Why the “Mad Men” Approach to Marketing Might Not Be Best for Your Medical Practice

5 Min Read

madmen.jpg

Driving down marketing costs with highly optimized, targeted campaigns might be a better idea than generating maximum exposure.

madmen.jpg

Driving down marketing costs with highly optimized, targeted campaigns might be a better idea than generating maximum exposure.

For one reason or another, medical marketers seem to be obsessed with the “Mad Men” model of marketing (no, we’re not talking about suave suits and heavy drinking). That model says, “We should generate maximum brand awareness on as many channels as possible.” It’s a grandiose, bigger-is-better worldview.

But the internet killed Mad Men, or at least their 1960s mass-marketing philosophy. In its place comes the crystal clarity of data-driven marketing, which was recently named the top priority for brands in 2016 in an Econsultancy survey of industry professionals. This mentality focuses on brand efficiency, and says, “Forget our global reach. How are our campaigns performing with regard to spending? Where can we drive down costs and optimize our message?”

For your medical practice, the latter is typically the more effective approach. Here’s why: 

Why Brand Efficiency Can Upstage Awareness

Medical marketing campaigns have one goal: driving ROI. Crafting a clever tagline on a billboard ad is all well and good, but generating a maximum number of new patients at the lowest possible cost is even better. For a majority of medical practices, especially those with limited marketing budgets, being everywhere is not as important as building a meaningful presence in a highly targeted location.

Rather than gauging your overall reach, it’s more important to ask: what’s your current cost-per-acquisition (CPA)? How many patient leads are you driving? Which channels have the highest qualification rates? Which target keywords — anywhere from 300-1,000 per campaign, with over 50 different copy variants — generate the highest traffic, and with which demographic groups?

The questions are specific, the answers are tangible, and the results come as a percentage decrease in marketing spend. Perhaps the biggest benefit is that once you know which channels consistently deliver, you can hammer them all the way to the bank.

“Try Before You Buy” for Low-Risk Scaling

The big risk of brand awareness strategies is that you can never be sure what your target demographics are thinking. Even if you pay huge sums to reach a wider audience, there’s no guarantee that the right types of patients will see and engage with your message. Instead, it’s more cost-effective to find out what works, and then maximize exposure in those areas.

For instance, healthcare marketers can start off with a variety of low-cost campaigns spanning a number of platforms — pay-per-click (PPC) on Google Adwords, paid Facebook ads, call button extensions, etc. — in order to test the waters and see what works. Tangible results in hand, they can aggressively scale the most effective strategies without taking big risks.

Of course, with data rolling in, you can proceed to optimize your campaigns continuously. One great method for this is A/B testing, which pits one ad copy version against another to determine which messaging is most effective for a particular audience. Marketers can also test the waters for new themes, topics, and search conditions (“30s males seeking podiatrists in Wichita, KS” could be your next big demographic). By optimizing PPC campaigns this way, we’ve been able to consistently achieve cost-reductions of 20-40% over the baseline.

We’ve become much wiser since the Mad Men era in more than a few ways, but for marketers, no advance has been more important than the use of testable metrics to drive down costs. And, of course, a brand efficiency model doesn’t prohibit a medical practices from rapidly expanding their campaigns if they wish to do so. It just provides a data-backed guarantee that they’ll find a receptive, engaged audience at the other end of the line.

(Image: wackystuff/Flickr)

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