Can Analytics Help Save Obamacare?

Written by Andrew Edwards. Posted in Analytics

The crash-on-takeoff of the Affordable Care Act website is already one of the most notorious flameouts in the history of digital enterprise.

Putting any merits or demerits of the ACA aside, we must grapple with the fact that as I’m writing this (one month after its launch), the digital platform upon which the ACA is perhaps too heavily reliant has been a near-total failure.

Many will be tempted to suggest this is because it’s a government effort and that government never gets anything right; it’s a sink of waste and foolishness and this proves how it ought to have been left to “the private sector” to construct and manage. But this is not necessarily the case, not least because the act was largely “privatized” in the first place, to placate a conservative congress.

Would the ACA be a much simpler proposition in a single-payer environment? No doubt. One of the the key challenges seems to be the coordination of numerous private databases in the service of what is essentially an e-commerce site. It really is not much different than a site that sells shoes, with special discounts for those who qualify. On the ACA site, you “shop for insurance.” Perhaps they ought to have given the whole project over to Amazon and had Amazon put a “healthcare” tab on the home page.

The difficulty with the the ACA web sites, apparently, is that many who seek to enroll cannot get past the authentication page, and cannot therefore apply for insurance.

To address the challenge, the White House has promised a “tech surge,” which seems to be taking shape in the form of a cry for help to Silicon Valley. It’s the first thing we’ve heard so far that seems hopeful and we wish them all the best.

Analytics or Continued Failure

The “fixers,” whomever they turn out to be, will need to pay close attention to analytics. At first, it will be all about error messages and fixing infrastructure. But once they get it to perform minimally, it will be, because of its early failure, just that much more important that the site delivers on conversion. Those in charge will need to rapidly identify friction in the system and make it more than a default way of solving a problem.

Why Digital?

We come quickly to the question of whether digital is the right way to have tried to solve the health care morass.

The prevailing wisdom is that digital is the savior; that it cuts friction, that it is swift and simple and creates a permanent solution. However, it is entirely possible that a system of 1-800 numbers and paper applications might have served as well or better than an online solution (of course, they will have needed the same massive database on the back-end, but that is another matter). The ACA may quite unexpectedly prove a watershed in our belief that digital can solve societal problems and instead prove that it really cannot–at least not without much, much more care and devotion that would have been required by another (non-digital) system.

Analytics is What Makes Digital Different

But digital compensates in many ways that non-digital cannot hope to compete.

The way that digital triumphs comes down to its built-in accountability. Let’s not try in this brief space to describe the KPIs and reporting dashboards that the ACA site operators must put in place immediately to understand user behavior and make the site as efficient as, say, Amazon.

Let’s say instead that without the ability to:

  • understand user behavior and spot trouble and fix it quickly,
  • continually test and improve using feedback and algorithms,
  • define desired outcomes and build in measurement and optimization;

…then digital really becomes just another choice among choices, and who can say if it was the best?

We suspect that this method was not followed in the development of the current infrastructure, and the results are a very poor showing indeed.

The only way to prove that the website for the ACA not only works, but works well–and works better than another system might have worked–is to apply robust site analytics, take careful note of what the data is saying, adjust accordingly and thereby demonstrate that digital is not just an obvious choice, but an essential component of the program’s success.


Building a Culture of Measurement

Written by Rand Schulman. Posted in Analytics, Convergence Analytics

convergenceI was sitting in my office the other morning, sipping a cup of coffee, when the phone rang. It was the chief executive (CEO) of a successful enterprise software company based in the Valley.

“Rand, we’re looking for a head of marketing to build a demand generation machine based on a scientific approach. Know anyone?” I thought, good question, but is he really looking for someone to head marketing, or is it some other role? Today, who is responsible for this activity across enterprise silos of data and new worlds of applied creativity to the various emerging channels, like mobile and social? Do I know anyone? Clearly, this CEO wants to build a company culture of measurement.

In our recent Convergence Analytics 2.0 report, we explore these evolving roles. In the past, this responsibility might have been owned by multiple people across the organization — the head of marketing, chief revenue officer, chief data officer (CDO), chief information offer, chief analytics officer, or other chief.

According to a recent Russell Reynolds article, there’s been a rise in the popularity of the chief digital officer role and last fall, Gartner predicted that 25 percent of organizations will have a CDO by 2015. That’s shaking up the corporate power structure in strange ways for many.

“The chief digital officer will prove to be the most exciting strategic role in the decade ahead,” says Gartner vice president, David Willis. “The chief digital officer plays in the place where the enterprise meets the customer, where the revenue is generated, and the mission accomplished. They’re in charge of digital business strategy.” Is that what we need now?

The role and reach of the CDO seems to be evolving as rapidly as everything else related to the digital, as it’s actually quite hard to find something that isn’t related to digital in some way these days. CDOs are appearing in companies, not as business unit owners, but as hybrid marketing-operating agents of change, seated next to the CEO at the corporate table.

Our CEO is looking to build a culture of measurement, which requires new thinking, as the tools didn’t even exist a few years ago. I told the CEO that it’s difficult to find the right marketing individual, as they need to have both analytic and creative skills to fill his demand. Yet today, those hybrid skill sets barely exist; they’re not being created in universities to address corporate demand for measureable results. Yet without those skills, it is impossible to fulfill the promise of the New Marketing Four Ps, the first “P” being people.

The new marketing leader will know when to hit the marketing gas pedal and how to analyze both program spend and macro shareholder value. They will be expert at driving company-wide KPI models that show when to invest in marketing — and when to pull back. When I was chief marketing officer (CMO) of WebSideStory, we used “magic SaaS” metrics that (then) Omniture CEO Josh James has written about and many follow today. We built a culture of measurement and after our IPO, were acquired by Omniture (now Adobe).

The new marketing leader will know how to create relevant content that converts. Like Innis and Ogilvy, they will be experts in communications and persuasion.

“Our colleagues want marketing professionals who can measure and optimize marketing effectiveness; the demand for those roles is essentially doubling annually,” says Alex Yoder, former CEO of Web Trends and director of The Oregon Association of Independent Colleges and Universities. “The amazing thing is this: despite a slow economy, the supply in these roles is just not there.”

US higher education, long a source of pride and differentiation across the globe, is undergoing a true crisis of value and identity. Pundits wonder whether universities are the next “bubble” of the US economy, while university students question whether their high-priced education and gargantuan debt loads — up 47 percent after inflation from 10 years ago — will position them for a college-worthy career.

Simply put, US universities are not adequately training students to meet the needs of the modern business. An imbalance exists between skills taught in classrooms and the skills sought in the marketplace. This imbalance is only accelerating with the rapid pace of change in technology and product innovation.

The silos at work in academia have also been a serious stumbling block for businesses, as our CEO is recognizing. In recent years, many organizations have revisited their organizational charts to fix the misalignment between marketing, engineering and operations silos.

Recently at SXSW in Austin, I sat on a panel with an ad agency CEO to debate the question, “Is too much math killing creativity?” The crowd leaned heavily toward creative, but when polled, attendees overwhelmingly said, “No.” They agreed that business value needs to be assigned to all creative and that conversions must be tracked through the sales funnel, from the very first level of engagement all the way through to revenue. The emerging paradigm in the news/media industry supports this; many are talking about a future that optimizes both ad spend and editorial content across acquisition channels, in “real-time,” based on economic demand functions.

To address the skills issue, I propose that we create a new major, as some institutions have, that spans existing schools and subjects, yet adds a modern shine to the old school plaque. I have proposed a content engineering degree, which leverages the existing curriculum and talent in business, liberal arts and engineering, yet also remains adaptable, to train students in new competencies as the market changes.

Clearly, we need to create a hybrid university graduate, perhaps a CMO, content engineer or CDO, who understands that the building of a business culture is based on both creativity and measurement, across business and demand channels, all driven by technology.

Our CEO is looking for an employee who has market-based skills. Anthony P. Carnevale, director of The Center on Education and the Workforce at Georgetown University, has called for a fundamental shift in thinking about the way students are educated. He writes, “The old model, where you go to college and then go out and find a job, is largely outmoded. It needs to be replaced with a new model, in which college years are spent explicitly preparing for an occupation.”

Innovation is part of the US DNA and has been for centuries. Today, our institutions of higher education are moving at a glacial pace, not keeping up with corporate demand for high-tech skills. Maybe the high-energy heat of market demand for digital sophisticates can “melt” the slow rate of change in higher education

I need to get back to that CEO with my recommendation. Not sure what I’ll say.


Are Multi-Channel Analytics Vendors Failing the Market?

Written by Andrew Edwards. Posted in Analytics, multi-channel attribution

The short answer is “yes,” at least for now.

The most important factor in a successful multi-channel analytics effort is the proper deployment of complex data collection and analysis in an even more complex digital marketing environment. Nearly every organization is currently grappling with the need to understand the success of multiple properties across multiple channels, while vendors are racing to supply them with the means for doing so.

It sounds like a great combination–a dovetail of supply and demand.

However, it isn’t working today and the challenges to success seem steeper than ever.

Many Vendors, Few Solutions

There is no shortage of multi-channel analytics vendors. In fact, as mentioned in the Convergence Analytics 2.0 report, there are probably too many vendors working in this space. Further, too many are making the same claims without sufficient differentiation.

Meanwhile, some of the top vendors (like Adobe) are now creating complete content optimization suites that provide the ability to create, measure and optimize digital properties within the same cloud-based offering.

All this should mean that marketers have lots of choices; oversupply should be a boon.

Except it isn’t working out that way.


You could say the challenge is related to confusion, but most organizations are not confused about what they need, nor are competing vendor claims getting in the way of deployment.

The main reason for the crisis in analytics today is that the technology is racing ahead of what customers really need and what they can profitably deploy. The gap between vendor capability and customer expertise is widening and may be approaching a stage of critical failure.

We know that many customers continue to struggle with more basic analytics challenges than those suggested by multi-channel, big-data efforts. An enormous and neglected challenge is that of talent deployment (or lack thereof). There’s a premium on technicians, analysts and expertise in multi-channel analytics, in general. Outside of the small vendor communities where experts naturally congregate, there are very few practitioner-experts dealing with digital data and its consequences.

Perhaps the primary barrier to adoption and success is lack of expertise.

Marketers are Not Technologists

Analytics solutions have existed for nearly twenty years, yet today (in some but not all organizations), there remains an only rudimentary understanding of how these tools function and what they deliver.

This suggests a fundamental disconnect between vendors and practitioners.

Vendors are by nature technologists; marketers are not. In a unique marketplace, where technology interacts directly with a constituency that is not technological by nature, the disconnect becomes acute.

Vendors build more and more complexity and “actionability” into their tools because the technology allows them to do so. Too often, though, they neglect to make the tools suitable for deployment by the practitioners to whom they are selling. They are building muscle cars when customers would rather have a fuel-efficient pickup truck.

Marketers look for solutions, but they’re not getting them. Instead, they are offered complex, even arcane toolkits they are asked to navigate and activate as if they were also technologists. Too often, the effort fails. There are too many moving parts, interface and data collection problems; there’s not enough expertise in operation of digital marketing tools or the interpretation of data.

It’s entirely possible that technological capability has begun to outstrip the common ability to comprehend and socialize its ramification.

It’s easy enough to suggest every organization needs to embrace multi-channel analytics and perfect their conversation with their customers based on observable behaviors. But even veteran analytics teams too often “max out” with web analytics; it’s a stretch for them to accommodate even a modest extension like mobile analytics. Add social, CRM, sales and supply-chain, and the most likely scenario is disorganization and dysfunction.

Ground Control to Major Tom

Vendors are floating in low-gravity cyberspace. They can see how technology can help marketers optimize their offerings and to them, it seems it ought to be rather effortless. But the gap between their ability to create technology that can do these things and their ability to create applications marketers can easily use is large and growing.

Meanwhile, marketers are feeling burdened and earthbound. They are struggling with data collection, knowing full well that without good data collection, there is no benefit to analytics. They are struggling with organization, understanding that analytics governance is a dream yet to be achieved. And they’re looking at the sophisticated marketing suites available to them and scratching their heads.

The trend is towards larger and larger disconnects. Marketers are calling out to vendors to come back to earth, to help them solve the basic, rather boring problems of getting the small things right before they try to conquer new worlds. Plain, vanilla web analytics can be hard enough to implement for many marketers. How can vendors expect practitioners to graduate to new analytics challenges before they have seen enough value in tools they’ve been using for years?

Is there a latitude where vendors can meet practitioners and come up with real solutions? Vendors need to come back to earth. Marketers need to make more room for digital expertise in their budgets.

If vendors stay in the stratosphere and marketers remain bogged down, the result is radio silence. We should fully expect multi-channel analytics to fail until the gap between application capability and expertise is narrowed.


Convergence Analytics 3.0

Convergence Analytics 3.0

Written by industry insiders Andrew Edwards and Rand Schulman, Convergence Analytics 3.0 is a Free Guide written for Digital Marketers interested in understanding the most important trends, technologies and practices in analytics today.


About Efectyv Digital

Efectyv Digital is focused on strategy for two distinct markets: digital analytics end-users; and marketing strategy for technology companies.

Click here to learn how how we can help your business grow >