Seth Godin on New Marketing

24 September 2009

Seth Godin has a new post (“The platform vs. the eyeballs“) up about how marketing used to be about renting an audience (“we want this size of a TV audience at such and such a time”) and the metrics were how many eyeballs did you get or what was the CPM:

You, the marketer, don’t care about the long-term value of this audience. It’s like a rental car. You want it to be clean and shiny when you get it, you want to avoid getting in trouble when you return it, but hey, it’s a rental.

And so when we buy ads, we ask, “how big an audience” and then we design an ad with our brand in mind, not with the well-being of the media company or its audience in mind. And if we get a .1% or even a 1% response rate, we celebrate.

Godin’s thesis is that new marketing focuses on owning the audience and not aiming for a 1% conversion rate but a 90% conversion rate:

Old media was not the same as old branding. Media companies built audiences and then brands rented those audiences.

Suddenly the new media comes along and the rules are different. You’re not renting an audience, you’re building one. You’re not exhibiting at a trade show, you’re starting your own trade show.

If you still ask, “how much traffic is there,” or “what’s the CPM?” you’re not getting it. Are you buying momentary attention or are you investing in a long term asset?

The rest of the post concerns Godin’s ideas on how to build the platform he mentions.  It’s interesting, but the above is what concerns me most since it seems to validate at least some of what I was saying earlier about advertising being a long-term, win-win relationship between the consumer and content providers.  The analogy to renting an audience as opposed to cultivating a long-term audience is quite good, in my opinion.

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The latest edition of FastCompany has an article by Adam L. Penenberg (author of the upcoming book Viral Loop) entitled Loop de Loop which is noted as being an adaptation of the aforementioned book.  While the article is, therefore, ostensibly about social media sites and their viral characteristics, the bulk of the article concerns the advertising implications thereof.  The future of advertising is pretty interesting to me and I have some thoughts on the article:

One assertion the author makes is

“Consumers will tolerate a whole lot of advertising if it’s disguised as entertainment, which is why marketers have responded to the DVR by making TV commercials more engaging–the kind that make viewers stick around–and integrating ads into shows.  The same holds true for the Web, and as with keyword-search ads, the trick is to market to people in a way that doesn’t make them feel like they’re being marketed to.”

I have to say that this seems to miss the point (unless I’m just nit-picking on the author’s choice of words).  The future of advertising is not disguising ads so that people will be fooled into consuming them; the future lies in being painfully honest with content consumers so that you don’t serve them barely-palatable ads but delicious ads – ads that they ask you to serve them.

You want consumers to want to consume the ads you’re serving them.  The way to do that is to make sure you’re always giving them what they want.  The only way to do that is to have a relationship with them, a relationship where there is a two way street of data flowing back and forth.  You allow them to tell you up front what they’re interested in right now, you serve them content (normal content and ads), they tell you what they liked and what they didn’t, and then you start over.

That sounds like a recommendation engine, doesn’t it?  In my mind, the vast majority of ads are just really dumb recommendations served up by really dumb recommendation engines.  The key is to start realizing that Amazon’s recommendation engine is a better mouse trap – a better way to serve up ads.  Once you’re thinking about it that way, it suddenly makes perfect sense to allow customers to (gasp!) rate your ads (Hulu does this, although I think their implementation could be a lot better).  Once your customers are telling you which ads they like and which they don’t, you can adjust the system (or the ad content) appropriately to keep them engaged with the system.

That’s the real danger confronting the advertising industry right now: consumers not only are disengaged from the system but actively blocking it.  It has been posited (one counter argument here, see also the same author’s ideas about what would happen if this were true and note how basically all 10 scenarios assume that ads are inherently bad) that, in a few years, the industry will hit a tipping point where blocking ads becomes so easy that the majority of users will do it.  As soon as that happens, the companies who don’t really understand the underlying issues are just going to put their ads in flash.  I think we can all guess what the users’ next move will be.

Advertisers have to keep consumers engaged in the advertising system – give them what they want (useful and/or entertaining ads), let them give you feedback (which they want to be able to do), and allow them to tell you when they want you to recommend another product or service to them (which they want).

I grant that some really good ads are not good because they recommended exactly what you wanted when you wanted it, but rather just because they were entertaining (think of the Budweiser Frogs and Louie the Lizard campaigns).  Such ads are obviously not the product of a recommendation engine in the sense that a computer algorithm thought that you might buy more X if you saw this funny video clip.  The ad being displayed to you at a particular time and in a particular way, though, can easily be thought of as the product of a recommendation engine: the system knew that you liked brand Y, or really like funny ads, or ads with celebrities and served up content that you found entertaining.  What does the system get in return (since most entertaining ads don’t really generate new sales)?  Two things: 1) data (assuming the consumer feeds back) and 2) a consumer who is just a little more engaged than they were a moment ago.  Both of which are priceless.  What does the brand get from entertaining ads?  The same thing they currently do: brand awareness and a more engaged tribe (in the Seth Godin sense).

The consumer gets what they want, the advertiser gets what they want, and the content provider (the ad distributor) gets what they want.  Advertising in such a model is no longer a zero-sum game where consumers lose (because they are basically forced to consume ads they don’t like), the advertiser might eke out a meager return but risks alienating a larger demographic with an ad that bombs or is just annoying), and the content provider loses since their users’ experience is that much poorer due to unwanted ads.

Granted, if you let users tell you when and how to serve them ads, you’re going to get a) a lot of people saying “never and through no medium” and b) a lower number of ads being consumed even by people who are open to ads.  So what?  Those aren’t the metrics we care about.  The metrics we care about are sales and happy customers.

That’s where we finally get back to the Loop de Loop article:  Regarding Andy Monfried, CEO of Lotame (a social media ad and marketing firm), the article says “For Monfried, an ad’s success isn’t based on how many people see the ad; it’s all about how much time someone spends engaging with it.”  Now, I am taking this quote out of context but I don’t think he and I are on completely different pages.  He is mostly talking about the level of engagement a consumer has with an ad within the context of a social network (and, by extension, how far they are responsible for spreading the ad throughout the rest of the network).  ‘Engagement’, here, doesn’t mean so much acting on the ad in terms of buying something or rating the ad, but rather in helping spread it.  Essentially, the consumer becomes a mechanism within the larger recommendation engine system: they recommend (either explicitly or implicitly) the ad to their friends.

The interesting point that emerges, then, is that the “problem” of not getting enough eye balls on an ad because consumers are allowed to choose not to view it is probably more than made up for by coupling a consumer-centric ad recommendation system with the viral properties of a social network.  In other words: make sure your highly customized, targeted ads “work” in Facebook and on Twitter (1) (2).

The article is good as far as it goes regarding social networking and its affects on advertising, but I think the author missed a golden opportunity to discuss the more fundamental issues.  I look forward to seeing how the book turned out.

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Ponderings

22 September 2009

As I read and think more and more about entrepreneurship, business models, business practices (especially agile project management, product development, and customer development methodologies), and how technology impacts them all, I find myself wanting to write about these topics and ideas that are floating around in my head.  That is what I intend to do here.  Comments are much desired.

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