Interrupt your rhythm and spend a few days with me and 80 people in a hurry to make a difference. Over the years I've discovered that theseseminarswork.
You can details and a link to apply right here. It's March 6, 7 and 8 just outside of New York City.
Having people apply for a seminar is an interesting choice. It certainly takes a lot more time (for you and for us) and also makes it more difficult to promote. In this case, I think it's worth it. The people in the room with you are as important (sometimes more important) than the person on stage. The connections and support and inspiration you get from those around you have a significant impact on who you will become.
We're limiting applications to 200, on a first-come, first-served basis, and then alerting successful applicants after a day or two.
The goal is simple: to create a posture of forward motion, a platform you can use to elevate your work, your company and your team.
You can find the details (and some photos) on this page. It's not inexpensive, and it's not for everyone, but for those that can find the time and urgency to step up and come, I hope it will be a turning point for you.
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Optimistic time seems like a good idea. "We'll ship in January." "The conference will start at noon." "I'll be there in ten minutes."
The hope is that the expectation of completion will raise our expectations and increase the chances that something will actually happen.
In fact, though, there are huge costs to optimistic time. When you announce things based on optimism, the rest of the world you're engaging with builds plans around you and your announcement. And the cost of the person who doesn't have your software or is sitting around a meeting room for hours waiting is high indeed.
The alternative is honest time. Time without recourse or negotiation. The Metro North train leaves at 5:52. Not 5:55, no matter how much you want it to wait.
The software ships, the conference starts--at precisely when we say it will. So the world plans on it and depends on it and effectiveness grows.
It doesn't ship because it's ready. It ships because it's due.
(Amazingly, this rule makes things ready a lot more often).
It's a point of view and a contract with yourself. It ships when I said it would.
Yesterday, President Obama gave a State of the Union Address that contained a series of proposals for US Congress on raising taxes, free education, and carbon taxes.
Every Obama proposal is Dead-on-Arrival. Obama may as well fired a spaceship at the sun. The spaceship would melt long before it got there.
Draghi vs. Obama
On Thursday, in just a few hours, ECB president Mario Draghi gets his "moment in the sun". And like Obama who telegraphed his speech in advance, rumor has it ECB Eyes €50bn Monthly Bond Purchases.
Steen's rationale, fully explained in a subsequent post is that Lower Interest Rates May Reduce Consumption. That is a proposition that Michael Pettis at China Financial Markets and Lacy Hunt at Hoisington Management both agree with.
Lacy Hunt pinged me with this thought ...
"Academic research indicates that QE in the US contracted rather than expanded economic activity, just as it did in Japan. Thus, Steen could have made the even stronger case that since it didn't work in the US or Japan, it will not work in for the ECB."
I have no particular insights into what ECB president Mario Draghi will say tomorrow. Yet, I suspect he will attempt some surprise move. Surprise moves seem to be the central bank move of the day.
Regardless, whatever the ECB does, those in Germany will say he did too much. Keynesian and Monetarist clowns will howl he did too little, especially if the initial reaction is bad.
Central Bank Impotence
Here's the deal: Like president Obama, the ECB is impotent. Both bark at the moon. They only thing the ECB can do is make matters worse. Obama cannot do anything at all.
If the initial reaction from Draghi's announcement is good (something I highly doubt), it will die soon enough.
Canada's dollar sank the most in more than three years after the central bank unexpectedly cut interest rates, saying crude oil's collapse will slow inflation and weigh on the economy.
The currency reached the weakest level in almost six years after the Bank of Canada reduced economic forecasts and lowered the benchmark rate target to 0.75 percent, from 1 percent, where it's been since 2010. Government bonds climbed, pushing yields on two-, 10- and 30-year debt to record lows. Crude, Canada's biggest export, has tumbled more than 50 percent since June amid a global glut.
"They are taking pre-emptive steps," Thomas Costerg, an economist at Standard Chartered Bank, said in a phone interview from New York. "If oil prices remain under pressure, you could potentially see further cuts. This was not expected, and it's going to put pressure on the loonie."
Preemptive Steps
How much more preemption before the derivative bubble blows sky high? On that question we find out more tomorrow.
US Dollar vs. Canadian Dollar
click on chart for sharper image
Since mid-2011 the "loonie" has lost about 24% vs. the US dollar. However, the dollar is a lot weaker than its Canadian counterpart compared to late 2001.
Canadian Yield Curve Inverts
30-year: 2.044% (Today's Low 1.998%)
10-Year: 1.426% (Today's Low 1.366%)
05-Year: 0.791% (Down 19 basis points, an 18% decline)
03-Year: 0.590% (Down 27 basis points, a 31% decline)
02-Year: 0.560% (Down 29 basis points, a 34% decline)
01-Year: 0.580% (Down 34 basis points, a 37% decline)
01-Month: 0.640% (Down 22 basis points, a 26% decline)
Blue Ribbon Announcement
Canada wins the blue ribbon for the first G-7 yield curve inversion since central bankers started unleashing competitive "preemptive" rate cuts.
Yield on the Canadian 1-year note, 2year-note, and 3-year note are all inverted (lower than yield on the 1-month note).
In addition, yield on on the 1-year note is inverted with the 2- and 3-year notes.
I smell a Canadian recession (and more surprise actions). A bust of the Canadian real estate bubble, one of the biggest in the world, is also on the way.
Mike "Mish" Shedlock http://globaleconomicanalysis.blogspot.com
Why pay an expensive bulldozer driver for foundation work when a drone from the sky paired with an unmanned bulldozer on the ground can compute 3-D plans and do the job better and faster?
Construction workers move over. You are next to be unneeded, unwanted, and unloved.
Construction-equipment maker Komatsu Ltd. has plans to solve a potential shortage of construction workers in Japan: Let drones and driverless bulldozers do part of the work.
Tokyo-based Komatsu said Tuesday it plans to use unmanned aircraft, bulldozers and excavators to automate much of the early foundation work on construction sites.
Under Komatsu's plans, U.S.-made drones would scan job sites from the air and send images to computers to build three-dimensional models of the terrain. Komatsu's unmanned bulldozers and excavators would then use those models to carry out design plans, digging holes and moving earth.
The drones, made by San Francisco startup Skycatch Inc., and construction equipment would move along largely preprogrammed routes. The goal is to automate the construction site, leaving humans to program the machines and then push a button to send them to work. Human operators would also monitor progress and can jump in to take control of a machine if necessary.
Companies have started employing automated trucks and other equipment at mines in recent years, but Komatsu's program appears to be one of the most ambitious plans to automate work in a setting as dynamic as a construction site.
The Skycatch drones are programmed to automatically fly over a set area and use sensors to collect data on the terrain below. The drones even return to ground stations and swap in new batteries when power is running low.
Job Site of the Future
"We think this is the future job site," said Akinori Onodera, president of the Komatsu.
The future comes fast these days. Most likely, this will be routine in a few years or so.
Meanwhile, the Fed (central banks in general), and governments are hell-bent on policies that are guaranteed to make matters worse.
Low interest rates to finance such operations, coupled with rising minimum wage demands provides maximum leverage for drones, unmanned vehicles, hardware robots, and software robots to replace humans far quicker than otherwise would happen.
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This post was originally in YouMoz, and was promoted to the main blog because it provides great value and interest to our community. The author's views are entirely his or her own and may not reflect the views of Moz, Inc.
Many of the traditional channels for online content discovery are thoroughly understood and their adoption rates are high.
The readily accepted channels—from SEO and PPC, to email and social media broadcasting—can deliver the best content to the right people at the right time.
Today, however, the Internet is experiencing a deluge of content, and many channels for content discovery are bloated. Estimates say that more than 2.73 million blog posts are written and published daily. Many industries are experiencing a content surplus, making it even more challenging for marketers to get their content seen.
Social media networks like Facebook and Twitter are adjusting their algorithms to ensure the least amount of organic visibility for brands, too. Traditional paid media, such as banner advertising, is becoming less effective year-over-year because banner blindness runs rampant. According to Solve Media, you're more likely to survive a plane crash than click on a banner ad.
That sounds farfetched until you look at the results from the Nielsen Norman Groups 2007 eyetracking study (shown below).
Red areas indicate where users looked the most; yellow areas indicate fewer views; areas colored blue depict the least-viewed portions of the page; gray areas didn't attract any views/actions; and the green boxes are used to highlight advertisements.
As a result, new techniques, tactics and tools are cropping up and being used by marketers of all stripes to maximize the visibility of their content. There's now an entire content promotion ecosystem. From influencer marketing to native advertising, brands are experimenting in new ways.
Many brands are sponsoring articles on blogs or other online publications with large preexisting audiences. An interesting stat we just included in our own " Content Promotion Manifesto" is that brands spent, on average, 6.7 percent of their content marketing budgets on sponsored content in 2013. It's trending upwards, too. From the The New York Times to Forbes' Brand Voice, there's no shortage of famous examples.
While advertorials have been around for decades, this top-of-the-funnel sponsored article channel is relatively new for many content marketers. Over the last year, we have received many questions from clients about sponsored content—questions about pricing, scale, value and strategy. We struggled to answer most of them; there wasn't anywhere to get answers.
Because of this, we decided to reach out to 550 online publications to gather as much information about their sponsored content programs as possible. We wanted to find out the following:
An agreed upon definition for sponsored articles
The current state of sponsored articles as a channel
Examples of sponsored articles
Sponsored article pricing and value
A media buying strategy for sponsored articles
Tools and platforms for sponsored articles
We quickly learned that sponsored content on blogs and other online publications, when viewed as a marketing channel, is very immature. Pricing doesn't have much rhyme or reason, either. However, after collecting and interpreting data on 550 online properties, and dissecting countless native advertising studies, we hope to shine a light on a little known content marketing channel.
The results of the study are outlined below.
Note: The complete Media Buyers Guide to Sponsored Content study is available for download here.
Defining Sponsored Articles
With content marketing adoption rates so high, many brands are looking to native advertising to promote their content. The Interactive Advertising Bureau (IAB) defines native advertising as "paid ads that are so cohesive with the page content, assimilated into the design, and consistent with the platform behavior that the viewer simply feels that they belong." According to the IAB, native advertising contains six different types of ad units: in-feed, promoted listings, in-ad with native element, paid search, recommendation widgets, and custom.
Sponsored articles fall into the in-feed subgroup. However, so does promoted content on Facebook, LinkedIn and Twitter. Bcause they appear within the normal content feed of the publisher, it doesn't matter if the publisher is Facebook or BuzzFeed.
In other words, sponsored articles amount to advertising on a media outlet in the form of editorial content that looks like it's supposed to be there. Brands value this because association with a publication and exposure to its audience can drive awareness, traffic, conversions, and leads.
The Current State of Sponsored Articles
We uncovered lots of fascinating information about sponsored articles while conducting our research. They are actually an evolved version of what many marketers call advertorials, which have been around for decades. The biggest difference between the two is where the content resides in the customer buying journey. Advertorials are middle to bottom-of-the-funnel content.
An example of a magazine advertorial
On the other hand, sponsored articles strictly reside at the top of the funnel. Their purpose is to be helpful, entertaining, or both. Top-of-the-funnel content doesn't appear to be salesy and brand-centric to the reader. It's the rise of content marketing that helped move advertorials up the funnel. This helps brands become not just purveyors of goods and services, but a producer of ideas and a distributor of knowledge.
Controversy
Sponsored articles have received pushback from some publishers, brands, and consumers—and even government regulators who are concerned because the articles resemble editorial content. This can damage the editorial integrity of a publication, as well as a brand's image.
Both publishers and marketers have a vested interest in not appearing to mislead consumers. Native advertising in general is misunderstood by many consumers and marketers. (That's partly why we conducted this study.)
In the video below, John Oliver does a good job of articulating many consumers' concerns regarding sponsored articles.
Copyblogger's 2014 State of Native Advertising Report surveyed over 2,000 marketers and discovered that 73 percent were either completely unfamiliar with or hardly familiar with native advertising.
Thirty-eight percent of the marketers could identify forms of native advertising from a checklist, and only three percent claimed to be very knowledgeable.
Earlier this year, Contently surveyed 542 U.S. Internet users to determine what they thought about sponsored articles. Only 48 percent of the respondents believed sponsored content that was labeled as such was paid for by an advertiser that had influenced the content produced. The rest thought the label meant something else.
Just over 66 percent of the respondents reported they are not likely to click on an article sponsored by a brand and 33 percent said they're just as likely to click on a sponsored article as they are to click on (unsponsored) editorial content.
There is also contradictory evidence surrounding the overall effectiveness of sponsored articles. Research from Chartbeat shows that only 24 percent of visitors scroll past the fold when visiting a sponsored article—compared with 71 percent for editorial content.
However, The New York Times claims readers spend the same amount of time on sponsored articles as traditional news stories. This is backed up by a study from Sharethrough and IPG Media Labs. They found that consumers actually look at sponsored articles more than typical editorial articles (26 percent vs. 24 percent) and spend a similar amount of time on each (1 minute vs. 1.2 minutes).
Not all publishers offer sponsored article opportunities to marketers. During our research, some respondents told us that protecting editorial integrity and preserving audience trust were a higher priorities. On the other hand, many big name publishers like Forbes, The New York Times, Business Insider, The Atlantic, Washington Post and The Wall Street Journal have all embraced sponsored articles as a revenue source.
BuzzFeed's entire business model is built around what it calls sponsored "listicles," a.k.a. sponsored articles. While some publishers are averse to adopting this native form of advertising, it doesn't seem to be causing any damage to the publishers who are using native ads.
The U.S. Federal Trade Commission (FTC) hasn't quite figured out how to regulate native advertising. The FTC has delayed handing down regulations around disclosure requirements, language and graphic separation. Until that happens, the display of native advertising will remain at the discretion of publishers.
With that said, the IAB has set native advertising guidelines for its members. The IAB reports that clarity and prominence of paid native ad unit disclosure are vital, regardless of native advertising type.
Their two criteria are straightforward:
Use language that conveys the advertising has been paid for, thus making it an advertising unit, even if that unit does not contain traditional promotional advertising messages.
Be large and visible enough for a consumer to notice it in the context of a given page and/or relative to the device the ad is being viewed on.
In the case of sponsored articles, a reasonable consumer should be able to distinguish between editorial content from the publisher and paid advertising.
Growth
A 2013 survey conducted by Hexagram and Spada revealed that 62 percent of publishers had embraced sponsored articles, with another 16 percent planning to go this route by the end of 2014. Comparable research from eMarketer showed that only 10 percent of digital publishers didn't have and weren't considering native advertising on their sites.
The 2014 Native Advertising Roundup revealed that 73 percent of media buyers use native advertising, and 93 percent expect to spend the same or more in the future. Native advertising spending in the U.S. is expected to increase from $1.3 billion in 2013 to $9.4 billion in 2018. A full 40 percent of publishers expect native advertising to drive a quarter or more of their digital revenue this year.
Native advertising, when compared to traditional display ads, have been found to be more effective. 25 percent more consumers looked at sponsored articles than display ad units. Native ads produced an 18 percent lift in purchase intent and a nine percent lift for brand affinity responses. BIA/Kelsey released a study which shows brands are planning on spending more on native advertising, and publishers stand to benefit as long as they can preserve the trust and interest of their audience.
Examples of Sponsored Articles
Since look, feel, design, language and requirements of sponsored content are left up to the discretion of publishers, the presentation of sponsored content on different sites varies widely. Some publications provide brands with what can be described as a virtual microsite within the site itself. Others are more streamlined, using an article that appears as a piece of featured content but is labeled as sponsored.
There are no real standards for pricing in the digital world with regard to sponsored content. This makes budgeting for the channel very tough to do. It also makes long-term strategic execution at scale and across multiple publications a near impossibility.
While the value of sponsoring content is clearly understood by many brands, how to execute it and who to talk to in order to get it done is generally unclear. The study set out to add rhyme and reason to this burgeoning channel by exploring costs and comparing them across a broad spectrum of online publications and blogs.
This is valuable information for marketers and media buyers wishing to negotiate with online publications. It can even be used by publications that have not yet offered sponsored content opportunities to establish fair pricing.
Since publishers completely control their own pricing and standards, they maintain their own criteria for validating costs associated with sponsored articles. In today's analytics-driven marketing culture, where channels are often compared and returns are measured, sponsoring content across several different publications can't be so easily consolidated into a single "sponsored content" channel since each one has a unique value proposition.
This study is the industry's first attempt to scientifically justify, quantify, and predict current going-rate prices of sponsored articles using explicit data points that can be measured for each online publication. Our goal was to create the first-ever quantitatively supported pricing standard for sponsored articles.
We hope our research puts an end to these challenges and empowers marketers with the ability to budget, negotiate, and ultimately scale the deployment of sponsored articles within their channel mix.
Research
In total, the research for this study was conducted over a five-month period of time earlier this year. It included manual outreach via email and phone to over 1,000 media outlets and blogs. The outreach resulted in responses from 550 publishers that sold sponsored article units.
The study took an unbiased approach to data inclusion and included a representative sample set. It collected data on globally-recognized publications, one-person blogs, and everything in between.
Publications were classified using the following criteria:
Content is created by more than five writers/contributors/columnists, and:
The website already utilizes traditional display advertising (e.g., banner ads)
Everything that didn't meet the above criteria was classified as a blog.
Each price collected in the study was the minimum charge for getting a sponsored article published, regardless of other pricing factors. A total of 17 factors were cited as justification for pricing schemes from the 550 publishers.
Word count: The number of words in a sponsored article
User time on page: The amount of time a typical reader spends on a web page
Links: Specifications regarding whether or not links would be provided, and if so, how many, where and whether or not they would be "nofollow" links
Lead capture: For publishers that provide links to gated assets, many charge on a per-lead basis
Impressions (CPM): Cost per thousand impressions based on historic data
Time and effort required from publication's editorial staff
Monthly website traffic
PageRank: Often used by publishers to justify relative pricing when they run more than one media outlet
Domain Authority: Often used for publishers to justify relative pricing when they own more than one publication
Page-level engagement: A metric that is measured by how far readers scroll down the page and the amount of time spent on a given article
Social media promotion: Often an optional add-on that would increase price (may come as part of a package deal)
Email promotion: Often an optional add-on that would increase price (may come as part of a package deal)
Display advertising: Often an optional add-on that would increase price (may come as part of a package deal)
Number of articles: How many sponsored articles you are buying at a time
Visibility time: The amount of time an article stays live on the site
Verticals: For large publications that cover many verticals or subject areas, some verticals are more expensive than others
Pay-per-click: Another engagement-level metric that is measured by the number of click-throughs to an intended landing page
In order to do a quantitative analysis, explicit data was collected from all of the publications to calculate predictor variables. Those variables included:
Domain Authority: A ranking score from Moz, on a 100-point scale, that uses more than 40 signals to calculate how well a website will perform in the search engine results pages (SERPs). The higher the score, the more authoritative the website is viewed as being.
Page Authority: Another ranking score from Moz, on a 100-point scale, that calculates how well a given webpage is likely to rank in the SERPs. In the case of this study, the publication's home pages were used.
PageRank: A ranking metric from Google that calculates the relevance of a webpage. This score analyzes the number of incoming links and the quality of the referring webpages to generate a measurement between 0 (low relevance) and 10 (high relevance).
AlexaRank: A ranking score from Alexa.com that is based on traffic data from users over a rolling three-month period. A site's ranking is based on a combined measure of unique visitors and page views. The site with the greatest combination of these is ranked No. 1, and higher number rankings correlate with lower traffic data.
Facebook Following: The number of fans (or "likes") a publication's Facebook page has.
Twitter Following: The number of followers a publication's or a blogger's Twitter account has. For publications with multiple accounts and/or contributing authors, only the account with the largest following was used.
Pinterest Following: The number of followers a publication's or a blogger's Pinterest account has.
Assumptions
It is assumed that the data set in this study is a representative sample of the entire ecosystem of blogs and other online publications because the results closely mirror Moz's distribution of Page Authority that analyzed more than 10,000 SERPs and 200,000 unique pages. This regression model had a mean (average) Page Authority of 40.8 and standard deviation of 15.1. The distribution can be seen below.
The regression model in this study had a mean of 47.1 and a standard deviation of 15.5. The sample set of blogs and publications had a slightly higher Page Authority than the Moz study. This was expected because the study only measured root domains and not long-tail pages within those domains.
Aside from that slight disparity, the distribution curves are nearly identical. For those readers who are number junkies, the descriptive statistics of the Page Authority data in the study are below.
Limitations
Variations in sponsored content offerings – The study established the pricing baseline based on the cost of one sponsored article. Since some publications only offered long-term commitments to marketers that could include other benefits (banners, email, social promotion, etc.), some publications' unit pricing could be inflated. As a result, the regression model may not be an accurate price predictor in all scenarios.
Social account data – Not all online publications have accounts on Facebook, Twitter and Pinterest. In these cases, the number zero was used to quantify followers. Also, for publications with multiple accounts on the same network, the study measured the account with the most followers.
Alexa Rank Inaccuracies – Alexa admits publicly that there are limits to making judgments from its data. Sites with relatively low traffic may not be accurately measured by Alexa.
Analysis
The graph below seeks to show the exact methodology we used to conduct the sponsored content pricing study. It's purpose is to give readers confidence in our pricing models so they feel comfortable in adapting the formulas.
When all prices are graphed, bloat appears on each end of the pricing spectrum. In order to reconcile the dense areas, the study broke down the pricing data and regression models for blogs and publications separately.
Blog Pricing Analysis
The graph below represents the distribution of prices for all 474 blogs in the study.
Because of the wide range and low frequency of prices recorded in the "more" area, we decided to label these data points as outliers. By removing the outliers (approximately 3.8 percent of the sample) from the analysis, the variance decreased by 87 percent, making for a more accurate predictive model. All descriptive statistics for the blog data sample before and after removing the outliers were laid out in the study.
With the remaining 456 cases, a multi-variable regression test for price against all of the predictor variables was run, after which the insignificant variables were removed to formulate the pricing regression model for blogs, as shown below.
The end result confidently determined the fair market price formula for a sponsored article on a blog:
Publication Pricing Analysis
The graph below represents the distribution of pricing for all 76 publications recorded in the study.
The outliers were kept in this regression model because of the range in quality and size of online publications is large. The descriptive statistics are available in the actual study.
Following the same methods as the blog analysis, the study ran a multi-variable regression test to construct a predictive model for publication pricing. After removing the insignificant variables the output looks like this:
The end result confidently determines the fair market price formula for a sponsored article on a publication:
What All This Math Really Boils Down To
With the formulas below, marketers now have a way to assign value when purchasing or negotiating for sponsored articles on blogs or publications.
Prior to this study marketers had no way of knowing if they were getting a fair deal or not using this emerging channel.
Blog Price Formula = -60.5 + 5.97(DA) + 0.978(thousand Fb fans) + 15.1(PR) – 0.000007(AR)
That said, media buyers should also note that many top-tier publications package their sponsored content offering in different ways. Keep this in mind when using the formulas above. Below are examples of some variation in sponsored article packages.
Networks and Tools for Sponsored Articles
While conducting research, several tools and networks kept coming up. Some networks set up for the sole purpose of connecting marketers with publishers for sponsored content. Even HubSpot has built an informal ad hoc network for its partner agencies to connect with its publishing customers. Content measurement tools, including Nudge, which was built to measure sponsored content, are starting to crop up, too.
A few other networks and tools worth noting:
Adproval: A media outlet marketplace for connecting publishers and advertisers
BlogHer: A blog and social media influencer community focused on social media coverage of women
Blogsvertise: A blog marketplace for connecting publishers and advertisers
Buysellads: A media outlet marketplace for connecting publishers and advertisers
Cision: The brand's Content Marketing Database includes a searchable database of over 2,000 sponsored opportunities with thousands of U.S. publications
GroupHigh: Blogger outreach marketing software that helps companies find bloggers, in addition to managing and tracking relationships, and measuring results
Izea: A sponsorship marketplace that connects social media influencers with brands
Markerly: A brand amplification platform that connects brands with bloggers
Sway Group: Connects brands and agencies with the largest network of female bloggers on the Web
The Syndicate: A brand storytelling partner and blog sponsorship network.
With the growth of online content showing no signs of slowing, the use of sponsored content as a marketing channel will undoubtedly continue to grow as well. Besides, it's a proven revenue stream for publishers who have often struggled to make money on the Internet.
However, as the popularity of sponsored content grows, so does the likelihood of it being regulated by governments. Until then, consider this post your definitive guide to sponsored content. The study can be downloaded here.
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