Be Like Mike!

(This is my first installment in a series on sales, sales management, and sales operations.)

Sales can be a tough gig.

I’m talking about the new-business, “hunter” type of sales. The type portrayed in the renowned 1992 film Glengarry Glen Ross. Sales requires a thick skin, confidence, hustle, and the willingness to grind away, prospecting, doing outreach, cold-calling. And, once you’ve identified, connected with, and qualified a prospect, there are the follow-ups, the countless phone calls, e-mails, meetings, and more needed to engage, influence and persuade. Along the way there is a lot of disappointment, false starts, rejection or, even worse, contacts that just go silent and ignore your attempts.

The world has changed since 1992, of course. A lot. The Internet has fundamentally transformed the business world and left its mark on sales as well. But, at the most basic level, the steps in the sales process – identifying, targeting, reaching, connecting with, persuading, and closing new business – are still the same. Sure, we may not cold call as much – thankfully – and marketing plays a much bigger role now (more on this in a later piece) but in the end, it still comes down to the same basic steps. And grit.

This is all the more true when selling for a startup, a weak brand, or disruptive, transformative technology, where you have to educate the prospect, create awareness, reframe the challenge, and nurture the opportunity to close. In these cases one might face a hundred rejections until you finally succeed. As I said at the onset, it’s a tough gig.

So let me tell you about Mike. Mike’s a dog. My dog. He’s average in size, about 45 lbs. He’s cute, in kind of an odd way, but he’s not winning Westminster any time soon. For one, he’s a mutt that was rescued from a pen where he was chained up with a half dozen others, several of which had died. But Mike – though under a year old, scrawny, weighing just 15 pounds, scruffy and mangy – made it. Mike’s a fighter. He’s got grit. Resilience.

Mike’s doing well now, he’s been with my family for over two years and he’s a wonderful companion to my kids and me. I walk him every evening, something we both cherish. I enjoy the quiet time to think and Mike? Well, Mike’s a dog, so who knows. Maybe he really hates walking and just does it for me. Either way, when I come home in the evening and he sees me get the leash, Mike’s ready to go, happy as can be.

During our walk when we turn a bend in the road and come up on a neighboring home, Mike always tenses up. There’s this stump from a dead tree, all rotted out and hollow, where just about every day there is this chipmunk. The stump is about 30 feet from the sidewalk; half the distance is a driveway so once we pass the hedge it’s a clear line of sight. Whenever we get to the hedge Mike slows down and he carefully peers around the shrubs, looking for the chipmunk. When he spots it, I usually let him off the leash and he begins to approach the stump. We have done this dozens of times and at first Mike used to just storm at the chipmunk, causing it to quickly tuck into a nearby hole in the ground and disappear. After a while Mike learned this wasn’t working and he now approaches ever so slowly, creeping while crouched low. Inevitably, the chipmunk senses Mike’s approach and he sprints in a desperate attempt to catch it before the wily rodent can slip into the safety of his hole.

Mike has done this hundreds of times and has never once caught the chipmunk. Not even close, really. He has varied his approach, taken different paths, and tried various angles of approach, all for nigh. But, each time he approaches the challenge anew, undeterred by his previous failures, and ever hopeful that today will be the day. And, eventually, he will succeed.

So what’s my point here? As salespeople – and we’re all salespeople to some degree in life – we can all learn from Mike. Every day is a new start and we should all begin each with the happy eagerness that Mike brings to each and every walk. Show your colleagues, your prospects, – hell, the tollbooth lady, the barista at Starbucks, or the fellow riders on your train – the same enthusiasm as Mike does when he sees that leash in my hand! (Note: sometimes Mike gets so excited he pees a little bit; do not take things to this level!)

And, most importantly, don’t ever give up. Show what you’re made up, try, try again. And then yet again. And, if that that still doesn’t work, then examine your failures, make adjustments, and try anew!

Be like Mike!

Posted in Lead Generation, Sales, Sales Ops | Leave a comment

The Enterprise Strikes Back!

The Enterprise Strikes Back!


Recently, there has been much talk about the declining role of the IT department. In 2012, when Gartner analyst Laura McLellan predicted that CMOs would surpass CIOs in terms of IT spending by 2017, marketers and techies alike shook their heads in disbelief. And promptly went about making the prediction come true.

To be sure, the three years since have been a thrilling and fun ride. But, like every party, this one too must end. While it’s not quite last call yet, companies are feeling the first signs of a hangover and starting to worry about the tab they’ve run up.

Laissez Les Bons Temps Rouler!

For sure, marketers love shiny objects. And, being human, it’s only natural to seek simple solutions to complex problems. And (seemingly) simple solutions are something we’ve seen a lot of lately.

Marketing automation and AdTech – two areas of massive growth recently – have captured a huge amount of investment and corporate spend. The same is true for social media, lead nurturing, and anything to do with data & analytics. And by doing an end-run around those stodgy IT folks and other barriers – avoiding CapX through SaaS-based pricing models, using cloud-based systems and Web solutions to get around infrastructure standards, etc. – marketing has had relatively free reign.

But has all this investment delivered much measurable return? Are campaigns performing far better? Is customer satisfaction rising? Do we know yet what our most profitable customers look like, what triggers their purchases, and how best to reach them? Not yet, says marketing. But we will. Real soon, too.

We just need to get our social measuring platform integrated with our CRM, develop an effective attribution model, get our web analytics data to line up with our paid search, and integrate everything with the wCMS to deliver a personalized web experience. Oh, and then everything needs to be tied back to our eCommerce system, which in turn will need to integrate with the back-office systems to support omni-channel commerce and in-store pickup. But we’re real close now.

The Important Role of Integration

And therein lies the problem: while each of these systems and tools may be exceptional in their respective areas – a small detail we will assume for now – without effective integration along the entire value chain they are of limited value and impossible to assess as a whole. We are left with fragmented silos, just pieces of the puzzle instead of the whole picture.

I recently had lunch with a digital marketing manager at a large hotel company who lamented that each of their portfolio brands had different agency partners, who in turn employed different tools for analytics and tag management. While they were all required to use the same wCMS, as mandated by IT, they were free to choose when it came to analytics, marketing automation, ad targeting, search and a host of other things.

The result was that there was no way to measure performance across the enterprise, much less the ability to track customers across multiple brand sites and the central reservation system to determine which channel, campaign, or series of interactions ultimately led to a booking. Worse yet, since search was not integrated with display media, and each was managed separately by brand, effective attribution was impossible. Individual brands were effectively competing against one another, bidding up keywords, and each department was optimizing for their own KPIs, chasing clicks and traffic without the ability to tie these to actual bookings.

Creating integrated dashboards – critical to actionable insight – was nigh impossible, since the various systems each had their own data formats and structure, and often identified and tracked users differently. Techniques like look-alike modeling were impossible to employ since there was no central CRM data to draw from.

The result was that every department showed impressive performance improvements, but the sum total of what they each lay claim to greatly exceeded the overall increase in business. And, while total bookings did increase, growth was merely in line with the overall industry due to a recovering economy. So, despite millions in investment, their performance was no better than their competitors, and, much like John Wanamaker a hundred years ago, they were still unable to determine which channels and methods were more effective than others.

Enterprise Software as Foundation

If this sounds like a familiar scenario to you, then you’re probably in your 40s, work in IT, and were around to witness the rise of Enterprise Resource Planning or ERP.

Before companies like SAP, Microsoft and Oracle offered integrated ERP systems, other parts of the enterprise – finance, supply chain, operations – were in a similar fragmented state. The only way to integrate one with the other, production planning with supply chain or sales with finance, was to export data from one system, create a report and compare it to a similar report from the other department’s system of record, trying your best to match them up.

ERP systems changed all of this and ushered in a new era of transparency, accountability, and performance within business and in doing so made things like lean manufacturing, just-in-time supply chains, and mass customization possible. Enterprise systems can do the same for advertising, marketing, and eCommerce. By providing the underlying infrastructure, systems of record, and means of integration, enterprise systems are the lynchpin to connecting critical business functions and the convergence of technology, data, and marketing, make them the logical choice to serve as the backbone of the inter-connected enterprise. They are crucial to a successful and rewarding user experience and effective omni-channel commerce, for few things are more detrimental to the customer experience than an order that cannot be fulfilled, is fulfilled incorrectly, or a transaction that times out due to poor integration.

Enterprise solutions enable cross-functional business processes that are the connecting tissue of the enterprise. They also provide the real-time visibility that is crucial to performance. Marketing, like other functional areas including sales or finance, is a means to an end and not a standalone function. As it becomes increasingly sophisticated and technology centric, it will need to be integrated within the broader enterprise IT landscape in order to be truly effective.

Hence, marketing and IT both serve the same master – the business – and the debate around who controls what should not be a competition. Both must operate in unison and function as partners, with marketing providing domain expertise and functional requirements, and IT ensuring effective operations and integration, just like other departments. Anything less would be a step back to the dark days of spreadsheets, printed reports, without visibility or accountability. Which some marketers may soon discover wasn’t all that bad.

Posted in Analytics, Business Intelligence, Digital Media, Enterprise Systems, Interactive Marketing, Internet Technology, Web Analytics | Tagged , , , , , , | Leave a comment

Data Can Guide Us

But We Have To Be Willing To Listen – And Take Action – To Benefit

Unless you’ve been living under a rock – and a pretty big one, at that – you’ve probably caught wind of the massive hype surrounding Big Data these days. Suddenly, the answers to all that ails us seem deceptively close, provided we can aggregate enough data (size DOES matter when it comes to data, it seems) and computing power, similar to Deep Thought, the fictional supercomputer made famous in the Douglas Adams novel The Hitchhiker’s Guide to the Galaxy.

And, as with hype cycles before, business and the investor community are clamoring to make massive investments in anything related to Big Data.

Data and analytics practitioners have long understood the value of data-driven insights. Regardless if marketing and advertising (which happens to be my field of focus), supply chain planning, demand forecasting, credit decisioning, insurance underwriting, fraud detection and prevention, or countless other areas, the collection and analysis of large pools of data have been the key to success for years.

So Why Don’t We Leverage Data More?

There are many day-to-day, more mundane examples where statistical analysis can help identify anomalies or spot outright crime.

A Little Child Shall Lead Them

An example where survey data would have helped.

One good example, from right where I happen to live, is the 2009 Atlanta Publics Schools cheating scandal. For readers unfamiliar, here’s a quick overview: in 2008 an investigative reporter from the Atlanta Journal Constitution noticed that some schools, primarily those within the Atlanta Public Schools system, had made rather impressive improvements in their standardized test performance. Upon closer analysis these gains were found to be not only impressive, but also statistically improbable. And, indeed, further analysis revealed the one of the largest cheating scandals in the history of the United States, with 178 educators from 44 schools suspected of altering tests.

But it took nearly three years for anyone to take note.

So why is quantitative analysis not applied regularly to more areas? At a minimum, it would seem that areas like government contracting, Medicare/Medicaid disbursements, or controlled prescription drugs would seem to be prime candidates for statistical analysis to identify fraud, waste, and abuse. These transactions are conducted electronically and controlled or regulated by the government, making the data easily accessible.

And, as it turns out, all of these areas appear rife with fraud and other abuses, costing the taxpayer as much as $300 billion annually. Moreover, once the data available is analyzed – even at just a very high level – outliers that warrant further review are easy to spot:

While these data points alone may not prove malfeasance, they clearly call for further analysis. One would think that, in these times of fiscal belt-tightening and austerity, citizens and lawmakers alike would demand they be investigated.

Unfortunately, one would be largely wrong.

So Why Don’t We Listen?

Why then, is the data ignored all too often, even in cases where it is readily available and speaks for itself, clearly warranting further investigation? There are several reasons for this, though none very good:

Conflicting Self-Interest

Humans are a predictable bunch and often prone to putting our own interests first. Contractors defrauding the government, pharmacists running pill mills, or doctors ripping off Medicare all share a common pursuit: money. There’s a reason it is said to be the root of all evil. Even the Atlanta schools cheating scandal, which jeopardized the educational success of thousands of children, ultimately came down to bonus payments for teachers and principals.

So, if doctors are willing to break their Hippocratic oath and educators will risk harm to the children in their care for monetary gain, who can we trust? Trust the data.

Willful Ignorance

When misdeeds come to light, the most common defense brought by those accused is that they simply didn’t know it was happening. When that fails, some may admit to having known but insist they were unaware of the damage caused. The leaders at Atlanta Public Schools actually suppressed a report – one they had commissioned and paid for themselves (via tax dollars, mind you) – because the report findings didn’t suit their needs.


This sort of selective hearing – or outright willful ignorance – is commonplace, but should never be an acceptable excuse.

Resistance to Change

It is said that the most dangerous – and expensive – phrase in business is “We’ve always done it this way”. People love stability. They hate – and will resist – change. Especially if it entails effort. And, if sticking to the familiar ways just so happens If it happens to also be personally lucrative – and provide job security and status – even better.

More money for less effort and risk is a powerful incentive.

Insight Without Action = Status Quo

So, while analyzing data and drawing conclusions is valuable, it is not by itself sufficient to bring about needed change. Ultimately, someone has to not only have the gumption to ask the right questions and the analytical skills to draw the right conclusion; they then also need the courage to speak up and call the emperor naked.

Management – and our society – should actively seek to create an environment where employees – or common citizens – feel empowered to express dissent and challenge widely held assumptions, without fear of retribution or backlash. But we should also insist on seeing the data to verify the claims made. And, once validated, we should act. Decisively, and with confidence.

Anything less is little more than a kabuki dance with data.

Posted in Analytics, BI, Big Data, Business Analysis, Business Intelligence, Uncategorized, Web Analytics | Leave a comment


PART 2 – Using Data-Centric Insights to Drive Effective Media Strategy

This is the second white paper in a two-part series exploring how big data is revolutionizing digital marketing. PART 1 – Getting from Data to Actionable Insight explained the data challenge and the promise it offered but with a focus on how to create a data-driven culture that leverages analysis to deliver actionable insights. This second part examines how business can successfully leverage the insights gained from their data-centric analysis to power and optimize media operations and deliver greater ROI.

Why read this paper?

Big data is big business these days. Research firm IDC forecasts that big data services and technology will grow at a 27% compound annual growth rate (CAGR) to $32.4 billion through 2017 – about six times the growth rate of the overall information and communication technology market. And the performance improvements, increased revenue, and operational savings promised by effectively leveraging big data are expected to dwarf that number. As companies scramble to implement big data strategies, marketing has been one business function where the potential benefits of increased efficiency loom particularly large. And much is at stake here. Industry experts like eMarketer and Forrester predict global spending on digital adverting will grow about 15% annually and top $200 billion in the next five years. Achieving even a small increase in efficiency could therefore deliver huge ROI.

But most organizations will require more than tools and technology to succeed. Many lack a data-centric culture and struggle to attract and retain talent with the deep analytical skills needed. And beyond mere talent, companies will need to change operational procedures and structure workflows and procedures to optimize the use of data-driven insights.

Actions Speak Louder Than Words

Abu Bakr, an advisor to the Prophet Mohammed, is said to have observed that action without knowledge is useless but, likewise, knowledge that is not acted upon is futile. Hence, simply knowing who your best customers are without having the ability to find and reach them is of little value to business.

Moreover, the crowded, noisy and hectic world we live in requires advertisers to go to great lengths to be able to break through the clutter and effectively deliver our message where our consumers work, live and play. More often than not, this requires us to deliver our message effectively numerous times, using multiple formats, media and channels in order for it to get delivered, noticed, and make an impact.

For a high-consideration purchase in today’s world it is not unreasonable to expect over a dozen interactions to take place between a brand and a consumer contemplating a purchase. As prospective customers move from awareness to consideration, purchase, and loyalty, there are countless opportunities for marketers to influence their path along the journey to a purchase decision – provided we can reach them at key inflection points. Just knowing who our customers and prospects are is valuable, no doubt. But knowing where they are when, how to reach them, and having the means to effectively do so with a well-timed and targeted message, is the decisive advantage.

Consumers form impressions of brands on the basis of their daily interactions across countless touch points, including advertisements, news reports, social media, and conversations with friends. It can be tempting to think that, unless consumers are actively shopping, much of that exposure is wasted. Research tells us this is not the case though. Occasionally, something triggers the impulse to buy and at this point all those accumulated impressions are crucial in shaping the initial consideration set and determine the sub-set of brands consumers regard at the outset as potential purchasing options.

This research confirms the importance of two distinct aspects: a brands ability to reach consumers when and where it counts across multiple channels, media and touch points; and a brands ability to accurately track and measure which interactions were most effective in converting their interest to actions so that they can invest more into efforts that appear to have the greatest impact. The first aspect is all about targeting, message development and delivery. The second is about data, insightful analysis, and accurate attribution. We will explore both in turn below.

Reach, Channels, Media and Frequency

Today’s marketer works in an infinitely more complex world than his or her counterparts of a generation – or even just a decade – ago. Instead of a simple media mix consisting mainly of print, broadcast and out-of-home media, the modern marketer has to consider channels and media that include online display ads, earned media, mobile applications, e-mail, social, paid search and more. Moreover, none of these exist in a vacuum and research has shown time and again that they are closely interrelated and can offer powerful synergy effects that marketers can tap into and leverage. For instance, targeted display media campaigns that are coordinated with efforts across other channels and media – social media, paid search, or effective PR, for example – deliver measurably better performance than when conducted on their own.

It is therefore important that brands effectively coordinate and track integrated campaigns across multiple channels and media, thereby creating as many brand interactions as possible along the path to purchase. And most marketers are able to fulfill this requirement and reach their target audience to deliver their brand message in a multitude of ways, either by internal resources or with the help of outside agency partners. But reach is just one part of an effective campaign. Coordination, timing, analysis, and effective attribution are all crucial components needed to truly optimize cross-channel media performance.

Unfortunately, too many marketers, including many large global brands, still lack an integrated platform able to effectively coordinate cross-channels efforts, collect the relevant data each interaction generates, and analyze it to accurately track and identify the efforts delivering the most impact. This shortcoming has many, often interrelated causes, including the use of multiple agency partners for what are deemed to be separate initiatives; the general difficulty in coordinating campaigns and tracking results across display, search and social media; and the lack of an integrated marketing platform with effective cross-channel metrics & analytics capability needed to support sophisticated attribution modeling. This inability to track efforts and accurately measure performance often results in brands doing the best they can, which more often than not means spray-and-pray media buys and crude last-touch attribution. This can lead to significant misallocation of marketing spend, since it completely disregards the value of the supporting interactions that preceded that fateful one that ultimately triggered the conversion event.

Sun Tzu observed that ‘strategy without tactics is the slowest route to victory” and his sage words apply equally to the challenges faced by todays digital marketer. For even the best audience segmentation and targeting efforts are rendered useless without the ability to target and deliver the brand’s message to the target audience at the right time and place via the needed channel. Likewise, he observed, “Tactics without strategy is the noise before defeat”. Brand impressions delivered to the wrong audience, at the wrong time, or via an ineffective channel are destined to miss the mark and will fail to have an impact, resulting in waste.

A Comprehensive Analytics Platform is Critical

Many companies offer solutions to help advertisers and publishers reach larger audiences. But, as with most things in life, it’s not always about size. Bigger is not always better. And, when it comes to digital advertising, it can actually be worse. And certainly a lot more expensive. If your audience analysis, selection, and targeting are done right, less can result in more: more clicks, more traffic, more engagement, and more sales. And less wasted effort, ineffective media buys, lost impressions, missed sales.

Your goal should not be to reach the biggest audience but, instead, the best one possible and, ideally, at the lowest cost. The audience that meets your target criteria and aligns best with the profile of your shoppers and buyers. The audience that engages, converts, and delivers revenue.

Accomplishing this will require you to:

Verify Audience – ensure all your purchased impressions are delivered and viewed by your target audience, not bots or click-farms.

Analyze Attribution – develop insights about the elements in your campaign that are actually driving conversion and ensure you understand the entire path.

Optimize the Campaign – do more of what works, less of what doesn’t. This may take some experimentation to get right, so continuously review the results and take appropriate steps to maximize effectiveness and optimize overall Return on Advertising Spend (ROAS).

From Data To Insight, Effective Action to Results

Finally, even with access to good data, rigorous analysis and timely, accurate insight, brands and their agencies still lack one vital component crucial to success: decisive – and timely – action. It’s no secret that the pace of our frantic, always-on world has accelerated and continues to do so. With the rise of social media, news spreads in near real-time and perceptions, attitudes and trends can turn on moment’s notice. Marketers need to be in tune with this, especially if their target audience includes millennials or other highly connected groups.

Brands and their agency partners must be plugged into current events, trending topics and the effect they can have on our cultural mood and Zeitgeist. While large campaigns will still need to be planned ahead to afford for effective coordination, they must be monitored constantly and designed with enough flexibility to be nimble and responsive, able to shift as needed. To do so, campaign managers need access to real-time performance data in a format that will allow them to tap into trending events and cultural phenomena and shift media spend quickly to capture the wave of interest and capitalize on it.

If Twitter is abuzz about Michelle Obama’s dress, then that’s a great opportunity to run ads showing your brand’s similar design, available at a fraction of what that Carolina Herrera number cost the taxpayer. If Pinterest is blowing up over Beyoncé‘s Alexander McQueen boots, it could be a good time to show how similar your line is, available to anyone online, at far more reasonable cost. Or, if the world is reeling from the heartache and agony of a deadly plane crash, it might be wise to pull your ads centered on air travel and replace them with the version that showcase the great American road trip.

Monitoring campaigns while in-flight, using real-time data, and optimizing them multiple times a day by reallocating spend and changing messaging, can enhance performance and dramatically lift effectiveness to deliver improved results measured where they matter most: the bottom line.

Posted in Big Data, Branding, Interactive Marketing, Social Media, Uncategorized, Web Metrics | Tagged , | 10 Comments

Reductio Ad Absurdum

MediaPost has a great cartoon in today’s entry of Stan Mack’s Real MAD – True Tails from Inside the Ad Biz series.

In it, we see a hapless AdTech salesperson trying to offer solutions to a rather clueless brand CEO. Despite his perfectly clear – and rather concise, albeit somewhat jargon-laden – value proposition, the CEO points out that he is not a “techie” and thus requires a “simpler” version of our protagonist’s pitch.  The second and third attempts – now largely sanitized of any “techie” terms, but also increasingly without real insight or differentiation –  end similarly fruitless.

I'm Not a Techie!

I’m Not a Techie!

Finally, our our salesperson gives his conversation partner the bottom line in easily understood terms. And, while his final summary is likely (we hope!) a true representation of the final outcome of his offer, the CEO really has nothing substantive to evaluate this. In the end, all he hears is what everyone else is promising.

At this point – one I have reached far too many times, unfortunately – the message is adequately simplified for the CEO to consume, though also homogenized to a point of having no substance. And, once the conversation reaches this signal/noise ratio, the only way to differentiate an offering or break through the clutter, is with more amplification. At this point, the competition is no longer based on merit or results, but boils down to who has the bigger bullhorn, the most reach, the biggest marketing and expense budget. This is what slows true innovation.

The fact is, CEOs – and certainly CMOs and their brethren CDOs – NEED to be “techies” to some degree, since today’s business relies on technology to work. And, let’s be frank, understanding the role of technology and its pivotal importance in modern business practices, is hardly the exclusive domain of “techies” these days.

Similarly, C-level executives can no longer excuse their ignorance of vital technical components by claiming their domain is “the big picture”.  Unfortunately, all too many seem not to have gotten the e-mail. Perhaps they’re still waiting on a memo, complete with the new cover sheets. Or, they’re simply preoccupied with today’s TPS reports.

Posted in Big Data, Digital Media, Interactive Marketing, Programmatic, Web Analytics, Web Metrics | Tagged , , , | Leave a comment


PART 1 – Getting from Data to Actionable Insight

This is the first white paper in a two-part series exploring how data is revolutionizing digital marketing. This document examines some of the difficulties business faces in meeting the data challenge and what steps must be taken to effectively leverage data-centric methods to gain actionable insights from the huge volumes of data now at our disposal.

PART 2 – Using Data-Centric Insights to Drive Effective Media Strategy builds on this document and examines how business can successfully leverage the insights gained from their analysis to power and optimize marketing operations in the quest for greater ROI in digital media.

Why read this paper?

Big data is big business these days. Research firm IDC forecasts that big data services and technology will grow at a 27% compound annual growth rate (CAGR) to $32.4 billion through 2017 – about six times the growth rate of the overall information and communication technology market. And the performance improvements, increased revenue, and operational savings promised by effectively leveraging big data are expected to dwarf that number. As companies scramble to implement big data strategies, marketing has been one business function where the potential benefits of increased efficiency loom particularly large. And much is at stake here. Industry experts like eMarketer and Forrester predict global spending on digital adverting will grow about 15% annually and top $200 billion in the next five years. Achieving even a small increase in efficiency could therefore deliver huge ROI.

Software vendors have flooded the market with countless products, all promising to help meet the big data challenge. Many are capable tools that perform well in their respective areas but address only part of the challenge. They can also be difficult to implement, hard to integrate, and often require deep technical and analytical skills to configure and operate. Today’s marketer needs solutions that are complete, integrated, easily implemented and intuitive to operate, requiring a minimal learning curve, if they are to deliver on the big data promise.

But most organizations will require more than tools and technology to succeed. Many lack a data-centric culture and will struggle to attract and retain talent with the deep analytical skills needed. And beyond mere talent, companies will need to change operational procedures and structure workflows and procedures to optimize the use of data-driven insights.

Big Data Is About Data, Not Size

But first let’s take a closer look at why the big data revolution is so significant and, while offering significant promise, also presents some unique and vexing challenges.

The challenge with big data isn’t just its size, but also its lack of structure, diversity and fluid nature. These factors, more than sheer size, make it hard to aggregate, integrate, manage and analyze.

While storage and processing capacity have increased greatly and costs have plummeted, there are other factors that limit our ability to manage, index and cross-reference large data sets. It used to be that companies collected data primarily as a part of their daily transactions and stored it in structured databases. This data was used mainly to track operations or forecast sales, inventory and the like. It was structured, well understood and relatively easy to manage and analyze. With the explosion of data sources, we have seen not only the volume of available data increase drastically, but also the very nature of the data itself change. With more and more business processes, operations and stakeholder interactions digitized, business now has data on just about every customer interaction, including click-streams from Website visits, search activity, mobile apps, digital advertisements, social media content streams, videos and countless more. And, as the “Internet of Things” becomes a reality and digital technology invades our homes, our cars and even our bodies (Google recently announced a contact lens with embedded microchip and sensor to monitor glucose levels for diabetes patients in real-time and send the data to an application in the cloud), virtually everything we do will generate data.

Analysts estimate that fifty billion sensors will be connected to the Internet by 2025, each one adding to the data pool available for analysis. While our refrigerators may not be networked (yet), our televisions, home security and thermostats are (note Google’s recent $3.4 billion acquisition of Nest) and all are generating data points. Companies will soon not only be able to collect information about every conversation people are having about their brand, but also monitor interactions with their products anytime and any place they occur.

But that alone will not make them better marketers. In fact, it could do just the opposite. Few executives lament a shortage of data as holding them back. Instead, like modern versions of Coleridge’s Ancient Mariner, they are awash in data, yet thirsting for true insight. Adding even more data – without corresponding improvements in the ability to organize, analyze and interpret it – could well prove counter-productive, leading to analysis paralysis or providing false cover for bad decisions. What harried business leaders seek are simplicity, inspired guidance and clear, actionable insight. And no amount of data can provide this on its own.

Getting from Data to Actionable Insight

Henry Ford once famously proclaimed that if he had asked people what they wanted, they would have said faster horses. And there would have been ample data to support this request. More skilled at engineering than equine breeding, Ford didn’t take this raw data at face value though. Instead, he analyzed it carefully, interpreted it creatively, asked deeper questions and innovated based on the insights he gained from his analysis. And herein lies the crux of the matter: it’s not the data itself, nor its size, that provides the value. Instead, it’s the insight we derive from it and the actions we take based this insight. Data is just a tool, a resource, nothing more than an inert ingredient until we add the catalyst. As Hamlet observed, “there is nothing either good or bad, but thinking makes it so”. Whilst he was musing on things unrelated to data analysis, his ideas are just as valid and applicable here: without human reflection, analysis and thinking, we will drown in data while actionable insight remains beyond our grasp.

So how do we get from raw data to actionable insight? How do we harness this flood of information to understand our customers better and take our business to the next level? The late Dr. Russell Ackoff, once described as the “Einstein of modern problem solving”, shows us the way in his famous article, “From Data to Wisdom”.

In it Professor Ackoff states “Data is raw. It simply exists and has no significance beyond its existence.” We have to enrich it by providing context, relevance and relationships, at which point it becomes information. Take the statement of “we sold 1,000 units last year”, a classic example of raw data that tells us very little. Are sales of 1,000 units good or bad? Is it more than the year prior, indicating an upward trend, or are we falling behind? Were the sales profitable, indicating a healthy business? Are we out-performing our competitors, indicating a comparative advantage? These contextual aspects are what give the data meaning, and thus render it into more useful information.

But information alone provides limited benefit, as it lacks purpose. While it may be interesting to note that your company doubled profits last year while sales increased by 20% to 1,000 units – more than twice your closest competitor – it still doesn’t give us any understanding of how or why this happened. Only by aggregating enough information, to where we can discern patterns and are able to draw conclusions, does it become knowledge. Acquiring this knowledge is valuable, for it gives us insight into how things work but it is still not actionable. It tells us that something works and how, but we don’t understand yet why – or, more importantly, how we can take action to influence it in a desired way.


Getting from raw data to insight you can use.

For knowledge to become actionable insight, we also need an understanding of causality, the why. Achieving a true understanding requires us to distill data, aggregate it into information and then knowledge, and then actually synthesize new knowledge from it. To build on our example, if the analysis of our data shows us that the regions that performed best – the ones that contributed not only the most to our overall sales growth but also the most profitable sales – all had sales people that had completed the new sales training program, then it stands to reason that this was a major contributor. We can then reasonably assume that if we were to train the salespeople in our other regions, they might also see an increase in overall sales as well as profit. With this new insight we now have an understanding of how certain regions perform better as well as why this is the case: their salespeople are better trained. This enables us to take action and train the rest of our salespeople. The analysis of subsequent data should then, presumably, show an increase in performance in these regions as well. This is a classic example of data-driven optimization: gathering data, aggregating and analyzing it to gain actionable insight, acting on it and then measuring the results to validate the effectiveness of our actions.

And, once we do this often enough, with enough data from across the enterprise, and marry these new insights up with our industry experience, professional judgment, and our understanding of business principles, we arrive at what Professor Ackoff referred to as wisdom. Wisdom, in his use of the word, refers to the ability to anticipate outcomes, to predict certain results based on historical data. It also enables experimentation by providing the basis for developing new hypotheses that can enable new business ventures, product extensions and new approaches that can be defined, developed, executed and then tested and measured.

Meeting Today’s Challenges

Professor Ackoff developed this approach back in the 1980s and published his insights in 1989. Back then our data sources consisted mainly of transactional systems commonly employed in business at the time, systems that managed sales, supply chain functions, financial systems and such. Reflecting this, there was far less data, it was clearly delineated by source, well-structured and stored mostly in relational databases. All of this made it relatively easy to collect, aggregate, refine and analyze. The biggest challenge faced by business at the time was the lack of integrated systems, which meant that the data had to be collected from numerous separate systems, converted into common formats, normalized, harmonized, and prepared for analysis.

These are all the same challenges we still face today. With the explosion of data sources and the corresponding increase in volume and complexity, however, they have grown exponentially.

Technology Only Goes So Far

Luckily, new technology has emerged to help us with our efforts. We have seen vast increases in our ability to store, manipulate and process data thanks to tremendous increases in computing power over the last decade. These have been further enhanced by developments like NoSQL databases, Hadoop and other distributed data storage and processing frameworks, new standards like PMML, advanced analytics platforms, and many others. Combined, these factors give us an unprecedented ability to collect, store, manipulate and process data electronically. The one aspect that has not increased significantly though, remains vital today: skilled, inspired human analytical skill.

Without careful analysis and inspiration we simply cannot advance from knowledge to actionable insight and beyond, no matter how big our data pools are or how powerful and sophisticated our technology might become. Professional analysts, systems designers, and programmers are also needed to design and develop the tools, platforms and programs needed to make the data volumes manageable, devise the logic by which we can process and analyze it and then present the results in a clear and actionable manner.

As companies and brands embark on big data projects, the shortage of skilled analytical talent is frequently cited as one of the biggest impediments they face, along with a lack of integrated technology platforms that are easy-to-use and yet flexible and powerful enough to be able to meet the needs of business. Developing talent and changing mindsets to become more data-savvy will take time, of course. Meanwhile, the AdTech market is scrambling to answer the call for better technology and provide integrated platforms able to meet the needs of digital marketers, freeing them up to focus on what they do best: develop effective targeted campaigns.

The Market Responds

With so much at stake and the potential rewards so large, the advertising technology sector has seen a flood of investment in recent years. The result are digital marketing LUMAscapes littered with dozens of startups, most less than five years old. And, as always happens following huge waves of innovation, necessary consolidation has begun. Weaker entities are being acquired and integrated by players that are stronger or have deeper pockets. And signs of promise are emerging, with several vendors now offering complete integrated solution platforms able to target, execute, monitor, analyze and optimize efforts across various media, channels and touch points.

And, recognizing the need for consulting services, campaign strategy and integration, a number of companies and agencies now offer targeted services, often coupled with platform solutions that combine several third-party components into a bundled offering. These service providers promise to get marketers up and running quickly, providing external staff where needed and helping to shorten the learning curve.

The next few years will be an exciting time in digital marketing, as brands and agencies alike embrace data-centric approaches for greater accuracy and efficiency. And, presumably, better business results.

Posted in BI, Big Data, Digital Media, Financial Crisis, Interactive Marketing, Web Analytics, Web Metrics | 3 Comments

Advertising That Works. Sorta.

Big Data, Analytics and Programmatic Buying Are No Panacea

Harvard Business Review recently devoted much of their March 2013 print issue, including the cover, to digital advertising and the way big data and analytics are transforming the field. You can read an intro to the piece here, but will have to subscribe to get the full article.

The Promise of Smart Advertising

The article discusses how today’s data-centric marketing is not only able to precisely target ad placements based on demographic, psychographic, behavioral, and a host of other data, but can then also reliably track and attribute subsequent consumer behavior to exactly the advertising that triggered it. This insight is then used to further tune campaigns, optimize media spend, targeting, and placement on an ongoing basis.

Usually, all of this is automated. Media is bought via programmatic platforms and campaigns are optimized in real time based on results achieved, driven by powerful algorithms and without human intervention. According to the HBR article – and countless ad-tech vendors’ marketing claims – this approach promises the equivalent of laser-guided precision ad units that hit the mark each time, at precisely the right place and time for maximum effect and minimal cost. HBR describes this new advertising landscape similar to the precision-guided munitions employed by our military. Perhaps an apt comparison, as they seem to share a common flaw: both require a change in approach and neither seems to work quite as promised in less than ideal settings. Allow me to elaborate.

Measuring is no Substitute for Managing

Digital advertising has always claimed to be more measurable than its traditional, offline brethren. While billboards, print, and broadcast media were forced to rely on crude (and often manipulated) metrics like circulation, Nielsen ratings, GRPs, traffic counts and the like, digital media could always point to its inherently interactive nature. And this claim could be substantiated by “hard” data, including click-through rates and paths, engagement, time-on-site and more.

Proper Ad Targeting, Context, and Placement are Crucial

Proper Ad Targeting, Context, and Placement are Crucial
(Image source:

Even better, when a product was purchased online or a lead generated, this action would commonly be credited to the media that drove the consumer to the conversion point, a process commonly referred to as last-click attribution. It seemed the only blind spot for digital media was the inability to clearly attribute offline purchase decisions to media consumed (and ads viewed) online, where both traditional and digital media appeared to be on equal footing. And, given that consumers were increasingly consuming media online and in digital formats, yet brands were still disproportionately allocating spend to traditional, all that remained was for marketers to shift spend so that online media got its fair share and all would be right. Wrong.

For one, it turns out that not everyone peddling eyeballs online is totally honest and a lot of those clicks and views are not by actual consumers but, instead, automated bots that generate phantom traffic. As a result, much of what brands spend on digital ads is wasted on non-existent views and fraudulent clicks. And it’s not just amateurs getting taken here. Even large, presumably sophisticated advertisers like AT&T, BMW, and McDonalds, running what I assume to be sophisticated (and expensive) campaigns, are falling victim to this and, at times, losing up to 80% of their spend to fraud according to one report.

But, click-fraud and bot-traffic aside, there remain other issues with today’s state of digital advertising and it is still far from the perfect, well-oiled machine portrayed in the HBR. For one, online display ads are notoriously weak in building brand awareness and show weakness even for direct-response advertising. A recent study illustrates this and data shows that consumers are statistically more likely to survive a plane crash than click on a banner ad. Of course, campaigns vary greatly in terms of effectiveness, but you get the gist. Beyond display advertising (banners and such), similar issues surface in paid search, social media, and the latest trend to emerge, so-called “native” advertising.

My Reality Belies Market Claims

At the heart of these issues seem to lay poor segmentation and targeting, along with the crude, heavy-handed execution of many of the campaigns. For all the much-vaunted data that Google and Facebook have on consumer behavior and the supposed sophistication of today’s marketers, I continue to be perplexed by the ads I am (mis-)served on a daily basis. Any parent who has had their teenage daughter borrow their computer for 30 minutes and then paid for this with countless ads for One Direction’s new tour or the spring sale at Forever 21 knows what I’m talking about. These re-targeted ads – which occur when you visit a site but then fail to buy (or even when you DO buy, ‘cause, y’know, you might have missed something, right?) – are becoming increasingly popular with marketers, despite a growing backlash by Internet users.

Marketing Still Requires Marketers

This is not to say that digital advertising isn’t the way forward. Nor that smart, targeted ads guided by data-intensive insight don’t hold great promise, for both are clearly true.

It’s just that, for now, they are not yet delivering on their promise of identifying the right consumers and serving them the most relevant ads at the most appropriate time. Big data, analytics and ad-technology will clearly play a key role in getting us to there. But, technology alone will not do the trick. While it is clearly necessary, it is simply not sufficient on its own. As programmatic buying and RTB (Real-Time Bidding) platforms gain traction and big data becomes an even a bigger deal in guiding marketing (hard to imagine in the current hype-cycle, right?), advertisers, their agencies, and consultants will need to ensure that the human component is given equal consideration. Business processes, marketing departments, campaign design, and media spend all need to be adapted to the new reality. Some even claim that the rise of technology-centric marketing calls for an entirely new member of the C-suite, the Chief Digital Officer or CDO. While this is a debate for another time, this much is clear: investments in hiring, training, and consulting services must accompany those made in systems and technology if they are to be effective. Technology, no matter how refined and sophisticated, is never the panacea promised by vendors. We saw this with ERP systems, EAI/BPM, and a host of other initiatives that all required several years and multiple investment cycles in both IT and human capital, along with structural changes to organizations and processes, to deliver on their promise.

Solid marketing fundamentals, effective strategy, strong creative, and execution still matter, and I fear there’s just no app for that. New techniques and tools will require marketing teams and brands to change their thinking, acquire new skills, and develop effective approaches. Same as it ever was, one might quote one of my favorite 80s bands.

Posted in Big Data, Branding, Interactive Marketing, Internet Technology, Web Analytics, Web Metrics | 6 Comments

Top Business Technology Trend Predictions for 2013

It’s that time of year again. As 2012 draws to a close, we decorate our homes for the holiday season, reflect on the year about to end and ready our resolutions for the New Year.

"Prediction is very difficult, especially about the future."

“Prediction is very difficult,
especially about the future.”
Niels Bohr, Danish physicist
(1885 – 1962)

And, of course, try to ascertain and prognosticate what developments the next 12 months will bring. Following this tradition, I have assembled my top predictions for 2013 below, based on daily observations, anecdotal input from others, conferences I have attended, trade publications, analyst reports, and Scotch-fueled late night conversations with others in the field. It should be noted that I am a hands-on practitioner and not an analyst, professional writer, or industry pundit. As such my focus is more practical – and perhaps more narrow – than some and the views represented are solely mine and unencumbered by any agenda. We’ll see in the coming months what impact, if any, this has on the quality of my predictions.

This is a long post, reflecting the magnitude of the change I sense is underway and the dramatic impact it will have on business and our daily lives. I apologize in advance for those who, like me, struggle when confronted with long prose (and short attention spans), but hope my tone and diction aid in making it somewhat consumable.

You will find that many of the trends outlined below are interrelated and mutually reinforcing. This is one of the reasons for their rapid, exponential growth and propagation. It is also why their impact on business and our daily lives promises to be significant, as individual developments act to reinforce one another, thereby unlocking synergistic effects that work to magnify and increase the overall impact of each.

For instance, as mobile device proliferation drives anytime/anyplace access, it will greatly increase network traffic and growth in “mineable” data volumes, which in turn will accelerate the growth of both cloud computing and analytics to extract value. All of this will spur investments in technology, and make technical proficiency more critical to all roles and functional areas of business. Likewise, as network access becomes more pervasive, users will derive more utility and benefit, which in turn will drive consumer and business demand for tablets and other mobile devices. Growth in device demand will, once again, increase usage, data volumes and the potential for value creation, thereby closing the loop and creating a virtuous (one hopes) cycle of self-reinforcing, explosive growth.

Mobile Computing

There has been much talk about the rise of the mobile Internet and it looks like the oft-heralded “Year of Mobile” may finally be upon us in 2013. While most analysts predict that mobile Internet traffic will not eclipse the desktop until 2014, some are now adjusting their predictions based on more recent growth data to say this will occur next year already. I remain skeptical of this. For one, many analysts include tablets accessing the Web via WiFi connections, which in my book isn’t true mobile. But, this may be splitting hairs.

The fact remains, however, that alternate devices – as in anything other than traditional desktop or notebook computers – are on a tear and this is fundamentally changing the Web. For one, companies now really need to take a hard look at their digital strategies with a serious consideration towards device diversity. Many see responsive design as the solution here, others are betting the farm on a mobile-first approach, with desktop almost as an afterthought. Only time will tell what approach is the better but one thing is for sure: the mobile Internet – regardless of how you define or respond to it – is here to stay and growing rapidly. Ignore this trend at your peril.

A lot of companies are still currently underinvested in an effective mobile offering and I regularly encounter large retailers, service providers, and entertainment venues that offer little or nothing in the way of a serious mobile strategy.


I view convergence as an overarching meta-trend of sorts and see it taking place on several levels, including user expectations, devices, technical standards, applications and business models. As such, it is driven by a number of other trends and, similarly, also acts to accelerate others.

Convergence has been happening for some time and across sectors, but is now increasing in scope, speed and impact. Think of data networks that have converged around common IP standards and protocols such as TCP/IP, and now carry data, telephony, television signals and more. Device convergence is seen in modern smart phones that handle voice, SMS and Internet access.

What’s new – and will become an increasingly powerful factor – is true convergence at the application, integrated device and business model level.

Examples here include mobile payments, such as Google Wallet and ISIS, which combine Internet technology, standards and infrastructure with payment industry standards, such as PCI, and mobile telephony and device standards. Square is another great example here and one that has been taking the retail payment acceptance space by storm. We also see increasing convergence at the application and business model level online, where these are increasingly coming together to deliver more integrated, seamless data exchange and a richer, more rewarding user experience, while also creating powerful synergy. Social media, smart phones and location-based services have been big drivers in this area.

Expect more of this, including examples that combine elements of social media, loyalty, discounts or daily-deals, and location-based services such as FourSquare. One example might be to offer certain users unique deals based on demographic and income data, past purchases, and other data once they are within a certain distance of a retailer or restaurant. Another example could be a targeted coupon from a CPG company, redeemed through a mobile payment service and offered upon entering a super market or department store. Some of this may appear a bit creepy at first and companies must take care to avoid consumer backlash but, just like targeted couponing around frequently bought items at time of check-out at the supermarket, this sort of real-time suggestive offer delivered via your smart phone represents an example of application convergence and will eventually become commonplace.

Tablet Computing

On the device and computing hardware front the biggest change threatening the traditional desktop or notebook computer is the rise of tablet computing.

Computing OS by Market Share

Combined, Android and iOS have displaced Wintel as the dominant computing OS.
Image Copyright 2012, KPCB

In fact, Business Insider cites this as the top threat to Microsoft’s hitherto reliable profit stream from their Windows operating system. Meanwhile, Mary Meeker of KPCB points out on slide 24 of her Internet Trends Update Presentation what a dramatic effect the rise of Android is having on Wintel’s seemingly unassailable lock on the OS market.

And, based on my personal use and anecdotal information from others, it would appear plausible that tablets are in fact cutting into consumer desktop usage, though few folks are quite ready to ditch their notebook computer altogether. Not yet, at least.

Expect this trend to continue and also look for more alternatives to Apple’s iPad to hit the market, including Android devices and targeted niche tablets such as Amazon’s excellent Kindle Fire.

With the introduction of Google’s Chromebook, starting at just $199, we also see how this trend begins to threaten the more traditional PC/laptop business and Microsoft’s core business.

My kids will be getting a Chromebook for Christmas this year, by the way, along with a new Kindle. My last purchase

was a notebook I bought last month with Windows 8 (plus a shit-ton of bloat- and adware) that left everyone in my household less than impressed.

I sure hope somebody in Redmond is reading my blog.

Big Data and Analytics

There has been a lot of talk about Big Data in 2012 and next year will see a continued focus on data, both big and small. This will have a fairly dramatic effect across all areas of business. Marketing – and digital marketing in particular – will most likely feel the greatest impact though, as the C-Suite insists on ROI and the data to back it up. Instead of feeling threatened, marketers should welcome this, though most seem currently ill-prepared to rise to the challenge. As I wrote a few weeks back, there are reasons for this, but these can be overcome and marketers should seize this opportunity to prove the effectiveness of their work and justify the investment it requires.

Marketing spend on digital channels continues to grow rapidly, at far greater rates than other channels and media. In fact, it is now second only to broadcast television – a misallocation that persists, despite consumers spending more time online than watching television – and one can expect the importance of metrics data surrounding reach, engagement, conversion, and attribution to increase in lockstep. And, since digital media is uniquely measurable when compared to traditional, and each interaction generates a data point, expect the resulting data volumes to grow in lockstep.

To truly derive value and actionable insight from these mountains of data, marketers will need to make investments in hardware, software, people and process in order to store, structure, dissect and analyze it. This will add further impetus to the rise of cloud computing, while the move to data-centric decision making will require more technical and analytical skills across all functional areas, including marketing.

Increasingly Cloudy

Cloud computing will reach true maturity and permeate both business and personal applications. Software-as-a-Service (SaaS) will become the dominant model for most corporate applications, displacing the traditional software lifecycle and license purchase model.

This will have dramatic effects on the IT department and the role of the CIO. Once freed – or, at least, greatly relieved – of the need to manage desktop applications, networks and common business solutions such as CRM, SFA and even Finance and ERP, the CIO will shift from an operational to a more strategic focus. Eventually, the role will morph into that of Chief Digital Officer. Not all will be up to the task, but those that are will find their influence and impact on the future success of their company greatly enhanced.

Cloud computing will also continue to penetrate the consumer space and eventually most of our data, applications, and content will reside there, accessible to us anytime, independent of device, place or time.

Social Media is dead. Long Live Social Media!

Social Media will experience moderation and enter the Trough of Disillusionment, before emerging stronger and more focused. This is not necessarily because the power of social media has been over-sold (though, at times, it clearly has) but, rather, because companies have over-invested and need time to digest, sort out what works, and apply more operational and investment rigor.

Already there are early indicators that many are falling out of love with the Web’s latest new new-thing and, increasingly CMOs – or maybe CEOs, concerned about overall spend in this area – are questioning corporate investments in social media and demanding to see proof of its effectiveness and ROI.

It is not uncommon for new, disruptive concepts to become over-hyped in their early stages, then fall into disfavor, only to emerge stronger but more focused later. Arguably, the Web itself experienced this in the late 90s with the dot-com bubble and bust in 2000. Expect social media to undergo a similar trajectory, though perhaps not quite as extreme. This should not be seen as a dismissal or distract from the validity and effectiveness of social media as a concept. Instead, interpret it as a call to moderate efforts, make them more thoughtful, targeted and focus more on quality over quantity, substance over style and frequency. We’ll get there.

Expertise in Technology Becomes More Important than Ever

As I wrote last week, expect technical proficiency across a wide range of common Internet standards and concepts to become more important than ever, across the enterprise and regardless of functional role.

The fact is, we live in a tech-driven world and business – and employees – will need to adapt and evolve or risk obsolescence. Internet technology and concepts now permeate every function of business, from accounting to supply-chain and whether you’re a lawyer or an HR professional, it behooves you to develop and maintain technical skills.

And that’s it, I’m spent. I hope you enjoyed reading my predictions and I welcome your comments, feedback and thoughts. I also trust you’ll join me again in a year – or maybe earlier – when I will review these and see how I did. Until then, best of luck, prosperity and good health in 2013!


Posted in BI, Big Data, Business Analysis, Business Intelligence, Interactive Marketing, Internet Technology, Mobile Internet, Social Media, Uncategorized, Web Analytics, Web Metrics | 3 Comments

We’re All Techies Now

The Marine Corps has a saying that, when things get serious, it doesn’t matter if you’re a cook, a truck driver, clerk or radio operator. When the shit hits the fan, everyone’s a rifleman. As a result, every Marine, regardless of military occupational specialty, is trained in basic rifle marksmanship and required to regularly qualify with their primary weapon, currently the M-16A4 rifle.

The rationale being that, since modern warfare is marked by fluid, often unpredictable battle lines and that even rear echelon support troops may find themselves in armed combat at a moment’s notice, every Marine must be proficient in basic marksmanship. As we have seen in Iraq and Afghanistan, there are no more “front lines” in today’s battlefield.

US Marines with their primary weapon.
Photo courtesy of the USMC.

The Internet – The Primary Weapon for Modern Business

A similar case can be made for a basic understanding of technology, in particular Internet technology, in the context of modern business. Whether you’re an accountant, supply chain manager, banker, salesperson, or marketer, the Internet is an integral part of your job.

Technology is everywhere, and the Web continues to upend and disrupt nearly every aspect of business. Organizations at the forefront of this trend are integrating processes and systems all along the value chain and one is hard-pressed to find roles not dramatically affected by this.  GE is now employing social computing to improve their industrial manufacturing processes and is integrating sensors that use TCP/IP and wireless protocols to optimize the efficiency of wind turbines. From procurement to logistics, over sales planning, POS, accounting, billing, payments and customer service, formerly disparate systems are increasingly integrated via networks built on Internet standards. And, in most cases, these systems are being accessed primarily via the Web (or Web-based technologies), often through a multitude of channels, including smart phones and other mobile devices. This not only streamlines business processes, reduces errors and cuts cost, but also increases speed and transparency.

Marketing in the Digital Age

One area that has been affected dramatically by the Internet is marketing. Today’s marketer works in an environment that is fundamentally different in just about every aspect from what he may have encountered as recently as a decade ago. With the rise of digital platforms, marketing has become far more complex, more fluid, and, importantly, more measurable. And yet many of today’s marketers have failed to evolve and often lack the technical skills and fundamental understanding of the Internet needed to most effectively employ the tools at their disposal.

It used to be that IT was a separate department that other functional areas called upon when they needed their PC connected to the printer or a piece of software installed. Accountants, sales people, supply chain managers, and, yes, marketers would go about their daily business blissfully unaware of what made the network run or how exactly their e-mail got to where it needed. Information technology was considered a cost center, not a source of competitive advantage or differentiation. All that has changed and many companies now – from retailers, to publishers, financial services companies, and consulting firms – derive a significant portion of their revenue from online activities. Digital technology is now so pervasive, affecting so many aspects of business in such fundamental ways, that many experts question if it even makes sense anymore to have IT as a separate department. Instead, technical expertise and digital fluency are now such an integral component of just about any business function, that these skills need to permeate each and every part of the org chart.

A Series of Tubes

When the late Alaska Senator Ted Stevens described the Internet as “a series of tubes” back in 2006, he was roundly ridiculed by pundits and members of the digerati. Ironically, he was  charged with oversight and regulation of the Internet at the time. But ask a random sample of marketing folks to explain the basic building blocks of the Internet – things like HTTP, TCP/IP, HTML and similar – and you just might find that the late Senator had a better grasp of things back then than many marketers can muster now. And, while many eagerly employ industry buzzwords like Big Data, real-time analytics, business intelligence, cross-media publishing and more, few can describe what they actually mean and even less could write an SQL query or build and launch a simple Website.

Now many of you may interject that there is no need to understand the technical underpinnings of these tools and concepts in order to use them. And, if your job is merely to write content for your Website or place media buys, you may be right. To a point at least. But if your role goes even just a little beyond that – and, let’s face it, most do – you’d be dead wrong. For even those simple tasks require at least a basic understanding of SEO, a grasp of how your content management system works, or how media buys are priced dynamically based on variable CPM rates, how to identify or avoid click-fraud, and a multitude of other factors that affect success.

If you’re in an only slightly more responsible role, you may be called upon to research and identify new marketing automation software, or help assess the cost, time, and effort to integrate your CRM platform with the new e-mail marketing system. Without a basic grasp of how these work, all you have to go on is the information provided by vendors or consultants. How would you know if an estimate is too high or, as often happens, unreasonably low? There are common reasons why most IT projects come in over budget, are completed late or fail altogether and, next to poor planning and project management (and I would argue that both of these are related to technology as well), a lack of technical understanding by key decision makers is often a root cause.

Trust – But Verify

For how can you or your team evaluate a proposal or tool without understanding both the business requirements and the technical criteria needed for it to work, especially when the two are so closely intertwined? If I had a dollar for every time I’ve heard a vendor tell me their system is “basically plug-and-play” and offers all you could ever want or need “out-of-the-box” with only some “minimal configuration”, I’d be a wealthy man. The fact is, IT is complex. And it has to be in order to solve the complex business problems that need to be addressed. Sure, the CRM system your company is considering looked easy and worked flawlessly during the vendor demo, but how much time and effort was put into preparing that slick presentation? And just because your consultant – who, let’s remember, is paid by the hour – says that adapting the system to your processes and integrating it into your environment is “straightforward”, doesn’t make it so.

Reality Bites

But bad IT purchase decisions and failed projects are but one symptom of inadequate technical knowledge within many organizations, albeit a very visible one. Much more prevalent – and insidious – are persistent under-performance and missed opportunity, which can often go undetected for years. The effects can be corrosive and will often lead to a vicious circle that feeds on itself and becomes self-reinforcing as more tech-savvy team members become frustrated and seek opportunities with organizations that “get it” and value their expertise.

Survival is Optional

The fact is, technical competence is increasingly important, regardless if you’re a project manager, analyst, or even a sales or account director. The days when a fellow like Tom Smykowski could get by on just “people skills” are over, today’s interconnected business calls for more. Much more. But, worry not, your company will most likely adapt and survive. The question many marketing professionals should ask though is whether they will. Younger, more tech-savvy employees are coming up quick. I was reminded of this just the other day by my 12-yo daughter. Previously, I had learned of her holiday wish-list from a letter to Santa written in crayon. This year’s list, which included a request for an iPad and a new smart phone, came to me via e-mail containing a link to Google Docs. And, just to be sure “Santa” – not always known for his technical prowess – got it right, she had included links to the exact products on retail Websites and photos of the desired items on Pinterest and Instagram.

Online collaboration via Google Docs, integrated with social media and delivered using the Internet. All this by a 12-yo child in seventh grade. I work with senior digital marketing leaders at Fortune-500 companies nearly every day and many of them would not be able to pull this off without help.

Would you?

Posted in BI, Big Data, Branding, Business Intelligence, Interactive Marketing, Internet Technology, Web Analytics | Tagged , , , , , , , , | 5 Comments

Business Seems Stuck in the 90s When it Comes to the Mobile Internet

Attend any digital marketing conference and you quickly realize who the belle of the ball is these days. Everyone, from agencies, management consultants, publishers, to technology vendors, seems to be obsessed with mobile. Everyone except business, that is. For while mobile currently makes up around 16% of total Internet traffic, and its rapid growth promises to fundamentally change the web, its share of advertising spending and overall investment is significantly lower. This indicates that business may, once again, be late to recognize a major shift.

We see this reflected in the lower advertising CPM for the mobile Internet, which is currently only about 20% of desktop CPM. This is often justified by pointing out that average revenue per user (ARPU) is similarly lower for mobile users. I contend this is the same circular logic that led to the initial under-investment by brick-and-mortar business back in the 90s, when the Internet first became mainstream. This myopia on the part of business allowed many traditional players to become dis-interGoogle Beta 1998mediated by the likes of Amazon, eBay and Zappos. Others lost market share to nimbler competitors who adapted more quickly. The current rise of mobile may well do the same.

For let’s face it, mobile Internet users are just like desktop users, only more so. As in more educated, more urban, more influential, younger, and more affluent. So why would CPM and ARPU trail by such significant margin? Well, for one, the mobile Internet experience is currently far different surfing the Web at our desk. Even putting network limitations such as coverage and latency aside – assuming for instance that we are connected via Wi-Fi, as most tablet users are – the difference in user interface and screen size of a phone or tablet demands a different approach.

Business and advertisers alike have been slow to adapt to this new landscape and they most commonly fail due to:

Not Offering a Mobile-Optimized Experience at all

Many businesses, including even large retailers, still do not offer an online experience optimized for mobile users. I have experienced this personally in just the last week when I tried to access a national retailer site using my smart phone.

Failure to Correctly Identify Mobile Users

Even companies that have invested in a mobile site often fail due to poor browser/device detection. Incorrectly identifying mobile users and sending them to the desktop site negates any effort and investment made in developing the mobile-optimized experience.

Not Considering a Connected, Multi-Device World

Business needs to understand that users connect and share information across various devices throughout the day and they need to take this into account and plan for it. If a mobile user posts a link to Facebook using his phone, this link may later be accessed by users on a variety of devices. Hard-coding the posters device choice into the link – as I had happen to me when a friend shared this CNN article earlier today – and then taking me to the mobile site even though I am accessing it on my desktop is simply unacceptable and will lead to frustration and drop-off.

Unsuitable Back-End Systems and Data Structures

Some companies may adapt their front-end UI for mobile users but fail to consider other UX aspects. Back-end systems, data structures and cumbersome check-out processes often need to be adapted for smaller screens. A huge look-up table may work (somewhat) on the desktop, but scrolling through a list of 20-30 options proves cumbersome on a phone.

Failure to Truly Optimize for the Mobile Use Case

Mobile users often have different needs and goals than those behind a desk. For one, they’re mobile (as in away from home), so a store locator driven by ZIP code won’t work if you don’t know where you are. Similarly, mobile users are often more task-oriented and will have little patience for superfluous content or fancy imagery.

Business should recognize that the current difference in CPM and ARPU for mobile users is caused by a poor mobile user experience and ads that are simply not designed appropriately. The sooner digital marketers and eCommerce leaders accept that mobile users are not inherently different from desktop users – but that they do have different needs dictated by their device – the sooner they will adjust and refocus their investment in the mobile Internet to reflect the reality of its rapid growth.

Posted in Branding, Interactive Marketing, Mobile Internet, Uncategorized | Tagged , , , , , , , , , | 6 Comments