Category Archives: media

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When Did PR Become This?

(See update at end of post.)

Because I’m not only the “head helper,” but also the “head recipient of email” at SmallBusiness.com, I receive an endless stream of pitches from people with titles like “PR manager.” Unfortunately, most (not all, but most) of the email is boilerplate crap sent to websites that sound like, maybe, they could be visited by small business owners.

Once in a while, I’ll see one of these worthless pitches and recall how long, long ago, I used to run a public relations firm. I can recall obsessing over to whom and how we would pitch a story. We would look for specific angles that benefit our client, but still provide the reporter plenty of opportunity to make it his or her story. I would often suggest people the reporter could talk with to get opposing or competitive sides of a story.

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The Pundit’s Worst Fear: When Facts Don’t Support the Narrative

All week, anyone who follows the news has been carpet-bombed with punditry informing them that House Majority Leader Eric Cantor’s defeat was because he supported immigration reform. Yet now, polls on both the right and left are revealing that immigration reform was far down on the list of issues that influenced the election’s outcome. Reporting on a poll conducted by Americans for a Conservative Direction, Politico says, “Only 22 percent of Virginia residents who voted for Cantor’s opponent, Dave Brat, cited immigration as the primary reason for their vote. About 77 percent cited other factors, such as the Republican leader’s focus on national politics instead of local issues.” (Tip O’Niell was, is, and will always be correct.)

I doubt, however, that such polls will change the narrative related to why Cantor lost. That the hubris and national aspirations of Cantor were the likely causes of his defeat, don’t fit nicely into a bigger narrative that works for pundits and analysts. Those are too nuanced and local…and personal, and don’t fit nicely into a national debate over one issue.

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What You Think You Know About Anything Is Typically Both Right Wrong

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Photo: Thomas Hawk via Flickr

(Note: This is a wonkish marketing/media related post. It started out as a comment, but grew into a blog post. If, even after being warned that it’s marketing/media wonkishness, you still want to read it, this post will make a great deal more sense if, for context, you read the essay linked below.)

“What You Think You Know About the Web Is Wrong,” an essay by Tony Haile that appeared earlier this week on Time.com, is one of those counter-conventional-marketer-think items that I typically find intriguing. And I find much to agree with in it. Unlike Haile, however, I do not think the greatest challenge (or, opportunity) to marketing is re-prioritizing web metrics and placing a new label like “Attention Web” on what, at the end of the day, is just another set of web metrics. I think the opportunity is developing a new understanding of the value of media that can correct those things we think about the way markets work  (and not just about the web) that are all wrong. While I think metrics and data will be at the center of that new marketplace, I don’t think the metrics that will ultimately matter will be “web metrics.”

While I agree with him on much, I’ll point out (as he discloses) Haile clearly has a dog in the hunt (he’s CEO of a web analytics company that has traditional publishers as clients), his findings seem to contain a bit of cognitive bias that enable his findings to line up precisely with those his  publisher-clients would, no doubt, love to believe.

Of course, as I’ve said for over a decade on this blog (as a running joke), “I never trust research or statistics unless they support something I already believe.” So I’ll admit that Haile’s research lines up with some of my cognitive biases also. However, unlike publishers with traditional media business models, my primary professional focus has always been on helping companies create direct-to-customer media channels and the type of recurring content that is mutually beneficial to customer and company. It is media that supports our clients’s various business models; not media that is a business model.

I find much to agree with him on the pieces and parts (or, as he describes them, “small signals and changes”) he uses to build a case for what he calls, the “Attention Web.” However, I believe that term and its description merely re-balance the relative importance of factors in the first-wave of web metrics that marketers and media companies have used to create those things we hate about advertising-supported websites (dozens of things to click, intrusive pop-ups, pageview-churning techniques like slideshows).

hammer-nailsHis suggestions that better design, smarter content and understanding how the web works are all great. But as with Haile’s observation that metrics that measure social “likes” and “follows” merely tell you about social “likes” and “follows,” the analytics he points to in the Attention Web merely reveal how much attention the site receives, or how a user actually “uses” the site, not how that attention relates to sales or how customers and brands interact. Advertising, be it on a website or in its various off-line forms and formats, is but one facet of a complex network of decisions, research, interactions, influence, training, support and on-and-on, that must work together to generate the metrics that relate to revenue for the seller and value for the buyer.

It would be so easy if the only thing that mattered in marketing was figuring out where to place an ad on the page to get more people to pay attention to it…but that’s just one tiny part of the journey from potential customer to owner.

Rather than make a case for finding another set of metrics that only matter to those who care about web metrics, I think marketers would be better served to skip the era of trying to game the “Attention Web” and go straight to trying to serve customers who are more-and-more migrating to an “Intention Economy” where buyers and sellers, owners and creators, causes and supporters form new models of web-enabled, mutually-beneficial marketplaces and relationships.

I think web and traditional advertising, and for that matter, traditional media channels and various channels of the web, will all play vital roles in creating such marketplaces. I agree that much of what Haile describes as the Attention Web is important to understand and use. And I fully endorse his findings on what I know also to be true from scientific research: Top Ten Headlines Generate Clicks to Articles That Aren’t Read.

But embracing the notion of an “attention web” is just another thing we’ll one future day think we know about the web that we will discover was both right, and wrong.

I think my RSS news reader is smarter than your Al Gore rhythm


(Sidenote: On SmallBusiness.com, I’ve written about the new Getty embed feature like the one I’ve posted above.)

The Verge has an interesting take on the acquisition earlier this week of the mobile app owned by CNN, Zite, by Flipboard, another app that does the same thing as Zite, but differently and with greater success (apparently).

Here’s a clip from the piece:

“The premise of apps like these is that they will find interesting articles for you that you never would have seen otherwise….And yet for all the millions spent and the machine-learning algorithms that have been built, none of them have improved on the big portals — CNN, The New York Times — or social networks like Twitter or Facebook, which bring you both the news and the conversation happening around it. Newsreading-app developers hire PhDs to do the easiest thing imaginable — find you something interesting on the internet that you haven’t already seen — and then beat you over the head with it, bludgeoning you with an endless barrage of links that never feel half as personalized as they’re made out to be.”

I especially agree with the writer on two things: (1) Twitter does a good job of finding me things I would have missed if I didn’t use Twitter (along with lots of links to cat videos, but still) and (2) I agree with the premise that PhDs don’t seem to be unlocking the secret of relevancy and context necessary to make their algorithms better than what I can hack together with other tools. It’s much like the way advertising “retargeting” algorithms consistently misinterpret why a web user might surf by a product without having any interest in purchasing it).

Where I disagree with the analysis is this: There is a technology that allows people to personalize and customize a flow of news that’s been around since the Mesozoic era of the web. It’s called RSS and is an often misinterpreted part of the infrastructure of the web that enables us to access content as a real-time flow of news, audio, video, etc. (Despite the never-ending predictions that somehow RSS will die, I’ve written before why that’s never going to happen.)

Ironically, the Verge piece not only fails to mention RSS, it fails to even mention that Flipboard is a self-proclaimed RSS newsreader.

But the thing is…

Flipboard, doesn’t look like an RSS newsreader. The vast amount of coverage it has received (and that’s a vast amount) has focused on its user interface that replicates, in skeuomorphic fashion, the conventions of a print magazine, specifically (thus, its name) the virtual flipping of pages.

I’ve always considered it a bit ironic that web-based tech and media writers would buy into the notion that the ability to turn a page is the killer feature of magazines that should be ported over to the web. I would think, rather, that great writing and graphics that work together to tell great stories would be.

Setting the stage for a real showdown

So here we are in 2014 and we’re still looking for ways that the web was supposed to do something promised to us by Al Gore when he invented the internet: Customize and personalize content and deliver it up to us with our morning coffee and toast.

For a moment, I’ll ignore that this blog has 12 years of me talking about this topic and pretend that we are starting out today and no one has ever actually thought of the hundreds of ways that exist for people to do this. In other words, let’s pretend to be like the Verge article.

Let’s make this a show down between what we will pretend are “brand new” personalized, customizable news catching filters created by people who weren’t around for endless iterations of this concept.

Here’s what we can do to test this brand new, never thought of before, “algorithm vs. human” theory.

(1) First, do whatever it is that you do now to catch up on whatever topic you turn to the web for. (Sort of like what scientists might call, “the control.”)

(2) Set up a TweetDeck account (or use the one you already have) for tracking a few hashtags (Here’s how.). If you are willing to spend five minutes learning to do it, set up some lists of Twitter users or topics you’d like to follow.

(3) Set up a Flipboard account (it’s an iPad/iPhone, Android app) and follow the standard instructions of how you should subscribe to the topics. Some of the instructions will result in you subscribing to an RSS feed, but they (wisely, perhaps) have hidden the “how it works” and are focusing on the “what it enables.”

(4) Set up an account on Feedly.com (an RSS newsreader with an interface and instructions you’ll understand that has an app version and is also available in a browser). While there are other new-fangled RSS newsreaders that are far superior to Google’s now defunct newsreader, Feedly is what I use, so I’m most familiar with its strengths and weaknesses.

(5) (Optional) Set up a Zite account (like, Flipboard, an app) and let their algorithms do their magic. It looks like Flipboard but the test is over the algorithm vs. manually choosing news sources.

(6) (Optional) Download the new app from Facebook called Paper and see their version of recommending news stories based on the preferences of people who were your kindergarten classmates.

I know that I’ve already revealed what I think you’ll discover is best among this group for  delivering a consistent flow of the most relevant and personal content, in the most efficient way. I trust the network of smart news catchers I’ve put together manually more than those that aggregate their suggestions by algorithm.