facebook’s ad platform to buy $100 worth of “Likes” … in countries where known click farms come from (gee – wonder if that affected results?).

The lesson here is fairly obvious. If you don’t target your ads (which is fairly easy to do on Facebook ad manager settings) I would imagine that of course you are attracting a lot of bottom-feeders. That’s lesson number one (and keep track because there will be a quiz). Facebook in 2012 since then said it deleted millions of “fake” accounts from click farms — something Muller follows up on by reproducing (more or less) the “Virtual Bagel” experiment.

What he discovered, however, is that nearly all of those new likes he got from a recent experiment were not engaging with his page. So … nothing seems to be solved, and may indeed be getting worse (according to Muller). In fact, it gets more nefarious. Many of these new accounts didn’t appear to come from known “click farm” countries. They seemed to be coming from the US. But there was something odd about these Likes … these accounts “Liked” way too many things to seem natural — and the things these “people” liked were odd.

My own experiment

Recently, I conducted some testing of Facebook (and other) ads for a client. I’m not going to divulge the results, but I will say this. Of the recent Likes we gathered, I decided to look at a representative sample to see if I could find accounts that screamed “click farm” — clearly.

I did not find a torrent of fake accounts. Not by a long shot. You see, I took the trouble to carefully target the ads.

However, I certainly found between 10% and 20% that were suspicious. A few fairly screamed click farm — which seemed to represent about 12% of the total (I looked at a sample of my new Likes — not all of them). Either way you cut it, paying for obvious fraud is not acceptable.

One of the new Likes my client gathered was from a person I’ll only identify as “Sheena.” Because there is a small chance — very, small — that I’m wrong, I won’t identify the account completely. But let me tell you a bit about “Sheena”…

Sheena certainly likes a lot of things. And yet, the only thing on her profile is that this blonde-haired twenty-something is female. Good to know! Oh, and according to her timeline … she changed her cover photo. There are no other posts to see.

Oh, and she sure likes a lot of things. To be specific … 33,000 things. Just to put that number in perspective, if you “liked” five things a day, for every single day of the year, rain or shine, come hell or high water, it would take you 18 years to hit that number. Or let’s say 20 things a day, for every single day of the year for 4 and a half years … Possible, but not plausible.

And it’s not just that Sheena likes so many things (and she’s so young and … blonde … too!) This little OCD like-monkey has quite the unusual taste in what she “likes.” It seems, for instance, that she “Likes” 10,000 restaurants. Which is quite the feat. I’m sure I’ll get to know “Sheena” better when we all see her on a future episode of “My 600-pound life” on the The Learning Channel. And it’s not just that she likes so many restaurants … she even likes every location of a franchise! Isn’t that neat-0!

She also “Likes” the Chicago Blackhawks AND the Montreal Canadiens. If you know hockey, you know how ridiculous that last sentence is. That’s like saying you’re a vegetarian who just LOVES to pick out their own baby cow to kill to make veal patties.

The sad reality is, I don’t really know if Sheena is a click farmer or not. I do know her account fairly screams it. My concern is that … I can’t tell. And that should worry Facebook a lot that people putting money on the table can’t really tell what’s fake and what’s real.

(And yeah, I supposed I should have named the blog “Is Sheena a click farmer?” … but “Sheena is a click farmer” sounds too close to “Sheena is a Punk Rocker” by the Ramones. And I like the Ramones. Suck it Robin Thicke)

I will say this: if you don’t target and test, you are opening yourself up to manipulation by fraudsters. Maybe that’s the price of playing this game. Nonetheless, I doubt there are very many businesses that contain an asterisk in their billing statements that reads “*Your results may vary. Sometimes you’ll be paying for a lot of fraud.”


Photo credit:By Plismo (Own work) [CC-BY-SA-3.0], via Wikimedia Commons

The big problem with content marketing is too much (crappy) content

So because no one else seems to be willing to say it, I will: The boom in content marketing has led to a tidal wave of crappy content. Either that, or Google has changed their algorithm to ensure that every time I search for something substantial I get shallow, pedestrian blog posts and 10-page Slideshare presentations that manage to say nothing.

Either way, it’s getting ridiculous. 

I’m serious people! Recently I’ve been working on experimenting with Facebook and LinkedIn ads for a client. So, when it was time to put together my own reporting on the results, I struggled with some of Facebook’s definitions. Yes, I found a glossary of Facebook ad definitions (here), but I was curious to see what other people had written about how they measure Facebook ad performance.

So I searched for information on many terms related to Facebook ads, and tried to find some posts on how others measured ROI of Facebook ads. The search was fairly useless, at first. Then I kept following bread crumbs to other … useless posts. Then I followed more results to find … shallow crap.

What really intrigued me, though, was that so many of these posts were from people who where obviously in the marketing biz. And they couldn’t muster anything much more obvious than “measure impressions and click throughs!” … Thanks Einstein.

Marketers writing about marketing (what I’m doing at this moment, yes I know the irony) in order to advertise a marketing service is something I call reflexive-marketing. And there is way too much f—ing reflexive marketing content out there people.

And it’s not particularly illuminating. Remember that 10 page Slideshare presentation I found? Honestly, putting a graphic up that tells the reader to remember that “Facebook is social!” kind of assumes the reader is an idiot or possibly has never been exposed to civilization on planet Earth. But maybe that’s who you think your audience is — good luck with that.

I even found a packet of posts from a huge website devoted to social media news on the subject of Facebook ROI.

All. Superficial. Crap.

So … If I’m getting swamped by content by marketers who can’t get beyond the superficial, the obvious and the near-moronic, what, in god’s name, are marketers doing when writing about their clients’ subjects?

OK, I’ve been venting. But you know what, I’d like to see a lot more people talking about what they really experience in the world of content marketing than 100 reflexive marketing blogs trying to blow a lot of smoke up my nether regions. But maybe that’s just me. Now excuse me, I have to cobble together some more reports based on Facebook’s epically shitty ad metrics data.

Oh, and just to show there’s an exception to the rule, here’s a great post on Facebook ROI from Emeric Ernoult on the Duct Tape Marketing blog: The 6 metrics that determine your success on Facebook. Not coincidentally, Ernoult’s company decodes Facebook’s shitty metrics into usable information. And no, I didn’t get paid to say that.

Photo Credit: Ben Brown via Compfight cc

A short primer for media and politicians on metrics

kitty count2The other day I had to roll my eyes again at the TV screen when yet another reporter covering the federal Affordable Care Act website ( did something that drove me crazy.

Many reporters — and politicians — simply don’t know how to use the terminology of website analytics. They make understandable but crucial mistakes that only help to confuse matters. I heard one reporter say that the federal website had reported more than 100,000 “visitors” and then in the next moment a graphic went up showing the 100,000+ “visits” reported by the HHS, which is not the same thing. I’m not sure who got which information wrong — but the point still sticks. There’s a lot of confusion about common website metrics terminology.

This wasn’t t he first time I’d heard, read or seen a mistake like this in reporting on the federal ACA website.

It is perfectly understandable, however, that media and politician are not familiar with web analytics and terminology. It is not always intuitive and it can get very complex. However … when reporting on a national story, it would help if everyone knew the key definitions that matter.

What follows are some key points about website metrics (and definitions) that may help shed some light on the matter.

“Visits” do not equal “Visitors.  This is an easy mistake to make, but getting this wrong will really distort understanding of website performance. A Visit is just another way of saying a session — or the number of times a visitor comes to your site, which expires after inactivity or when leaving the site. Let’s use the convention analogy: the Visit is just the number of times visitors come through the turnstiles to enter the convention center. They may visit and look around, go to lunch, come back, go to their hotel room, and come back on day two of the convention. That’s three visits — three clicks of the turnstile. So yes, one person may do that many times, so “Visit” does not equal “Visitor” in the sense that it is measuring people.

“People” and “Unique Visitors.” So what everyone really wants to know is how many real people visit a site. The closest (though imperfect) way to count this is by counting the number of Unique Visitors. This is the count of unduplicated visitors to a website, over a selected period of time. Google calculates this, for example, by looking at cookies and their match to browsers. You can see the problem there … if the same person erases cookies or switches browsers or devices (like using your smart phone or iPad) you get multiple counts from a single “visitor.”  Some experts estimate “Unique visitor” count is artificially high and can be off by 25% to 39%. Using the convention analogy again, Unique Visitor is the number of badges you give out to approved attendees. They may get their badge scanned many times for entry to the event … but you only made one badge.

Pageviews  When trying to determine overall popularity of any website or portion of a website, you’ll want to know the Pageviews. This metric is fairly intuitive — it is literally how many web pages are served to a browser, and the count is added up over time. If you visit the home page and go to another page, then back to the home page, then to another page, then back to the home page, that’s three pageviews of the homepage. Pageview metrics are great for their overall count, but where they really count is in determining interest among all the sections and pages of content of a website. An example: Let’s say a site gets one million pageviews. “Great!” you say. Then you find out that of those one million pageviews, 600,000 were in the “Help” section and the “I don’t know where to start” page … then it’s not so good news, is it?

The convention center analogy doesn’t work so great for this metric, but you can think of every page of your site as a booth at a convention, and this counts the number of times people looked at a booth (see, I told you the analogy wasn’t that good).

Bounce Rate Maybe I missed it, but I have yet to hear or read anyone asking about the ACA website’s bounce rate — which is important. It’s important to all sites as a broad metric, and it is especially important as a “red flag” indicator. Understanding Bounce Rate is also important as a “reality check” on all metrics.

So what is Bounce Rate? It’s a single visit without any interaction. In other words “We came, we saw one page, we left.” Most people would be shocked to find out just how high bounce rates are for any website. I’ve seen sites that get extremely healthy traffic — and have seen Bounce Rates of around or close to 50% … yes, meaning half of all visits are one-page-and-gone. If a website is having bad technical problems, it should have a Bounce Rate far higher than 50%. When those problems get solved, it should go down. Again, this is a metric best observed over time. As a stand alone number, it’s not so important. The question is — what’s influencing the Bounce Rate (up or down)?

For the question of form completions: Any website can use multiple forms — form completion can go by many names, but “form completion” is the best, IMHO. I saw in the most recent data released by Health and Human Services that they referred to forms completed. That is a sterile but accurate and appropriate way to judge a website’s performance as well. What media and lawmakers should be asking is how many of those forms completed have led to actual coverage — that’s what everyone is wondering.

But from what I understand how the site work, insurance companies will ultimately be granting the coverage — so that is technically not a standard metric to be gathered from live data — it can only be compiled after input from insurance companies. Forms NOT completed is an interesting question too — which may give everyone an idea of the abandonment of effort. Just my two cents.

Are there other metrics that the media and politicians should be watching?

* Original image credit: By David Corby Edited by: Arad (Image:Kittyplya03042006.JPG) [GFDL, CC-BY-SA-3.0 or CC-BY-2.5], via Wikimedia Commons