networks

Data: the oil which lubricates the network

In Hardt and Negri's seminal writing, Postmodernization, the authors described the digital area as a paradigm in which "providing services and manipulating information are at the heart of economic production." We can see this play out when thinking of the most successful and dominant players in today's market - Google, Facebook, Apple, Amazon, Netflix, Spotify, etc. Each of these firms provides services (and sometimes product goods) which connect nods (that would normally be disparate) to create more customized experiences. Things connected to other things. Things connected to people. People connected people. Digital facilitates the network which connects nods that otherwise would be disconnected and data is the oil which lubricates these networks. Today's dominating technology extracts the data we passively shed in our day-to-day actions -- research, communications, movement, consumption, commerce -- to optimize our day-to-day lives, helping us make better decisions through the benefit of collective intelligence. Make no mistake, this is not without its tradeoffs, of course. Just like anything else, there are both positive and negative consequences to these technologies and their ability to "provide services and manipulate information." That said, here is one of the coolest examples I've seen lately where data was used to lubricate the network and provide utility to the people.

Ever visited a city and wondered "where should we eat?" In most cases, you try to avoid the chain restaurants because the Olive Garden in NYC is likely the same as the Olive Garden back home. Instead, we venture to fully experience the culture of that city through the tapestry of its cuisine. You know, eat like the locals. We consult Yelp and curated lists from blogs to find the best places to dine in the city. But what if we could use the data people shed as a proxy to find the best spots based on where the people actually go? Apparently, the folks at Crimson Hexagon -- an AI-powered, social listening technology company -- wondered the same thing. To illuminate this curiosity, Crimson used its platform to identify the most popular foods and drinks in New York City on Instagram according to the use of associated hashtags. They gathered the posts containing those tags in the five boroughs over a period of time and visually represented where the true 'hot spots' are in the city. 

Full transparency, Crimson Hexagon is both a close colleague and friend of mine. That said, it does not bias how cool this active truly is. Check it:

Created by Crimson Hexagon

State of the Advertising Industry: The Music of Disruption

Bob Dylan once sang, “The times they are a-changin’.” This premise is truer than ever in today's marketing and advertising world.

Advertising firms were once the authority on idea generation. They were the best mass storytellers and the best attention-grabbers. They were the modern day Don Drapers.

But that isn’t necessarily the case these days. The ubiquity of new technology means anyone with a phone, tablet, or computer is now a content creator. The pervasiveness of social media propagates these ideas from person to person. Meanwhile, new analytics capabilities empower anyone with an affinity for quants to direct placement and inform content creation.

All of which adds up to less power for traditional advertising firms and sets the stage for disruption that will fundamentally change the way we do business — and soon.

Sound too apocalyptic? Just look at the music industry.

As recently as the early 2000s record labels ran the show. They funded handpicked hitmakers for long sessions in big, expensive studios. Top-notch sound engineers guaranteed pristine sonic quality and A-list directors were hired to make lavish, over-the-top videos. Singles had long given way to albums with “filler” songs, meaning fans wanting a hit song had to cough up $17 for the entire album.

Business was booming until a viable alternative came along — the world wide web.

The Napsters and Limewires of the world, and ultimately Youtube, iTunes, Spotify, and Pandora, ushered in the disruption in music in a newly networked world.

Here’s why history may repeat itself, this time with the advertising industry:

Ubiquity in Technology. The spread of broadband internet and CD burners allows more and more people to experience free music access (peer-to-peer exchange). For advertising, the devices in our pockets, bags, and desktops allow anyone to be a content creator, not just a consumer. A clever creative talent with an iPhone can legitimately create content for a brand without the overhead of a Madison Avenue ad agency.

Medium Shift. The product the music industry was selling — CDs — was no longer the medium people wanted. CDs were a secondary medium to the music itself. Likewise, advertising was once dominated by TV, print, and radio. Today content relevance is far more important than the channel by which it was delivered. In fact, there's often more credence awarded to content delivered via Facebook, Twitter, or Youtube because it was curated for me, by my people.

Access to Tools. Programs like Fruity Loops and Cakewalk reduced the financial barrier once presented by expensive recording studios. In advertising, firms once provided access to expensive software like Photoshop or InDesign that now can be accessed for free from Reddit or BitTorrent.

Decreased Learning Curve. The web allowed music makers to learn from each other, which reduced the need to apprentice for years before ever creating anything. Today social networks allow idea generators and content creators to share learnings about the craft, instead of being an apprentice at a big firm.

Democratization of the Internet. Broadband internet removed the middleman — radio, MTV, etc. — and allowed these new, non-major-record-label producers to reach music fans directly. Advertising content also needed TV, radio, and newspapers to be seen. Today social network platforms, search engines, and email allow non-agency content creators to reach the public directly.

Content Parity. It turns out people were fine with the varying quality of MP3s. Expensive sonic quality ceased being a discriminating factor for music fans, which leveled the playing field for amateur musicians and producers. While ad agencies tap big directors to shoot over-the-top productions for expensive media campaigns, the content that gets people talking the most is produced by amateur makers. It doesn’t seem to matter that it’s a vertical video shot with an iPhone. Production values are no longer a key differentiator.

Distributors as Arbiters of Value. The launch of iTunes told the world — and the buying public — that it didn’t matter if a song was recorded in fancy studios or in someone’s bedroom with free software. It was all 99 cents. Big ad agencies charge for the time it takes to create content while publishers like Buzzfeed, Complex, and Vice charge per piece of content, not the time it takes to make it. Again, all content is valued the same no matter the investment to create it.

Bypass the Traditional System. Online music outlets like iTunes, CD Baby, and TuneCore allow amateur musicians to reach customers, often sitting shoulder-to-shoulder on the screen with some of the biggest names. In advertising, brands needed agencies to do the content work for them. That’s not the case anymore. Outfits like Maker Studio have amassed thousands of content creators worldwide and use technology that makes it easy for brands to manage campaigns. No agency needed.

Overwhelming Supply of Content. The influx of so much content in the market, from amateur content creators to superstars, with reduced time between album releases, means there’s more desired music than there is time to consume it. That greatly reduced the half-life of a song. Same is true in advertising. There’s so much content in the market now that brands see a greater supply of content than they need.

Access Over Ownership. The oversupply of content means fans don’t feel the need to own music anymore. They want to hear music they like on demand. Likewise, brands are wondering why they need advertising agencies. More brands are writing “jump ball” briefs to access the best ideas from a wide variety of potential partners — traditional agencies, YouTube stars, or aggregators. The agency model is no longer a very smart model for big brands – except the biggest brands and companies that require a factory-like agency to manage the enormous flow of content; think Ford and Procter & Gamble.

These implications have led to new vehicles for discovery (Facebook, YouTube, Snapchat), consumption (Vice, Complex, Buzzfeed), and creation (Maker Studios and Social Native), which sets the stage to disrupt the status quo of the advertising industry much like the music industry.

It won’t be long before more brands start to wonder, “With so much content being produced in the world, why would I reduce my access to it by having just one agency responsible for making it?” And perhaps more importantly, brands will soon say “With such a high amount of content available to me, why am I paying so much for it?”

Indeed, the times they are a-changin’. But there is hope. As the advertising and marketing world around us changes, we marketers and advertisers must change also, and these changes require us to reconsider the role we play as agency partners. Perhaps the best way to offer “agency” would be for agencies to move from being outsourced creative hands to true brand partners. Only time will tell.

Unlocking Networks: Want to truly understand people and make accurate predictions? Look at their networks.

It’s been said that good marketers see consumers as complete human beings with all the dimensions real people have. But do we marketers really understand people?

For decades we used demographics to identify and segment groups of people in an effort to create better products, serve relevant messages, and forecast more accurate predictions. This is the holy grail of marketing.

But demographics don’t describe “real people.” While gender, race, age, household income, and other demography-based inputs are “truths,” they are static facts and do not accurately describe who people truly are. This, of course, is why savvy marketers focus their segmentation efforts (to whom they target their messages) on psychographics — people’s interests, preferences, and attitudes — because they paint a more vivid picture of "real people.”

Now we’re getting somewhere, but not close enough because psychographics are merely byproducts of our networks. And networks are much better indicators of who people are, and what they are likely to do. 

Let’s unpack this further.

By “networks,” I mean the groups of people with whom we exchange information, experiences, and behaviors: friends, family, classmates, co-workers, teammates, congregates... our people.

And our people give insight to who we are and how we see the world. Within each of our networks are shared beliefs, unwritten rules, rituals, and social norms that guide the behaviors of the people in the network. As Aristotle said, “Man is by nature a social animal,” and these dynamics are the glue that keep our people connected. 

Much of our daily life is governed by norms — unwritten rules we follow to remain community members in good standing. As such, our interests, proclivities, and actions tend to follow the way of our networks and spread in a predictable and contagious fashion.

Our networks inform our psychographics. Therefore, not only are our networks more powerful descriptors of who we truly are than typical demographics, but they are also more holistic representations of ourselves than psychographics alone.

Unfortunately, traditional marketing segmentation misses the mark. Common practice identifies groups of people based on demographics (with a bit of psychographic seasoning) and buckets them into target audiences — a group of passive people waiting for marketing messages to wash over them.

But people aren’t passive, and audiences aren’t real, so this approach often leads to broad generalizations and trite overtures. Peek into most creative briefs, and chances are you’ll see brands targeting “millennials,” as if everyone between the ages of 18-34 are the same because they were born within the same generation. It just isn’t so. As a result, marketers make blanket generalizations about a cohort of dynamic people, and the subsequent work often falls flat.

What a waste.

Networks, on the other hand, are dynamic, human, and innately social. And people use their networks to describe themselves. Take me, for example. I’m a Collins, I’m a Michigan Wolverine, and I’m a non-denomination Christian. I subscribe to these networks and take on their respective characteristics to stay in good standing with my people — as we all do with our own unique networks.

Understanding the dynamics of these networks is the gateway to consumer intimacy and relationship development because these groups of people are, in short, real. Marketers would benefit greatly by shifting their focus from talking at passive “target audiences” to engaging with active “target networks.”

Even more interesting, networks are also more accurate indicators of what we’re likely to do. This is heavily supported by behavioral science research. Humans are naturally inclined to take on the actions of the people around us, so much so that our behavior can be predicted from exposure to the example behavior of others. And we are most influenced when we observe the behavior of people most like ourselves — our networks. That means if brands can understand the dynamics of my network, then not only will they better understand me, they’ll also be able to predict my behavior with a high degree of probability.

Now that’s powerful. 

These predictions are driven by the natural propensity that people have to rely on one another. We’ve built trust within our networks and rely on their expertise and experiences to help inform our decisions. In fact, research shows that we trust the recommendations of our people more than any form of advertisement or media.

The collective intelligence of our networks help us decide where we go, what products we consume, who we vote for, and which brands we choose. As a result, our consumption patterns naturally follow that of our networks. Want to predict what people will do next?

Watch the behavior of their networks.

Contrary to conventional wisdom, we are not independent agents in this world, where our decisions are driven by our preferences and IQ. Rather, we live in complex systems — networks of people — where members therein help shape each other’s affects, cognitions, perceptions, and beliefs. We rely on our ability to learn from the behaviors of our people, and they set the example for how members of the network should also behave. These networks move forward on the basis of a simple, subconscious, question: “Do people like me do something like this?”

If the answer is "yes," then we follow suit; if "no," then we don't take action.

We don't inquire.

We don't share.

We don't buy.

It’s that simple. And it all starts with people — real people — and the influence of their networks. This sets the stage for a more actionable approach where brands can deliver ideas, products, and communications in an effort to influence consumer behavior.

Considering the ubiquity of social media in today’s connected world, marketers can now apply network thinking to the use of these tools in a way that promotes social pass-along and enables more accurate predictions.