DMD Intelligence

With all the recent discussion surrounding Google’s deprecation of third-party cookies and Apple’s recent iOS 14.5 release, it’s no wonder healthcare marketers are feeling uncertain—and even anxious. What do these movements really mean for healthcare marketing and HCP engagement?

To fully understand the impact of iOS 14.5, it’s important to consider both the motivation and mechanics behind Apple’s transition to greater transparency.

To Track or Not to Track… That Is the Question

Apple’s previous options regarding privacy—in respect to location services—allowed users to choose from one of three options. 

• Only While Using the App
• Always Allow
• Don't Allow

With iOS 14.5, the options are now:

• Allow Tracking, or
• Ask App Not to Track

In early March, a few of my colleagues and I attended the RampUp LiveRamp Summit in San Francisco. We sat in on a number of digital forward-focused presentations while meeting with a variety of thinkers and leaders in the advertising technology space. Guest panelists represented a diversity of perspectives from companies like Disney, Verizon, Google, and Pandora to more healthcare-centric companies like ourselves.

While the spectrum of topics was broad, many were connected by three pressing matters: the future of cookies, data privacy, and the use of data for the greater good. We’ve had some time to digest how the information we heard impacts healthcare marketers specifically. Here are some thoughts.

This is the final article in our “Pharma and Digital Ad Fraud” series, which has considered a range of issues related to non-human website traffic, including bot creation, bot detection, and fraud prevention.

These days it’s hard not to be alarmed about digital ad fraud. Bots make up more than 50 percent of all web traffic. Digital ad fraud is predicted to cost $19 billion in 2018. Huge bot networks are readily available for rent, and bots convincingly masquerade as human.

Fortunately, advertisers, marketers, and technology companies are joining forces to improve the accountability of digital media. Here’s a quick look at what accountable media means for pharma marketers.  

Our “Pharma and Digital Ad Fraud” blog series examines essential issues related to digital pharma marketing. Previous blogs have discussed good and bad bots, blacklisting and whitelisting, bot generation techniques, and most recently, two simple ways to reduce the risk of ad fraud.

This week we’ll look at the relationship between bots, web analytics, and marketing planning.

Over the last few weeks, we’ve considered a number of issues related to digital ad fraud, including how easy it is to create bots, how hard they are to detect, and how prevalent they’ve become on medical websites. Today, in the fifth blog in our “Pharma and Digital Ad Fraud” series, we’ll explore some proven techniques for safeguarding your digital marketing campaigns.

My Oncology Tomorrow experiment demonstrated how simple and inexpensive it is for cybercriminals to steal ad revenue from medical websites. For less than $200, I created a fake publishing platform, flooded it with bots, and generated $312 in first-month revenues.

To date, our “Pharma and Digital Ad Fraud” blog series has focused primarily on how bots operate in the digital advertising space. In this fourth installment, we’ll consider how bots impact pharma brand websites.

We all know the web is overrun with bots that siphon off millions in ad revenue every single day. Most of us are actively looking for better ways to limit the damage, including getting smarter about how we buy digital media.

This is the third blog in our "Pharma and Digital Ad Fraud" series. In the last few weeks, we’ve explored the differences between good and bad bots, as well as the strengths and limitations of blacklisting and whitelisting. Today, we’ll look at some of the ways bots are created and why they’re so prevalent.

Bot traffic now exceeds human traffic across the Internet, especially in pharma. According to our research, 60 percent of total traffic on some healthcare websites is bot-generated.

Where do all those bots come from? To find out, I took a journey to the dark side of online publishing and bot generation. Here’s what I learned.

This is the second blog in our "Pharma and Digital Ad Fraud" series. Previously, we explored the differences between good and bad bots. This blog will consider several ways pharma marketers can ensure more of the visitors to medical website are actual humans.

This is the first blog in our "Pharma and Digital Ad Fraud" series. In the coming weeks, we’ll take a close look at the threat bots present and what pharma marketers can do to reduce the risk of ad fraud.

Jupiter Research predicts that in 2018 advertisers will lose $51 million dollars per day to digital ad fraud. Growing advertising budgets and high CPM make pharma a particularly attractive target for cybercriminals. Fortunately, there are ways to protect your marketing budget from fraudulent activity.

Developing a thorough understanding of bots is the first step. We’ll kick off our new bot series by exploring the differences between good bots and bad bots.

As we look toward 2018, one thing is certain: Digital ad fraud is here to stay. Beating it will require a thorough understanding of bots, bot detection technologies, and digital audience identification.

These are complex topics, and early next year we’ll begin a blog series that takes an in-depth look at many of them. In the meantime, we want to answer some of the basic questions that will continue to inform pharma marketing’s response to digital ad fraud.