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PharmaLeaks 2: Demographics and Revenue Structure for GlavMed, SpamIt and Rx-promotion

In this entry, Damon McCoy provides results of the study about customer base, products and revenue structure of major online pharmaceutical affiliate programs.

In previous studies, a lot of people, including our group, have inferred just small little parts of these online businesses. And it’s always been unclear as to how accurate these inferences are, and we have only got tiny little pieces of the businesses that we can infer.

However, in PharmaLeaks we have had fortuitous events of getting a large corpus of actual ground truth data that’s been leaked from a few subsets of these online pharmaceutical programs. And with this ground truth data we can do a far more detailed analysis than any other analysis of how these businesses operate, and the dynamics of these three key players: the customers, the affiliates, and the affiliate programs; and understand a lot how this business functions, and understand the fragile parts of their business deeper.

A lot of this information leaked because of the ongoing rivalry between two of these spam operators.

So, let me just quickly go into detail about what this leaked corpus looks like. As part of this leaked data set, we have numerous leaked sources of financial and operational information from three separate affiliate programs. A lot of this information leaked because of the ongoing rivalry between two of these spam operators, and they tend to get pissed off of each other.

They will somehow obtain some information, they will leak it sometimes widely on the Internet, sometimes a little bit less broadly to a large set of law enforcement and reporters, just to say that the other people are really bad and you should lock them up and put them out of business. And then, in retaliation, the other operator will in turn do the same thing to them.

Major pharmaceutical affiliate programs

Major pharmaceutical affiliate programs

So, we received the windfall of this kind of rivalry. And as part of this we have the back-end database, which includes order information, transactional information, a very rich set of information on the GlavMed / SpamIt programs, which are two of the larger online affiliate programs, according to when we did our analysis of spam and linked it back to the different pharmaceutical affiliate programs.

We also have chat logs from the operators of the GlavMed / SpamIt programs which, again, give us a lot of metadata and insight into how their business operates. We have a more restricted set of transactional information from the Rx-Promotion affiliate program – again, an extremely major online affiliate program that constituted a large portion of spam while they were operating. And we also have extremely fine-grained revenue and cost structure information for Rx-Promotion.

Just a quick summary of this data: it encompasses over $185M in revenue of purchases. It encompasses over a million customers, over 1.5 million orders, and over 2,600 affiliates (see below).

Operational summary for major pharma networks

During our analysis of this data, we realized that GlavMed has often denied that they are the operator of SpamIt, however by our analysis of the databases of GlavMed / SpamIt, we realized these two are operated by the same people. And also, Rx-Promotion transactional data, as I said, is somewhat limited. It is limited to the US customers. Luckily, US customers make up the majority of all customers. So we get a fairly detailed picture of Rx-Promotion from this limited transactional data.

Customer demographics

Customer demographics

Now let’s delve into the first player in this spam economy, which is the customer. So, a quick rundown of the demographics of their customer base (see stats to the left). As you can see, majority of it is from the US, then a smattering from Western Europe, Canada and Australia. All told, 95% of the customers are from those four locations. This largely confirms what we presented last year when we inferred from some weblogs the composition and the demographics of the customers.

Product demand

Product demand

So, now that we know the demographics of the customers, let’s look at what these customers are buying. As this ironically shaped graph shows (see image to the right), as you might suspect, they don’t put the Viagra and the Cialis on the front page for no particular reason – that is in fact the large share of what they are selling, the ED pills. And they are selling them to largely male demographic.

They also have a large formulary of other drugs they sell, and they do sell a small fraction of those things also. It depends on the formulary, some pharmacies sell more other drugs and less ED depending on the formulary that they carry, but this is the case for SpamIt and GlavMed. And in fact, 75% of the orders and 80% of the revenue for the GlavMed / SpamIt program are derived from the ED medications.

Revenue structure for Rx-Promotion

Revenue structure for Rx-Promotion

Now let’s take a quick look at Rx-Promotion which had a slightly different formulary. Here is the revenue structure for Rx-Promotion (see graph). We couldn’t get the demographics: the dataset wasn’t rich enough to figure out the demographics for the Rx-Promotion.

Here you can see this kind of interesting, kind of tooth graph. As you can see, they derive a little bit more of their revenue from the pain medications. They derive a lot of their revenue from the ED. You can see the X axis, which is time moving forward, and the Y axis being their revenue numbers derived from each product, but in the middle of this graph you can see this sharp falloff in their revenue.

This sharp revenue falloff was caused by them losing a relationship with one of their payment processors that accepted VISA payments for a certain class of drugs. You can see the class of drugs that fell out of their revenue. And as you can see, this disruption in their payment processing caused their revenue to almost half at this period. At the beginning of this disruption they in fact became unprofitable, and it took them about two to three months to re-establish this payment processing relationship.

As you can see, when a program incurs this kind of payment processing disruption, this has a huge negative impact on the profitability of these businesses. This comes from some of our findings when we mapped out the banking relationships between these programs. This is indeed a fragile, hard-to-replace portion of their business.

Read previous: PharmaLeaks: Understanding the Business of Online Pharmaceutical Affiliate Programs

Read next: PharmaLeaks 3: Customer Acquisition and Affiliate Statistics

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