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Marketing to Dr. Watson: Here’s how we might use data to influence machines

(Cross-posted from Klick Health blog.)

This past week, IBM’s Jeopardy-winning AI Watson furthered its medical career with new jobs that could significantly disrupt healthcare and permanently shift pharmaceutical marketing practices.

That might seem dramatic given Watson’s humble start as a game show contestant. But ever since it (I keep struggling to not say “he”) trounced the world’s best Jeopardy players, I’ve followed its rapid progress from Alex Trebek’s stage through medical education and now into gainful employment. With each step, I’ve become increasingly convinced that Watson and systems like it will drive or at least facilitate fundamental changes in healthcare—and healthcare marketing. So how might we respond?

From Jeopardy to oncology

For those who don’t know, it was reported this week that Watson will officially begin work helping doctors diagnose and treat patients, while helping insurers evaluate treatment coverage. This follows many months of Watson getting educated in medicine. For oncology, Watson was trained by the world’s best oncologists and has effectively consumed, as I understand it, every piece of useful data on the topic, including the latest research—with which it stays continuously up to date. It then uses the same approach it used on Jeopardy to apply that knowledge to diagnosis and treatment.

Physicians give Watson a case, just as Trebek gave it an answer, and Watson gives them diagnostic and treatment recommendations with varying probabilities of correctness. (Example: A 95% chance that, based on the information provided, a person has prostate cancer.) Physicians then choose to agree or disagree with Watson. But, as one oncologist noted during a pilot, it’s hard to disagree with a system that knows exponentially more than you, is trained by the world’s best physicians, and is completely up to date with the latest research.

And Watson isn’t the only system showing promise at improving diagnosis and treatment while reducing costs. Also this past week, Indiana University researchers reported on predictive modelling techniques that improve patient outcomes by 40% and reduce treatment costs by 50%.

Towards a new discipline: “Artificial Intelligence Optimization”

While the creators of these systems take pains to say they’re not displacing doctors, just augmenting them, I consider that political correctness rather than fact. With soaring costs, doctor shortages and challenges for doctors to keep pace with the increasing volume of research and data, it seems inevitable that a shift to artificially intelligent doctors will occur—especially since their “brain” can be distributed as software or made available via the cloud. (At the most controversial end of the spectrum, venture capitalist Vinod Khosla says machines will do 80% of what doctors currently do.)

Such a shift is already happening with web- and smartphone-based consumer tools. For example, Symcat provides patients with free big data-driven diagnoses, Medify provides patients with disease and treatment guidance based on evaluation of published research, and Treato, which I’ve written about previously, analyzes social media conversation to determine what real patients think of treatments.

If the shift towards machine-driven diagnostics and treatment, and away from physician-driven, continues, it could have a significant impact on pharmaceutical marketing. How do you influence an algorithm?

From my perspective, the common thread through these services is their reliance on data–structured and unstructured. Hence the focus of pharmaceutical marketing might need to shift increasingly towardsmaximizing the generation and digital distribution of data that improves appropriate diagnosis and treatment of patients who can benefit from an intervention. For example, investment might be warranted in:

  • Additional clinical trials that result in published data Watson and other systems can use for diagnostic, treatment and insurance recommendations
  • Encouraging patients to talk openly (in a compliant way, of course) in public forums about their positive experiences with a treatment, so social media aggregators pick up and analyze the posts
  • Data monitoring to identify and address prospective negative data that could adversely impact treatment usage

Of course, these are just some early thoughts. I imagine that as this trend hastens, we’ll develop dedicated disciplines to optimize data for artificial intelligence and analytics engines the way we currently optimize content for search engines. The good news is that, overall, this should improve the application of data to diagnosing and treating patients, while helping address ballooning healthcare costs. The challenge is that the path is uncertain; Watson is an amazing diagnostician, but it can’t predict the future.

At least not yet.

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The risk of other people’s platforms

(Cross-posted from the Klick Health blog.)

A few weeks ago, I received an alarming email from Twitter stating that my account was suspended for impersonation. At first, I thought it was spam. But after navigating to my Twitter profile and seeing an account suspension notice, I went into panic mode.

I’m by no means a huge Twitter user, but like many people and brands, I use it to connect and communicate with an audience, and have cultivated a presence on the platform for more than four years—all the while dutifully staying within the boundaries of Twitter etiquette and rules. Losing my account felt like being evicted from a house that I built.

It was, however, a house that I built on someone else’s land. And being so abruptly removed was a reminder of the risky path many brands walk by putting too many eggs in other people’s baskets—be it Twitter, Facebook or YouTube.

My Twitter suspension email, apparently for impersonating myself. After a few emails to support, my account was reinstated, but with no explanation.

What’s your company’s AOL keyword?

I often hear marketing managers talk with reverence about platforms like Facebook and YouTube while grudgingly acknowledging that they need a website at all. Some companies go so far as to redirect their domain to their Facebook page, and Facebook reps have talked about a future in which companies with Facebook pages won’t need websites.

And it seems appealing. Who wants to maintain a website when companies like Facebook give you the tools to communicate and engage directly with your audience? Free? (And pharma is by no means exempt; an increasing number of pharma brands are launching branded Facebook and YouTube pages, albeit with modifications such as removing comments to avoid regulatory issues.)

But I’ve seen this story before, and it doesn’t end well for brands. Remember AOL keywords? In the late 1990s and early 2000s, it seemed like every brand was promoting its AOL keyword rather than its own URL. How about MySpace?  Today, it’s Facebook pages and Twitter hashtags. Tomorrow it will besomething else.

The risks of relying on other people’s platforms are many. As I experienced, you can be shut down, with little recourse. Even if not, you’re  investing in building content on someone else’s platform that doesn’t benefit your owned properties (for example, by increasing your inbound links and search engine rank). Then there’s the bait-and-switch, whereby platforms tweak their original offering to the point where brands find themselves increasingly paying for what was originally free exposure. Perhaps most importantly, yesterday’s hot social network is today’s viral joke; all that investment is wasted if users turn elsewhere, and history suggests they will—while websites endure.

Spokes are fine, as long as there’s a hub

Social media should drive traffic to your website—not usurp it—as shown in this hub and spoke model.

Unfortunately, I haven’t been entirely heeding my own advice. At the time my Twitter account was suspended, I had let my personal blog lag. I wanted to tell the world about the incident, and see who could help. But I had few blog readers who would listen.

Fortunately, I still had Facebook and email. So, after using them to track down a Twitter contact, and submitting a formal appeal through Twitter online, my account was eventually reinstated—albeit with little explanation. (It probably helped that they accused me of impersonation, but the domain name of my personal email address, simonsmith.ca, is the same as my Twitter username, @simonsmith.)

The experience reinforced to me the value of the hub and spoke digital marketing model. Other people’s platforms—the spokes—can certainly be useful in achieving your marketing objectives. But it’s critical to diversify—a wheel with two spokes will collapse—and to develop a strong hub to which the spokes drive traffic.

And never rely on just one platform. Because one day, you could be kicked off.

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Mobile ownership in different demographics (and its impact on pharma marketing)

I recently published my first official POV whitepaper, “Mobile ownership in different demographics,” on the Klick Health blog. The publication grew from some research I did to support a mobile strategy for a pharmaceutical client. While the POV should be of interest to pharmaceutical brand managers, it should also be of interest to anyone working in digital marketing or curious about digital trends in general.

Some pharmaceutical brand managers are skeptical about mobile adoption amongst patients indicated for their treatments. Sometimes, this is quite justified (for example, research suggests that people with type 2 diabetes are far less likely to own mobile devices, including smartphones). Sometimes, it can reflect a general bias about older demographics—groups more likely to have conditions that require pharmaceutical intervention, but often thought to be less digitally survey.

Turns out that’s not entirely true. While older demographics were initially slower to adopt smartphones, they are now adopting them faster than younger demographics. And for tablets, older demographics are adopting them far more rapidly than younger demographics; tablets could soon have greater penetration in older demographics than younger.

Check out the POV and let me know what you think.

 

 

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Responsive design from the trenches

(Cross-posted from the Klick Health blog.)

Talk about creating a new or mobile-optimized website these days, and you can’t avoid the topic of responsive design. But despite being a fairly established subject of conversation (see our post from a year ago), it’s still quite misunderstood—and even contentious. So I figured a quick dispatch from the trenches was in order.

But first, a recap. With responsive design, a single website can display differently across devices using a single codebase and rules that alter design and layout for different resolutions. For example (albeit a very simple one), these rules can specify that at a desktop resolution, supplementary information appears in a sidebar, while at a smartphone resolution it appears beneath primary information. This approach differs from creating a mobile-specific site in that you don’t need a separate codebase for each supported device type.

At a high level, it works as follows:

  • Wireframe and design interfaces for different devices/resolutions (usually common desktop, tablet and mobile resolutions)
  • Develop a single site with a single codebase to serve the appropriate layout and design for each device/resolution
  • Use rules (such as CSS media queries) to show the appropriate layout and design for the appropriate device

See for yourself

At this point, some examples would probably help. To see these examples in action, you can either (a) look at them in your browser (be sure it’s a modern browser, like the latest version of Internet Explorer, Chrome, Safari, Firefox, etc.) and resize the browser window from full-width to smaller width until you see the design change or (b) look at them on your desktop computer and then on an iPhone or Android handset. Take a look:

  • Klick’s website: Since you’re here, give it a shot!
  • Velcade RN (https://www.velcade-rn.com): This is a simple responsive site that Klick created for registered nurses.
  • Clear Air Challenge (http://clearairchallenge.com/): This is a more complex responsive site where the design has many “steps” and several layout changes.
  • Earth Hour (http://earthhour.fr/): This is another fairly complex example that incorporates video.
  • Fork CMS (http://www.fork-cms.com/): Another example that demonstrates multiple “steps” for different devices, meaning that it shows a different layout and design for multiple devices, not only desktop and mobile.

Unfortunately, there aren’t yet a lot of pharma examples, but they’re coming—and we’re working on some projects currently that will launch in 2013. We anticipate this to be a key trend over the coming year due to unprecedented growth in mobile device adoption and internet use.

That’s important because the requisite technology (e.g. CSS3) for responsive design is widely supported on mobile browsers. While browser capabilities on the desktop can change slowly, due to the persistency of older versions, most smartphone browsers are modern because (a) smartphones are new and don’t have to contend with the same legacy software issues; (b) the dominant platforms, such as iOS, come with updated browsers with each operating system upgrade; and (c) personal smartphones aren’t locked-down by IT departments.

Advantages and disadvantages

This said, we don’t always recommend responsive design, as it’s not always suitable for a project. When considering responsive design, here are some key pros and cons:

Advantages

  • More cost-effective for the long-term due to maintenance of a single codebase rather than multiple codebases
  • Ensures content available for different devices is always up to date (no need to ensure multiple codebases are updated when changes are required)
  • Can reduce regulatory burden once responsive-design review process is established; it may not be necessary to review every page of different sites for different devices once your regulatory department understands how the design differs for each device, and that the available content will be the same (or where it will differ)
  • Better future-proofing; avoids the need to create specific sites for each new device/resolution (and with the ongoing mobile device wars, and new devices seemingly launching each month, this can be an important consideration)
  • Becoming a best practice and recommended approach (for example, Google explicitly recommends it for mobile search engine optimization)

Disadvantages

  • Generally, not suitable for complex applications, games, or multimedia applications where some more advanced interactions are required; this may change, however, as HTML5 support strengthens
  • Generally, not suitable for a large existing website; converting it to responsive design can be more expensive than creating a mobile-specific site (although the long-term cost-savings may still recommend the responsive approach)

Five criteria for choosing responsive design

So is responsive right for your next project? Typically, we recommend the approach when the following criteria apply:

  • Project is starting from scratch and there is no need to re-code an existing website
  • Required mobile functionality is fairly traditional, not excessively complex and works well with common user interactions (taps, etc.)
  • Client’s internal regulatory group is open to or already accustomed to responsive design, and amenable to reviewing content for different resolutions in a more streamlined fashion that creates efficiencies
  • Will reduce the amount of future maintenance required (such as by reducing the number of codebases that must be maintained)

Do these criteria apply for your next project? Do you have experience with responsive design? Do you foresee any challenges implementing it for future digital marketing? Let us know in the comments.

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Not directly measuring ROI? Time to update the plan

(Cross-posted from the Klick Health blog.)

Let’s be honest: digital marketing has long failed on its promise of accountability.

Sure, you can track the digital part well—impressions, clicks, time on site, conversions and such. But if you’re driving offline transactions, such as filled prescriptions, things get more complicated. Much ROI reporting for offline transactions is indirect, such as through time-based or geographical comparisons. Much less is direct, connecting actual transactions concretely to campaigns.

Recently, some colleagues and I got a deep dive demo of Crossix, which is becoming the pharma industry standard for such direct ROI reporting. This demo showed just how much the promise of digital marketing accountability is now being fulfilled—and how advertisers who fail to demand it will be disadvantaged.

Know what’s working (and what’s not)

In a nutshell, Crossix partners with pharmacies to track prescriptions. It then cross-references prescription data with campaign data to provide ROI* reports—and much, much more. All of this is done in a patented, privacy-protected, HIPAA-compliant way.

For example, imagine you ran display advertising, search engine marketing and lead generation campaigns driving visitors to a drug website. (Crossix can also track offline campaigns, but let’s stick to digital, since that’s our focus.) With your campaigns appropriately tagged, Crossix could report which channels, placements and even creative resulted in the most prescriptions.

Importantly, it could also report which reached the wrong audiences, to help you optimize targeting. For example, Crossix can report which placements reach people already prescribed your drug or unlikely to be take it because they usually take generics.

Beyond coupons and savings cards

Sure, coupons and savings cards have long helped connect advertising campaigns with transactions. (Marketers have done stuff like that since the early 1900s.) But only if people download or register, then redeem. Companies like Crossix can—by working with partners who have pools of audience data—connect transactions with ad impressions, whether or not they result in a download or registration and redemption.

It’s like knowing which customers looked at a billboard and then bought your product.

And while Crossix is certainly a leader, it’s not alone. For example, Facebook is working with Datalogix to track offline sales driven by Facebook ads, and one of Datalogix’s data sources is CVS. No doubt big ad players like Yahoo! and Google will follow suit.

The bottom line is, well, the bottom line. There are increasingly fewer excuses for not knowing exactly how well your digital marketing campaigns are performing.

* I acknowledge that this still wouldn’t be a complete ROI picture since it doesn’t capture all revenue and expenses, but it makes more comprehensive ROI calculations much more accurate.

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Innovations: Can Treato make social listening safe (and useful) for pharma?

(Cross-posted from the Klick Health blog.)

The benefits of social media listening often don’t outweigh the risks. It can sometimes mean nothing more than word clouds that quantify brand mentions. What we really want is insight. Not just data.

Enter Treato. An Israeli startup that’s about a year old, it aggregates health-related social media conversations and analyzes them with natural language algorithms to reveal “the voice of the patient.” The result is comprehensive market insight that Treato says achieves 80% accuracy compared to other methodologies, but with much greater scale.

“Everyone tries to listen,” says Michal Tamir, Treato’s VP Marketing and Business Development. “We actually understand.”

Eavesdropping on a billion conversations

I came across Treato recently while reading about new digital health startups and accelerators. There’s been a recent surge of disruptive innovation in digital health, unleashed in part by adoption of mobile platforms and apps, as well by healthcare inefficiencies that beg for novel solutions. Intrigued, our analytics team contacted the company for a demo.

Visit Treato’s free public site and you can immediately grasp the potential. Search for a pharmaceutical brand and you get instant results showing how patients rate it relative to competitors, what they’re taking it for, and what side effects they’re experiencing. For more qualitative insights, you can also see anonymized patient quotes that Treato analyzed to generate your report.

Treato gleans all of this from unstructured data, having crawled and analyzed more than 1.1 billion posts from over 1,500 websites generated by more than 23,000,000 patients and covering more than 24,000 drugs and conditions.

This differs from sites like PatientsLikeMe that use a more structured approach. Whereas PatientsLikeMe is similar to a facilitated focus group, Treato is like eavesdropping on patients talking other over coffee. The former approach may yield answers to specific questions, but the latter reveals a level of openness and honesty that more structured methods might inhibit. It’s also far more scalable; no registration is needed for participation, and everything people say publicly online can be indexed.

Patient intelligence without adverse event reporting?

In addition to its free service, Treato offers a professional service called Treato Pharma that’s available to pharmaceutical companies and their marketing agencies. If the free version is akin to a heart rate monitor for your brand, the paid version is a tricorder.

After you configure Treato Pharma for your brand and its competitors, you can navigate through tabs covering “Patient Insights,” “Competitive Analysis,” “Drug Switching” and “Top Websites.” Here you can uncover what patients are saying about your product, what they’re saying about competitive products, what’s driving them to switch products, and which websites are most likely to host conversations about your product (which you can use to inform media campaigns). You also get a dashboard to present key insights from each area on a single page.

To understand just how powerful this can be, consider Treato Pharma’s ability to report product effectiveness by condition. If your product has multiple indications, Treato Pharma can show how patient sentiment differs for each.

Competitive reports are equally useful. In our demo, Tamir showed how Treato Pharma allows you to see what topics people discuss more or less with your product than with your competition. For example, if patients talk more about “weight gain” with a competitor’s product, that might trigger you to revise your market positioning or even prompt research that could support a new product claim.

Importantly, you can analyze how the patient conversation changes over time. This lets you gauge the effectiveness of marketing campaigns; by comparing patient awareness or sentiment before and after a campaign, you can understand its impact and ROI.

Powerful, yes. But what about implications for adverse event reporting? “That’s the number one question we get,” says Tamir. But Treato has a legal opinion, she says, that the aggregate and anonymized data they use doesn’t contain the patient-specific information required by the FDA for a reportable adverse event. Treato can also remove information as needed, she says, to address any regulatory concerns.

Next up: Tapping Facebook’s massive user base

While the current versions of Treato and Treato Pharma are impressive, improvements are already planned that should make them even more so. This includes the ability to export data (although not yet to Excel, to the disappointment of my colleagues in our analytics department), as well as expansion to indexing Facebook data. The latter reflects a trend, says Tamir, in which people are increasingly discussing health issues on Facebook.

Treato has also experimented with Twitter, but they claim it offered little value. “Ninety nine percent of brand mentions there are spam,” says Tamir. Also, she says, the 140-character limitation inhibits deep insight.

Overall, Treato Pharma seems like a powerful tool for pharma marketing, and one that I hope to test further in the next few months. But as with so much else in digital health, a good marketing product might not be enough to attract users. We’ll be watching closely to see how Treato goes down with regulatory and legal.

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What Apple can teach you about benchmarking success

(Cross-posted from the Klick health blog.)

With Apple’s new iPhone announced, one reaction is predictable: critics will benchmark the iPhone against competitors and scoff at its inferior numbers—higher price, slower processor, less RAM. Given Apple’s history, here’s another prediction: iPhone fans won’t care, and Apple will sell several million units in days.

Despite such potential for misleading conclusions, benchmarking is essential to contextualize performance. So it’s inevitable that when presenting analytics data to clients, we must answer the question: “Are these good numbers or bad?”

Unfortunately, the answer isn’t always simple. Like the iPhone’s detractors, it’s easy for us digital marketers to focus on the wrong metrics and lose sight of the big picture. And so, in the spirit of iPhone announcement season, here are some benchmarking tips to avoid that fate.

Focus on meaningful metrics

What’s the most meaningful metric for evaluating an iPhone’s performance?

Ultimately, it’s not processor speed or storage capacity. It’s units sold, which is an indication of the product’s fit with its target market, and Apple’s success at everything else that makes a product successful—from marketing to customer support.

Obvious, maybe. But it’s easy to obsess over superficial, inconsequential or excessively granular metrics at the expense of overall success. This is because what’s easiest to quantify unduly influences what gets measured, and what’s easiest to analyze unduly influences what gets optimized.

For example, take click-through rates. They can certainly indicate an advertising campaign’s success. But is a higher than average click-through rate always good and a lower bad?

Truth is, it depends. If your goal is converting clicks into, say, registrations for an email newsletter, you may accept a lower click-through rate if it means higher quality registrants. More meaningful metrics than click-through rate might therefore include conversion rate or cost per conversion. But these are harder to measure, analyze and benchmark, since offers, calls to action, landing page designs and media costs can vary substantially.

Ease of benchmarking, however, shouldn’t dictate what gets benchmarked. Don’t lose sight of the forest for the trees.

Choose the right comparisons

Once you’ve identified meaningful metrics, your next step is choosing comparisons.

Apple is a master of shaping this conversation. Rather than comparing the speed of itsprocessors to that of its competitors, for example, Apple highlights performance for tasks that users care about, such as the time it takes to render graphics. It also emphasizes improved performance of new products versus old, to demonstrate concrete improvements to existing customers and justify upgrades.

These are benchmarks that drive Apple’s business. What about for digital marketing? In my experience, digital marketers emphasize cross-industry averages (for example, the 0.09% click-through rate average for display ads) and sometimes intra-industry averages (for example, prospects who visit a branded pharma website are on average 8.9% more likely to start the treatment).

These aren’t necessarily the most useful benchmarks. But they’re the most available. What’s less common, but often better, is benchmarking against market leaders within your therapeutic category, and—like Apple—against your own past performance.

For example, TGaS Advisors aggregate, anonymize and make available data on the performance of pharmaceutical digital marketing, including peer-to-peer comparisons. For historical comparisons, most analytics platforms (including Google’s free tools like Analytics andTrends) allow past performance benchmarking.

Of course, better benchmarking alone won’t help you achieve Apple-level success. But at the very least, you’ll have a more meaningful understanding of your digital marketing’s efficacy, higher-impact targets for optimization—and better rebuttals to your detractors.

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Why this digital pill is a big deal

These ingestible sensors (green) from Proteus Digital Health relay information to a patch which in turn relays information to a smart device. The sensor recently received FDA approval.

A few weeks ago, a friend and I were discussing the problem of drug compliance. Deeply involved in the drug world, he noted that it’s a great problem from a business perspective because everyone wants to solve it: patients get and stay healthier if they’re compliant with a drug regimen (think, for example, about people who don’t complete a full course of antibiotics); payers avoid expenses related to drug non-compliance (keeping with antibiotics, think about repeat infections and antibiotic resistance); and drug companies simply make more money by selling the appropriate number of pills prescribed by doctors.

But how to solve it? Many have tried—including me, with various digital compliance tools developed for pharmaceutical companies when working on their marketing. My friend and I had brainstormed some other ideas. But truth is, human nature, logistics and pricing preclude most of them from working. For example, how do you design a compliance solution that works for people regardless of their age or the type of drug they’re taking? How many people over 85 would be comfortable with a digital compliance solution? Would confusion over its use cause more problems than it solves, thereby worsening compliance or producing invalid compliance data?

That’s why the FDA’s approval of an ingestible sensor by Proteus Digital Health is such a big deal. You swallow it and it relays information that you or caregivers can track. This includes information about drug compliance, as well as other information such as your heart rate. So people taking drugs need not do anything different—the pills themselves can include a Proteus sensor. And apart from improving compliance, these “digital medicines” can also report information that aids understanding of drug effectiveness.

For me, the existence of this product, and its approval by the FDA, heralds a new stage in the sensor revolution that’s underway. Whereas products such as FitBit and Nike+ FuelBand track biometrics with external sensors, Proteus’ technology tracks biometrics from the inside—and, importantly, without the need for surgery or pain. And since they can be combined with a range of treatments, including generic drugs, it could transform medicine. For example: every pill can now be a smart pill; drug dosages can be personalized based on individual responses; generic drugs can likely be combined with digital technology to create new, patentable combinations.

And, of course, compliance problems could quickly be identified and addressed.

Image credit: Proteus Digital Health

 

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What if Facebook were crowdfunded?

Peter Thiel made a $500,000 investment in Facebook in 2004, giving him shares now worth over $1.5 billion. What if the crowd had made that investment instead?

Crowdfunding is hot. So hot that the US government is on board, allowing people to crowdfund for equity. Other countries are jumping on the bandwagon as well. That’s opened an industry of everything from new crowdfunding sites to crowdfunding-focused due diligence firms. And with companies now able to raise millions on sites like Kickstarter, clearly it’s viable for entrepreneurs.

But there are no practical examples, that I know, of what might happen if a company were crowdfunded for equity, hit the big time, and returned huge money to investors. How much might those investors see? How might that money work its way through the economy? How does that compare to what happens with angel and venture capital investors?

So I thought about Facebook. In August 2004, Facebook raised its first outside investment from Peter Thiel. Thiel’s investment was $500,000 and earned him 10.2% of Facebook’s shares at the time. Today, he reportedly has 2.5% of Facebook. As I write, Facebook is worth $62 billion. That means Thiel’s share is about $1.5 billion ($1,550,000,000, to be exact). His ROI was 309,900%.

What if, instead of raising money from Thiel, Facebook has raised that money through crowdfunding for equity? I’ve seen reports that the average contribution on a Kickstarter project is around $71. I imagine the number varies depending on factors like the project, the audience and so forth. It also seems to vary by crowdfunding site. But let’s stick with that number for argument’s sake.

With an average contribution of $71, Facebook would have needed about 7,043 contributions to reach its $500,000 target. That seems like a high number, but by the end of 2004 Facebook had about 1.5 million users, so it amounts to less than half a percent of its user base. So I think it’s possible it could have raised the money from users.

If those users had crowdfunded for equity, where would they be today? If my math serves correctly, the average investor would now have shares worth $220,100. The median annual household income in the US in 2006 was $50,233. So the average contributor and their family could take about 4.4 years off working if they’d like.

So is this better than any one investor, like Thiel, making a killing? While I’m pro-crowdfunding, and in favor of crowdfunding for equity, I think it remains to be seen how this will play out. On the one hand, in this example, the money would be more widely distributed through the economy, including geographically. On the other, this isn’t enough money for any individual investor to retire on, nor is it enough for them to invest large sums of money in massively high-risk, game-changing ideas like mining asteroids.

Ultimately, I think there will be a balance. Some initiatives will rely only on crowdfunding. Others will rely on crowdfunding and, likely later, larger rounds of financing from institutional investors. And in the case of massively high-risk, capital-intensive, game-changing ideas like space tourism, mining asteroids and building electric sportscars, we’ll probably still need the Peter Thiel’s of the world.

(Note: There’s a good chance some of my stats and math are off. I’d also like to have more information about how the money earned by individual contributors might trickle through the economy, versus all the money going to Thiel. Please leave  any feedback in the comments, and I’ll update the post accordingly.)

Image credit: David Orban/Wikimedia Commons

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How being healthy got me denied life insurance—and how I fought back to get preferred rates

Exercise can be good for your health but sometimes bad for your life insurance application

Was I dying?

It was about a month after my 35th birthday. I had applied for life insurance and undergone the requisite tests. For previous applications, the results came back quick. And they were typically good—I was fortunate to earn a “super preferred” status, probably owing to decent genes combined with obsessive health habits. And, of course, mild hypochondria.

This time, I heard nothing for weeks. So I nagged my insurance broker, who in turn nagged the underwriter. First we learned there was a delay because they asked the lab for additional tests. Uh oh. And then, late afternoon on a Friday, I received an email from my broker with this ominous line: “Can you please call my cell at your earliest convenience about your insurance application.”

I called. Immediately. And I learned that my application had been declined. With no immediate explanation—they would be sending the information to my doctor after I signed a release. Given that even smokers and people with chronic illnesses can get life insurance, albeit at higher rates, I assumed the worst.

And so began a worrying, frustrating but ultimately educational and empowering struggle to understand what happened—and to fight back.

From panic to fear to uncertainty

My initial panic was calmed somewhat by my insurance broker. It was the weekend, so no further information was forthcoming from the underwriter. But, after nagging him further, he assured me that, if it were something really serious, they would send information to my doctor immediately, without first seeking a release from me.

And so I waited to sign the release and see my doctor. All the while, hypochondriac that I am, worrying how long I had to live. (Which resulted in lots of soul-searching, journal writing and clarification about what I felt was important in life. But more on that some other time.)

A few weeks later, I was in my doctor’s office reviewing the information forwarded from the underwriter. I waited for the bad news. But the only thing my doctor could see was that I had two slightly elevated liver enzymes, aspartate transaminase (AST) and alanine transaminase (ALT), as well as antibodies to hepatitis A. My AST levels were 39, compared to the lab’s upper range of 33 for normal. My ALT levels were 71, compared to an upper range of 45 for normal.

But, my doctor assured me, these were not particularly concerning; someone with liver damage from hepatitis would have numbers in the high hundreds. And, I explained, I had antibodies to hepatitis A because I had been vaccinated against it prior to traveling to Central America a few years ago—so that was actually good news, because it meant the vaccine worked. (Although I should have also had antibodies to hepatitis B, as I was vaccinated for that as well, but did not. That meant I needed a booster.)

So what was going on?

Nonspecific indicator, wrong conclusion

To gain some assurance that everything was okay, and to hopefully get life insurance at least at standard if not preferred rates, my doctor ordered some further tests, and I did some further research. And good thing: turns out, the underwriter likely jumped to some wrong conclusions.

I began with the requisite internet research and discovered that AST and ALT are fairly nonspecific indicators. They’re not like, say, high cholesterol or blood glucose, both of which typically indicate a medical condition of concern. Rather, they can be elevated for many reasons. Like having an infection. Or taking a Tylenol. Or doing strenuous exercise—and, particularly, lifting weights. (The enzymes are not confined to the liver. They are also present in muscle tissue, among other things.)

Lifting weights? Why, yes. Research (like this study reported in the British Journal of Clinical Pharmacology) shows that “liver” enzymes (many of which, remember, are also found outside the liver) can be elevated for at least seven days following strenuous exercise, peaking at about 36 hours.

For the past few months, I’ve been doing high-intensity weightlifting (“Occam’s Protocol” from Timothy Ferriss’s 4-Hour Body) involving high weights, low repetitions, and good time between sessions to allow healing. It effectively builds muscle mass. And, given time limitations that come from having a full-time job and a family, it’s a good fit for my lifestyle.

However, it may also be a great recipe for increasing enzymes that insurance underwriters consider a potential marker of disease. And that might explain my insurance application’s decline: I had the initial blood test 48 hours after a high-intensity weightlifting session.

Arguing my case—and winning

So my doctor ordered another blood test for liver enzymes specifically. This time was 72 hours after my most recent weightlifting session. The results were better: My AST score was within range at 32, and my ALT was significantly lower, at 56, but still not quite within range. Just to be safe, my doctor ordered an abdominal ultrasound, which came back clear.

And so, along with my doctor’s submission, I submitted a note to the underwriter via my broker, explaining that I believed:

  1. They were initially concerned because my AST and ALT scores were elevated
  2. This caused them to order a hepatitis screen, which showed antibodies for hepatitis
  3. This caused them to decline my application
  4. However, my AST and ALT were likely elevated because I was being healthy and exercising
  5. And my hepatitis A antibodies were almost certainly due to a vaccination, which I did to avoid getting infected

Along with the note, I submitted the research linked above.

A few days later, I received an email from my broker stating the following: “I am very pleased to inform you that your application has been approved at preferred rates. Thank you for your patience during this process and I must say that your diligent actions made the issues much easier to deal with.”

Phew. A long, scary battle, but worth it. I can’t say it makes me any less of a hypochondriac. But it certainly makes me even more inclined to be an active participant in understanding and managing my health.

Image credit: Mike Baird

Note: For anyone interested in speaking with my broker, perhaps because you’ve gone through or are going through something similar, his name is Robert Barkin and he works with Creative Planning Financial Group. You can find his contact information here.

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