Posts Tagged ‘marketing’

01
Mar

Creativity Without Conversion Equals Zero

Written by Rand Schulman. Posted in Analytics

conversion funnel strategiesA few months ago I had the opportunity to lecture in the content engineering class at the University of the Pacific (UOP), where I’m an executive-in-residence for digital marketing and media and where I have helped design the curriculum. For the last few years, I lecture every semester on the newest technology-drivers

What a difference a few years make and I am pleased to say that change is afoot at the university and across the U.S., as schools are now building programs geared to meet the critical requirements of business in some of the most sought-after areas of marketing: social media, content marketing, and content analytics, where clearly an imbalance exists between skills taught in classrooms and the skills sought in the marketplace. A few years ago many of the students questioned the value of analytics.

This time I presented my case study of a consumer packaged goods (CPG) company using cross-channel analytics, correlating online and retail behavior, utilizing mobile apps, iBeacons, and augmented reality. I’ve written about it here. In class we mapped out just where content was created, who created it, and where measurements are needed. We talked about CPG company goal of increasing lifetime value (LTV), greater customer engagement, and we designed calls to action and discussed and identified conversion events and stages. We talked about metrics for augmented reality, profile information, and purchase history and their relationship and how we look to normalize structured and unstructured information in analytic applications. We discussed what person in the process is responsible for what action. They get it.

Universities and their business partners are indeed looking for ways to leverage their current curriculum toward a higher technological quotient. They see the need to produce graduates with the skills geared for today’s competitive environment. Yet teaching “Internet marketing” and “how to” classes – most often a minor repackaging of traditional marketing – is only a quick fix when instead we need an earth-moving overhaul at a foundational level.

For the last four years, UOP has been creating a program that addresses the needs of graduates, one that leverages the university’s existing curriculum in business, liberal arts, and engineering, but also remains adaptable to train students in new competencies as the market changes dynamically. When we started the program, few students in the liberal arts school studied the scientific method of test and control or used analytic tools. Today, students in the content engineering course build websites and use analytic tools to test and optimize the results. Some sites have thousands of visitors a day. They are learning that creativity without conversion equals zero.

We need to create a stronger culture of measurement in higher education, one that is market-based and rewards innovation. 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.”

U.S. 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 U.S. economy, and university students are questioning whether their high-priced education and gargantuan debt loads – up more than 50 percent after inflation from a dozen years ago – will position them for a college-worthy career.

Says Jim Sterne, chairman of the Digital Analytics Association, “The need for analysts and content engineers who can determine the value of content is so great that our association’s online courses have been steadily sold out since inception in 2006. When times are good, companies invest in tools and systems.”

The market needs well-trained content marketers who can create compelling content and measure and optimize that content using new analytics, predictive modeling, business intelligence (BI), marketing, and content management tools.

Marketing students should be given rigorous, cross-disciplinary training in writing, analytics, and technology; engineering students should be taught to create content; and English, journalism, and communications students should be taught about optimizing content for business value.

“I’m pioneering content engineering in our English department focusing on teaching the latest tools of analysis, analytics, and optimization alongside traditional writing and marketing techniques,” says Dr. Eric Sonstroem, the UOP English department chair. “I’m determined that my students really understand how content works on the Web, how it can be tested and measured, and how you can act on the data you get back.”

While classroom teaching is critical, UOP is also in the planning stage of a “hands on” content lab for its new campus in downtown San Francisco, opened last month near Twitter, Adobe, and in the city’s start-up SoMa district. It is envisioned that the lab will create, utilize and test software applications, conduct research, and educate students on content creation and analytic applications, and that students will intern within the tech community headquartered in the area.

UOP is certainly not the only institution of higher learning to address the data-driven marketplace needs, but the one I’m most familiar with, and other schools are today launching their own programs. Innovation is part of the U.S. DNA, and has been for centuries. Our institutions of higher education have been moving at a glacial pace but it’s beginning to thaw as the heat of market demand for digital sophisticates is “melting” the slow rate of change in higher education. We need to turn up the heat.

18
Apr

2014: The Year Marketing Automation Gets the Recognition It Deserves

Written by Andrew Edwards. Posted in Marketing Automation

A recent article in VentureBeat said that marketing automation tools had only a 3 percent penetration rate at non-tech companies. Meanwhile, marketers are clamoring for ways to act upon data.

More or less, the weakest link in the chain of digital analytics has been the “make necessary changes” part. It’s now been several years since marketers began to understand that having the information alone really didn’t help the business. Recommendations became important. And after recommendations, then action.

Action is messy. It hasn’t had much to do, until recently, with automation. It required getting marketers, developers, creatives and business owners to agree on what changes were needed based on the data. And then the often too-laborious process of actually implementing the changes and trying to tell if there was a meaningful difference in the before and after states. Too often these efforts fell apart in partisan bickering between teams and refusal of many to take risks.

When we talk about marketing automation today, we are referring to SaaS offerings like Eloqua, Hubspot, Leadsius, Act-on and others that build a form of call-and-response matrix into marketing efforts. The easiest way to understand this is to compare it to what used to happen if you were reading a comic book when you were a kid, and saw an ad to “send away” for something either free or cheap. You would do that, and then you’d get more offers from the same company in the mail, as they hoped you’d soon spend more.

Much more dimensional and sophisticated versions of this are being played out by marketing automation tools, and according the the VentureBeat article, there’s plenty of room to grow.

A recent example of how one company is addressing a call for marketing automation is Tealium’s AudienceStream. Tealium already has a key foothold in the tag management industry, and that puts it at an important juncture of data collection. AudienceStream links the collected data from many sources (legacy of Tealium’s TMS) and allows the marketer to quickly set rules, thresholds and triggers that communicate via new APIs to marketing-action software already in the market. In other words, an AudienceStream powers an Eloqua. Once the rules are set, AudienceStream can communicate with a tool like Eloqua and help determine what message goes out to what user without continuing human intervention.

We’re not at the stage yet where entire site pages and app screens are being re-made on the spot based on very fresh data. We are at a stage where certain updatable modules on sites, and certain marketing messages can be automated and substituted based on data. The reason why this market sector has such growth potential is that it actually fixes a real problem.

While we’ve had lots of time to gnaw on old chestnuts like page views and unique visitors, we’ve hardly gotten to a point where we can say we’ve got organized, incremental methods that improve marketing velocity. And we know that most of the friction comes from friction between different teams with different agendas.

Marketing automation has no agenda except to respond to data and seek a return on marketing content. It frees up humans to do more strategic work. It may have only a small percentage of the market today, but as marketers get more and more familiar with successes based on these tools, that percentage is likely to begin growing rapidly in the near future.

Think of 2014 as the year when marketing automation finally got some of the recognition it deserves.

 

28
Oct

Convergence Analytics Now: 3 Ways This New Market Changes Everything

Written by Andrew Edwards. Posted in Convergence Analytics

Convergence analytics has been called “multi-channel analytics,” “big data visualization,” “business intelligence for marketers,” “real-time analytics,” “enterprise analytics,” and very recently even “omni-channel analytics.” It’s a safe bet that a hundred different vendors are fielding a tool (or suite of tools) that they will claim, in some way, shape, or form, can “measure data from any source” and “present it to the [target audience] in a visual, interactive interface.”

The most remarkable aspect of the market right now is its relative incoherence as compared to more mature markets like “digital analytics” or “direct marketing.” As the market begins to crystallize, both vendors and practitioners will need a core set of definitions around which to formulate requirements and offerings; hence the need for an overarching concept like convergence analytics.

The convergence analytics market encompasses all of these buzz factors and more. It represents the future of all digital analytics from this day forward. As has been said about other rapidly growing industries, “it’s still early days,” but we’re seeing an explosive growth in offerings, and if you’re not already dealing with CA today, expect that you’ll need to do that in the not-very-distant future.

Convergence analytics, from a technology-centric viewpoint, represents an emerging market that concentrates on the confluence of digital analytics, big data, robust algorithms, and advanced visual presentation. From a marketing standpoint, it’s about the “un-siloing” of data from a variety of places within the organization. Start with the combination of desktop, mobile, and social; then go from there.

How It Changes Everything

1. Web, social, and mobile: not cutting it anymore. When we ran our first CA survey, about half of the respondents said they defined “multi-channel” to include the above three disciplines. However, the other half said it included those plus more channels. The number of organizations needing to combine data from more than just these three sources is growing rapidly. “Web analytics” is already retired as a term in and of itself. “Digital analytics” seems fairly coterminous with the above three areas of interest. But just those three don’t cut it anymore. Organizations now want to look at those plus demographics, campaign data, ad-buy data, e-commerce data, in-store data, call-center data, CRM data, unformatted data from a variety of sources, and so-called “big data,” which is a buzzy way of saying “everything that can be tracked.”

2. Connectors, connectors, connectors. As in real estate, in which “location” completes the three most important aspects of a property, connectors may prove to be the most important asset a convergence analytics vendor possesses. Much of the technology behind connectors (and the rest of CA) has been around for some time, yet now it is put together in new ways (the Wright brothers did this with bicycles, boats, and kites; we ended up calling it an airplane). Now existing technologies are coming together to form convergence analytics.

But the most important unit of CA vendor technology – the one they build their businesses around – are the connectors they build to a variety of data sources. If they don’t work properly, nothing else in the analytics process works either.

In order to master convergence analytics, many practitioners will have to understand some previously data-scientist-only terminology like “ETL” (extract, transform, load) – which is what connectors really do. If you thought marketers had already needed to go a long way toward technology and data, it’s only just begun.

Getting to know the details behind how data integration actually deploys will change the workday of every marketer from now on. And if you’re not doing so already, get ready in the near future to ask your current or prospective analytics vendor about how many channels they connect to – and what they will do if you have a new data source for which they don’t already have a connector.

3. Convergence analytics ownership in flux. Who will own convergence analytics? It’s destined to become the clearing house for all marketing data (and much that isn’t related to marketing); but it represents a much higher technology bar than any breed of tracking tools that have gone before. Will marketers really run convergence analytics the way they have run digital analytics? Will they want to? Will the CMO be responsible for a vendor solution that crosses not just marketing disciplines but also IT, sales, operations, and perhaps even finance? Will she want to? Will newly minted data scientists rule the convergence analytics roost?

All of this is unsettled and up in the air. But it’s going to land soon – probably pretty near your desk. And when CA becomes the norm (as it soon shall), get ready for some major organizational changes. Whomsoever can claim to understand this new type of offering best and most comprehensively will likely carve out a new and very desirable niche for themselves within the organization.

The insights available from the control of an unprecedented amount of previously siloed data is going to be – unprecedented! And the winning organization will be the one that gets out ahead of these major transformations with the right people in the right place at the right time.

 

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