Closing the B2B | ad tech gap

4 ways the new age of ad tech fails b2b marketers and what to do about it

(An excerpt of this article ran in Ad Age on January 15, 2016.  http://adage.com/article/digitalnext/close-b-b-ad-tech-gap/302149/. Here’s full post). closing the gap

Recently, I saw an IAB B2B Programmatic study that revealed nearly half (47%) of B2B marketers don’t even know what programmatic buying is. That’s a staggering gap compared to B2C marketers where fully 62% of marketers use programmatic (Source: eConsultancy).  This gap is even more stunning considering that B2B represents $77 Billion in digital media with 66% of B2B marketers recognizing that programmatic is just as valuable for them as it is for B2C marketers, (Source: IAB: 2015 Programmatic and The B2B Marketer – Study – http://www.iab.com/news/programmatic-and-the-b2b-marketer-study-confirms-more-education-is-needed/

What’s accounting for this gap between B2B and B2C marketers?

IAB rightly believes education will help, but I suggest there’s something more fundamental going on.  Beneath the “cool ad tech veneer” lies a vast sea of ventures specifically designed to chase large consumer ad dollars but in the process, left B2B advertisers in the ad tech dust.

Here are the fundamental B2B gaps I see and what you can do to overcome them.

1) The great CPM/ CPA performance divide.

Unlike B2C marketing with well-organized branding/ promotion/ direct marketing buckets, B2B campaigns are a more fluid mix of CPM and CPA goals requiring tactics to be both thought leadership and demand generation.

Unfortunately, startups with their decided preference for CPM deals where generating a click is much easier than a qualified lead, created this artificial CPM/ CPA divide that B2B marketers have to live with. The result is that business marketers must patch together a crazy quilt of CPM ad buys along with CPA programs requiring lots of coordination between uncoordinated platforms and networks – a challenge all around.

To combat this issue, pivot from tracking typical metrics like “clicks” or “likes,” to KPIs like Cost Per Visitor. Not all networks will play with you this way – but the quality, “niche” networks will work with you to develop meaningful KPIs.

2) The confusing content marketing tech landscape is a kill joy

B2B revenue results rests on the back of hard working content – technical documents, white papers, thought leadership publications, case studies, reviews, social, PR on innovative new breakthroughs; making B2B businesses far more reliant on content marketing than their B2C peers.

The problem is that content marketing, as a category, is a fragmented, operational nightmare. Content creation platforms are walled gardens from buying platforms and social media is detached from targeting platforms. Throughout this chaos, “data” plays hit and miss trying to analyze these disjointed pieces. The complexity sucks much of the inspiration out of the process.

Salvation here means looking for operationally complete platforms that marry content-based data with ad buying capabilities and an integrated set of analytics that normalize the learning between the user’s topic discovery steps to a qualified lead.

3) B2B programmatic landscape is like blowing out a targeting candle with an impression hurricane.

One word sums up this problem: “scale.” The ability to deliver “billions of impressions” for a campaign is not something B2B ever needs unlike many consumer marketers.  Yet programmatic’s brute, muscly impression pushing machine grinds out any nuanced precision that is critical for B2B marketers.

Solving this issue requires some imagination for now until the programmatic system stabilizes (it is still in its infancy as platforms go). In the meantime, here are some stop gap measures:

  • B2B should think of programmatic as the opportunity to automate optimization efforts, not as a way to uncover lower cost CPM (though that might happen)
  • Over time, header bidding, while not new in itself, will bring many niche publishers into the programmatic ecosystem relatively quickly. Keeping up-to-date on this trend can give B2B marketers new programmatic inventory that’s very targeted.
  • Include “learning KPIs” in programs so that whether campaigns “win or lose,” the brand gained new learning to optimize the next round

4) The fallacy of audience targeting for B2B

No matter the ad tech platform, algorithmic targeting promises precision to deliver the “right time/ right place/ right message…” benefit to advertisers.

Who can argue with that until you start unpacking the core model for B2B and then the gaps become plain as day.

The basic structure of most targeting technologies (allowing for some oversimplification) rests on a demo profile using basic attributes like gender, geo, education etc. This target is then enriched with external data (usually via DMPs) to add “precision” like keywords or device awareness or “interest categories” – a fairly broad set of classifications that all keywords are categorized under. Optimization occurs as the algorithm learns which profiles do the most clicking and continue to go find more of those high clicking profiles.

There’s a lot to love about this tech if you are a B2C marketer, but unfortunately this model fails apart at the outset for B2B and goes downhill from there.

  • B2B audiences don’t fit into any “standard” demographic profiles such as gender or income. Even attributes like “title” are not easily applied to B2B
  • Using demographics as the basic targeting foundation does not reflect real time intent of users. This explains why we see so many ads for serious white papers on silly sites with cute kitties.
  • The ability to target by topic (not keywords mind you) is a proven strategy for B2B marketers, yet this capability is highly constrained to fit narrow “interest classifications” ala Google or the content syndication networks. The current level of “interest targeting,” quite literally, is “off topic” for B2B audiences given these categories’ very consumer orientation.

To solve this gap, the key is to look for content tech players who are integrating topics with programmatic ad tech and sentiment analysis with social publishing. Context for B2B is the inverse of B2C. Topics come first and then selected demographics – such as geo.

The new age for ad tech seems to have left B2B mired in an ecosystem that doesn’t fit them well. Yet, with $77 Billion in digital media spend, B2B deserves some serious respect.  Hey Silicon Valley – are you listening?

 

The Kuhn Connection

(Or what a scientist from 1962 can teach us about ad tech in today.)

In a moment of frustration after meeting some potential tech partners who seemed not to sense that going forward, ad tech will be about the “how” – not the disruptive “wow,” I wrote a post in Ad Age explaining the importance of operational structure in ad tech: “Here’s the only marketing trend you need to know for 2016”.

While my arguments were lost on the tech folks, the article struck a nerve with Ad Age audiences because it expressed a deeply felt marketer frustration that tech is just too damn dominant in the ecosystem, making a marketer’s job just too hard.

I go on to suggest ad tech is overdue for a “paradigm shift” itself that can disrupt the colossal mess of complexity, fraud and technological black boxes that is now ad tech.  My conclusion is that in 2016, “…marketers will replace the “awe” of algorithmic magic with awe-inspiring new questions about how (not if) we balance ad tech with the art of marketing.”

The groundswell of community support for the post was overwhelming. Amid the inbound, there were tons of questions curious about Thomas Kuhn and secondly, which solutions will realize the promise of integrated user experience out of the current ad tech operational chaos.

Therefore, to answer these questions, let’s take a 50 year trek through the historic evolution of paradigm shifting and the disruptive innovation myth so we can see just how ad tech is about to get disrupted itself (and by whom).

Thomas Kuhn – the Father of Paradigm Shifts.     

Thomas Samuel Kuhn was a noted American physicist, historian, Harvard professor and philosopher of science, who published a highly respected book in 1962 entitled: “The Structure of Scientific Revolutions.”

The oxymoronic title of the book alone alludes to its quirky nature but does nothing to hint at the profound impact the book was to have in its day and for the next 5 decades.

When Kuhn was working, the 1960’s were tumultuous and exciting times with many major scientific advances being made in rapid succession. Kuhn undertakes, with profound scholastic discipline, to lay the groundwork for how the scientific community can standardize revolutions; using the well-known term “paradigm shifts;” so they are responsibly vetted before being unleashed on the public. Kuhn didn’t invent the term paradigm shift, but he gave it a specific meaning so it could become the foundation upon which scientific progress can rest upon with confidence.

Kuhn was deeply concerned with ensuring that scientific advancement is based on solid evidence and not wild conjecture or speculation. His emphasis on structure (as in the title) reflects Kuhn’s deep ambivalence about the concept of paradigm shifts. Paradigm shifts for Kuhn were extraordinary events that can only occur when there is an increasing number of paradigm-busting anomalies that challenge known paradigms.  He fully appreciated their fundamental place in scientific advances; “[A paradigm shift] represents a shift in the problems available for solutions … transforming the imagination to change the very nature of how the work is done.”

But he advised caution because: “Almost always the men who achieve these fundamental inventions of a new paradigm have been either very young or very new to the field whose paradigm they change.” This was the scientific version of; “Ah – all these young whipper snappers with their crazy new ideas.” Kuhn was the ancient age of 40 when his book came out.

Kuhn’s Legacy  

Kuhn understood that science was just smart enough to be truly dangerous. He articulated the process for advancement that spoke to generations of scientists because it delivered the needed framework for establishing responsible scientific advancement given the haphazard and dangerous nature of paradigm shifting. His established hallmarks for managing a paradigm shift are:

  • Default position is trust in the current paradigm the scientific community has accepted (“normal science”) even in the face the unexplained anomalies
  • If the number of anomalies continue to increase especially as a result of new data, then the scientific community must reach new agreements about how to measure the characteristic of the anomalies. Note – there is no paradigm jumping going on yet – but a simply a community consensus on how to accurately measure the results observed.
  • Vetting of scientific results must include peer reviews and repeatable results from independent experiments
  • Once community verified, the new paradigm is accepted by the community and thus becomes the “new” normal science
  • “rinse and repeat” …

These principles are widely and rightly credited with the creation of well-established methods and processes for managing paradigm shifts. Kuhn puts tremendous responsibility on the shoulders of the scientific community; “As in political revolutions, so in paradigm choice—there is no standard higher than the assent of the relevant community… This issue of paradigm choice can never be unequivocally settled by logic and experiment alone.”

All this structure allowed the 1970s, the direct heirs to Kuhn’s ideas,  to be considered the Scientific Golden Age. More than that, Kuhn’s principles gave us nothing less than our very high standard of living because scientific breakthroughs could safely developed and adopted.

Clay Christensen – the Father of Disruption Innovation  

Kuhn may have deeply impacted everyday life but he remained obscure to most folks until Clay Christensen who, in 1997, published the run-away best seller business book called:  ‘The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail.” It was a roadmap for how businesses take “paradigm shifts” (from Kuhn) and create a competitive advantage through “disruptive innovation.” Failure to ride the disruptive innovation wave, the book cautioned, was likely to put a company on the path to destruction. Disrupt or be disrupted became, arguably, the first mega business meme.

At its core, Christensen’s idea rests on Kuhn’s concept of paradigm shift but it was recast in a decidedly sleeker package:

  • Identify those paradigm shifts likely to change industries
  • Create the disruptive innovation to capitalize on the paradigm shift
  • Automate everything so you can produce a product at a lower price with lower but acceptable quality
  • “Rinse and repeat” so as to maintain competitive advantage

Christensen astutely provided stress relief to business leaders who were reeling in the chaos of the 1990’s digital revolution with his “silver bullet” answers to complex problems. The 1990’s were a “Reality be damned as long as it’s disruptive enough” kind of decade.

An important side note is to recognize that in the 1990’s, many future VCs were cutting their teeth at organizations where the Disruption Myth was a widespread, accepted business strategy. As we will see, this plays an important part of our story.

What’s different between Kuhn and Christensen?  

The decades when Kuhn and Christensen were influential had many similarities. Generally speaking, both decades saw major technological advances; the 1960’s focused on industrial scientific advancements and the 1990’s digital revolution kicked off on August 6, 1991 when: “Berners-Lee posted a short summary of the World Wide Web project on the alt.hypertext newsgroup, inviting collaborators.” (Wikipedia). Just a few years later, Amazon and Google launched and the digital revolution attracted investments to anything “dot com.”

Whereas the decades themselves strongly paralleled one another, each man’s response was quite different. For Kuhn, a clearly paid out process for integrating new ideas into scientific knowledge was critical. By contrast, Christensen’s model was more concerned with the “big” concept around the importance of disruptive ideas, leaving big operational (yes – structural) gaps in his theories.

  • How was one to define a paradigm shift?
  • How do these disruptive innovations get incorporated into existing business models?
  • What were standards for measurement?
  • Could technology be duplicated so that it was transparently verifiable?

These and many other questions remained unresolved in Christiansen’s theory because he offers no framework for the industry’s development and evolution for disruptive innovation.

In practical terms, this meant and still means a lot of bumbling around in pursuit of the disruptive idea. Christensen’s meme did what every good meme does – go viral and in the process become a “truth” upon which almost all technological disruption since must rest.

Reality be damned.

In Disruption We [shouldn’t] Trust

Kuhn’s legacy is our trustworthy system to integrate new scientific ideas into our body of knowledge which has helped commercialize many new technologies; improving our standard of living decade after decade.

By contrast, while Christensen’s book itself was financially successful, it seems his theories were not. Probably because of its popularity, it took nearly 17 years for anyone to actually pick apart the math behind the Christensen’s work. Jill Lepore, a professor of American history at Harvard University and chair of Harvard’s History and Literature, analyzed the data behind his theories and scathingly observed in her 2014 New Yorker article, The Disruption Machine: What the gospel of innovation gets wrong:   “Disruptive innovation is a competitive strategy for an age seized by terror …founded on a profound anxiety about financial collapse, an apocalyptic fear of global devastation based on shaky evidence.” She continues; “Most big ideas have loud critics. Not disruption. Disruptive innovation …has been subject to little serious criticism,”

Lepore’s goes on to challenge the underlying assumptions about the disruption myth and wryly notes that the investment fund established by Christensen using his principles was a total failure and shut down.

While Christensen spoke to the angst many business leaders felt, he left out any process for vetting the new technologies that were flooding the market. We can’t chalk it up to coincidence that the “dot com” bust happened just three years after Christensen’s book was published, washing away many disruptive Internet ventures. In other words, our faith in disruptive innovation to build sustainable business is as real as a unicorn in the forest.

Christensen’s Legacy Haunts Ad Tech Today

To this day, ad tech continues to live in the shadow of the Disruption Myth, trapped there by an investment community that believes unblinkingly in the ideology of disruptive innovation, largely I think because of their early exposure to Christensen’s model. This devotion shapes what and who VCs invest in, with blinders on as to the effect the tech has on marketers (agency and advertisers). This Ad Age post I did called, “Why Excluding Marketers from the Ad-Tech Boom Is a Failed Strategy” (April 30, 2015) laments the flood of “cool” ad tech that is increasingly detached from the real world of marketing. “My anger swelled at the scope of the marketing efficiency devastation. And my frustration knows no bounds at the abundance of tech “products” with an appalling lack of “productive” solutions. Mostly though, we lack systems where everyone has a chance to benefit — investors, ventures, advertisers, agencies and of course “Judy Consumer.”

The vestiges of the Disruption Myth that continue to haunt ad tech today are:

  • VCs who continue to fund ventures based on their disruptive algorithm or automation platform without considering how the technology lives within the marketing ecosystem
  • CEOs with little or no direct experience in the industry who create disruption without necessarily creating value for marketers
  • The community of marketers that has largely been marginalized leaving the disruptions to be shaped in the VC/ tech echo chamber
  • Measurement standards that are “best we can do” – not the best that can be done
  • Lack of transparency fed by the “black boxing” of disruptive tech

On a human level, Christensen’s legacy means that if you work in marketing today, you are in peculiar type of hell. You appreciate the potential of digital marketing to build businesses yet you’re frustrated at the chaos and corruption of ad tech that is built on pillars of impressions sand funded by disruption-obsessed VC money.

Marketers are reeling from trust issues; between agency and advertiser and between brands and digital audiences. They are reeling from attribution issues and most challenging of all – they are overwhelmed in understanding how measure the artistry of marketing into the ecosystem as an equal partner to the technology. This is why the word “bust” is not far from the lips of any investor in ad tech in a “history repeating itself” déjà vu moment evocative of 2000. But it doesn’t have to be that way.

Slaying the Disruptive Innovation Myth.

Till 2014 or so, marketers were all too happy to take a hands-off approach, leaving the geeks to work it out amongst themselves. Marketing trade organizations belatedly scurried to catch up, by that time, the VC disruption die had been cast and tech disruption obliterated any investment in marketing artistry or operational excellence.  Marketers had very much lost control of their own industry.

Reality be damned ads long as it was disruptive enough.

By 2015, though the “disruption” cracks were becoming gaping holes as marketers struggled even more in the fragmented ad tech landscape. An Entrepreneur article I did exposed the high cost of ad tech to people: “Disrupting the Disruption Myth” (August 2014) My aim was to crack open VCs narrow definition of what a disruptive venture can be, using Xiaomi’s (pronounced SHOW-me) phenomenal growth as a prototype of a wildly successful venture without any disruptive tech in sight.

Back in 2014, I may have been just one voice, but by 2015, there was a growing chorus of marketing voices demanding ad tech disruption be about human disruptive technology.

Looking for Disruption in all the Right Places.

If Kuhn had been writing in the 1990’s instead of Christensen, I suspect the ad tech landscape we have today would have been far different. There would have been “community” due diligence around how a disruption is an improvement over existing approaches.  There would have been peer review to establish standards to describe these approaches. And most certainly there is would have been vetting process ensuring that potentially deeply invasive technology is used responsibly and to serve people well.

But as it was, the technologists and the “disruption myth” devotees at investment firms, have been in charge for the last five years with pretty much a free hand to “disrupt” at will. Now that many ventures are struggling – even the high flying ones, many VCs and technologists are scratching their head wondering what went wrong.

Any marketer can tell you. The only thing that ad tech really disrupted is the human element of marketing; so crucial in the creation of meaningful connections between brands and audiences.

That’s why going forward, there will be a new paradigm in marketing where the “how” is more valued by investors than the disruptive “wow.” The ventures emerging will create innovation specifically geared to balancing the art and science of marketing within a structured model of transparency, vetting and measurements. From 2016 and on, the community of marketers will be far more active in creating and assessing the disruptive value of new tech as disruption will mean innovation that drives genuine progress.

Ad Tech Disruption in the Future

By now, we can appreciate how the structured approach to “paradigm shift” that Kuhn imagined, was morphed by Christensen into a non-structured disruptive myth ideology that for ad tech, means a lot of chaos and operational dysfunction.

In 2016, the disruption dust cloud will lift, allowing clear heads to pivot; abandoning their reliance on tech-based disruptions in favor of ventures that focus on operational ad tech as their innovation.

Strategically, these ventures will share some common characteristics that are Kuhn inspired, distinguishing them from their Christensen-imbued predecessors:

  • The distinct lack of disruptive “wow” or black boxes in favor of an operational analytical “how.”
  • Abandoning the near sacred MVP (minimum viable product) model of most ad tech startups in favor of a new MVP = Maximum Valuable Product. Consumers are very sensitive to subtle changes that can occur in frequent platform iteration causing changes to expected campaign ROI.
  • New “outcome-based” SaaS models as marketers begin to drive better contextual experiences through new contextual tech AND processes.
  • Engineering obsession around a highly satisfying and frictionless user experience without ad tech compromise.
  • The financials of these ventures will be realistically investable but also sustainable by the industry. Plainly put, today’s current VC expectation that ventures achieve 60%+ margins is unrealistic causing much of the click fraud that is weighing down the industry.
  • Their leaders will likely be experienced marketers rather than 20 something tech geeks. Marketing is as much about processes as it is automation. It takes real world experience to create that merged vision of art and science.

And the winners are…

Taken together, we will see a blossoming of ad tech over the next five years in various industries and functions making these ventures interesting (and dare I say disruptive):

1) Healthcare as an industry is going through a “retailization” transformation that is largely about creating user responsive systems and services. This is, for the healthcare industry, a paradigm shift as the industry moves from “fee for services” model to an outcome based model.

A host of disruptive marketing technologies will burst onto the market from innovations around wearable tech to tackling the mountains of medical/ provider data. Healthgrade (http://www.healthgrades.com/) is an example of a company working on wrestling all this data into a user friendly format. Today, they help about 1 million people a day make sense of the vast amounts of doctor and hospital data (like reviews) available all customized to meet the needs of that individual. They plan to expand to power better ways for consumers to manage medical expenses through aggregating medical information, offering product information and making it transparent for the patient to decide while managing users’ online security.  Ultimately this, like other ventures in this space, rely on an excellent user experience.

2) Direct marketers are likely to be winners in the new ad tech disruptive game because they are making the leap to deliver personalized experiences where tech supports the very human side of customer acquisition and retention.

Going forward, direct marketers will expand their email/ database capabilities into new marketing cloud offerings like Bombora (http://bombora.com/products ) who; “Aggregate. Organize. Activate.” data to make it incredibly useful for B2B marketers across business applications.  Cue Connect (http://www.cueconnect.com) is also interesting because it takes a “direct” product level approach to helping retailers stay connected with customers and create excellent user experiences. Their online platform gives retailers new insights and tools to provide a better, integrated on/offline shopping experience for their customers using products level (not the more typical user level) insights based on their behaviors (i.e. – share or saving as a favorite).  This product centered approach reflects a sensitive understanding of “how” real people shop for stuff – the “wow” is there but it’s not the point.

3) Content marketing is on ascend almost in direct inverse proportion to the degradation of CTRs on many forms of display advertising.

Today though, this category of ad tech is a messy, fragmented, incomprehensible landscape of content creation, social publishing, sentiment tracking and on. Each venture, eager to be disruptively investable, went deep into a functional silo leaving the marketer with a dizzying myriad of options that don’t play together too well. Native, just one form of content marketing, is an example with its dizzying array of networks and “platforms.”

Disruption here will revolve around ability to deliver true relevant brand messages through contextual advertising technology that will be well-defined; merging human creative process with programmatic RTB technologies. Our venture is an example in this space as we link data related to content and RTB programmatic advertising. Another example is Kargo, a great mobile venture that excels at amazing, rich and personalized video experiences.

4)  The massive business called TV will be (finally) disrupted with the arrival of VR (virtual reality) in 2016 and Apple TV which will drive the final nail in the old world TV distribution model. The paradigm shift here will be the reverse of control from broadcasters and content providers to individuals where video streaming, gaming, shopping are all delivered seamlessly across devices.  It is likely that TV disruption will come from the mega networks (ie Facebook) as any large tech company (ie Samsung).

The way forward depends on the human element.

Current marketing chaos is rooted in an excruciatingly unsustainable model imposed on marketers by VCs who limit their vision to disruption described with words like scale, algorithm and SaaS anything.

But now the alarm bell is ringing in everyone’s ears because more money is spent on more tech, yet marketers are getting less done and investors are getting less returns.

We can do better and Kuhn showed us the way.  In 2015, marketers have experienced a paradigm shift of their own in the form of community unity propelling marketers to take back control from the technologists. Redemption will come from discarding the unproductive Disruptive Innovation mythology from our thinking (it may take VCs longer to let of this cherished tenant) and replacing it with a disciplined process as Kuhn imagined but coupled with a new sensitivity around the need for practical solutions that allow marketers to create new user experiences.

2016 will see the triumph of marketing brains and art over pure disruptive tech brawn. I’d like to think would Kuhn be proud.

The Facebook Experiment

Recent research findings confirms what everyone knows. The more you use Facebook – the less happy you are with your life because you are constantly comparing yourself to other FB people (most of who always seem more successful or happier than you)

Read the results for yourself. The Facebook Experiment

‘Go Small or Go Home’ Is the Next Big Thing in Ad Tech

[This post first appeared in Ad Age – 3/17/15 – http://adage.com/article/digitalnext/small-home-big-thing-ad-tech/297601/]

“Go big or go home” is the mantra that drives the current ad-tech gold rush. It refers to the prize that awaits ventures capable of scaling their audiences — the faster the better — guaranteeing huge ad budgets in the rapid shift from traditional to digital media.

Advertisers, for their part, were seduced by ad tech’s undeniable appeal for “predictable” marketing — devoid of quirky, error-prone human intuition. Powerful ad-buying platforms promised billions of impressions, delivered faster and cheaper than ever before.

But, as in every other gold rush, a few “unicorn” successes don’t guarantee a sustainable ad-tech industry. The recent weakness of some high-flying ventures like Say Media, which is scaling back, Sulia, which shut down, or Rocket Fuel, post IPO, reflect how underwhelmed advertisers are by the performance of “scalable” ad-tech platforms.

Their disappointment is well-founded. Ad tech’s performance paints a sobering picture, demanding a critical look at the “scale” game.

There’s rampant ad fraud driven by arbitrage incentives endemic throughout the ad-buying process.

There’s shocking low quality to all the billions of impressions delivered, frustrating advertisers’ desire for quality engagement with real people.

All these symptoms are the toxic results of the unbridled drive to scale. Ad tech confused the internet’s ability to scale technically to billions of digital nodes with marketing’s desire to reach billions of people. This colossal “bait-and-switch” scale game left advertisers deeply mistrustful of ad-tech, as all those algorithms stomped on the very human and delicate brand/consumer digital dance. This leaves us with retargeting ads that follow us relentlessly and banner ad blindness that’s more acute than ever.

It’s time to put people first

What’s going to make it right? A fundamental shift that replaces our slavish devotion to “Go big or go home” with a focus on innovation that delivers human-scaled, “people-first” digital marketing.

Believe it or not, this “people-first” vision was the foundational inspiration for the very earliest, heady internet days, circa 1996. We felt giddy at the possibility of experiencing a personal, human-scaled internet — an internet of “me.”

This was the era of Yahoo’s exuberant “Do You Yahoo” tagline with a whimsical personal portal expressing the joy implicit in its name. AOL, MySpace, Google and Amazon all glowingly promised us digital agents that could fulfill our every digital desire. Scale back then meant internet-powered individual “Judy consumers,” but lots of them, who all controlled their own experiences.

Alas, the technologies needed to deliver that noble vision were decades away. In the intervening 20 years, that personal internet vision got lost in a sea of scale.

For those of us fortunate enough to have experienced those early, wondrous internet days, we know that social, content and mobile tech can now realize the promises made so long ago of a “people-first” internet. As “Judy consumer” continues to strengthen her digital muscle, scale must expand to also include the technological expressions of human dynamics like relevancy, trust and contextual engagement.

Practically speaking, the ad-tech landscape will look quite different than today. Here are some trends that will drive the next era of ad tech:

  • The internet is a content-serving engine that, increasingly, will reward those ventures that can deliver hard-to-find niche topics integrated into local search, local commerce and hyper-topic digital communities.
  • The emergence of engagement-based private exchanges with quality, albeit smaller, audiences.
  • Metrics will evolve to be smarter around “intention” and “attention” of audiences.
  • The introduction of “pull” or opt-in marketing platforms that deliver real people ready to engage (don’t look for a billion anything in these platforms).
  • Programmatic technologies that can interpret the correct context throughout an offline/online user experience.

For those with the courage to push the redo button, “Go small or go home” will be how the next wave of ad tech will evolve into new marketing tech ventures of tomorrow. These ventures will get very big indeed.

The Marketing Measurement Maze: measuring marketing is a mess.

Wow – I kvetched about the marketing metric mess back in 2010. I was right back then. Alas it is far worse now. *sigh*

Trenchwars Weblog

Forgive the illustrative nature of the headline  – but I had to laugh out loud about this whole thing or else I would cry.

This post is a follow up to my previous post about how fragile measuring marketing technology really is based on a real time experience I was having with Technorati regarding the authority ranking of this blog.    Unhappily, my initial concerns about marketing measurement were realized so it is worth recapping.

About a week ago, by accident, I learn that according to Technorati this blog, getting a mere 1,000 visitors a month, vaulted 4x in authority rankings to about 400 when previously I ranked about 100. For about a week, I jumped up and down a few times going between 400 and then 600 (see pictures in my previous post).I contacted Technorati and told them I think there is a glitch. I got a very polite…

View original post 329 more words

7 schizophrenic traits every startup CEOs must adopt

Trenchwars Weblog

CEO PSYCHOSIS The role of CEO is often described in gauzy, glowing terms espousing passion mingled with ambition that runs deep enough to change the world. All this noble ambition belies the uncomfortable reality that the inner world of a start-up CEO is often a constant state of conflicting realities that can distract from the mission at hand.

This list reflects my personal experience as the CEO of a social commerce startup. I can tell you – the dual reality can be disconcerting at first but after a while it gives you a certain edge that makes you tougher and smarter the longer you stay at it.

1) Your vision must be out there enough to generate investor interest but not so out there so as no one knows what you’re talking about. We’ve heard it from the pundits a lot – be different, don’t just iterate on another idea. Gotcha but then…

View original post 594 more words

Why did social media become so urgently important right now?

So much has happened in social media since this was written in 2010 and yet the operational model for how companies leverage social marketing as still as fuzzy now as then. *sigh*

Trenchwars Weblog

Nowadays, I sometimes feel like the doctor who is often asked his advice “off duty”. Once I say I am in marketing, the inevitable questions begin. “How can I launch a product with just social media?” (You can’t). Is social media really free? (No). Can I be successful at social media without an agency (yes…but). This is not just mere curiosity; there is urgency to the questions I have not encountered before.

Now aside from the inconvenient truth that I am practitioner of marketing and perhaps not an “expert”; the other inconvenient truth is that there aren’t many experts to found anywhere because social media has barely been on the corporate radar for 24 months and it is very fast evolving category of marketing that is growing in importance. This expertise gap understandably makes companies scrambling for advice with a frantic energy approaching panic.

So with that perspective, let’s return…

View original post 630 more words

Follow

Get every new post delivered to your Inbox.

Join 2,663 other followers

%d bloggers like this: