Entries tagged with “page views” from Tools of Change for Publishing

The Realities of Big Web Traffic and Advertising

Mac Slocum
December 18, 2008 | Permalink | Comments (0) | Listen

Major news sites that rely on advertising as their primary revenue stream need to log hundreds of millions of page views per month to attract significant attention from advertisers, according to a new report from Lauren Rich Fine, research director of ContentNext.

From Advertising Age:

"Based on our research, the conversation [with advertisers] gets interesting at 200 million page views plus a month, but much more so around 800 million," Ms. Fine writes ...

... The report also looks at whether the [New York] Times could ever succeed as a web-only product, and concludes that it could -- once NYT.com starts generating 1.3 billion page views a month.

(Note: Advertising Age cites ComScore Media Metrix figures that put the Times' traffic at 173 million page views in October, but the Times communications department says this figure is very low).

Traffic estimates in the hundreds of millions and billions are a shock to the system, but they're nothing new. Jeremy Liew analyzed the online media industry in early 2007 (a time when Web advertising was still enjoying double-digit growth) and concluded:

At large scale, without a great deal of targeting possible, a startup's "run of site" or "run of network" advertising might be able to get to the $1 RPM range (Revenue per thousand impressions, including CPM, CPC, and CPA models). To get to $50m in revenue you would need 50 billion pageviews in a year, or just over 4 billion per month.

This type of analysis -- which is certainly on target -- is why it's important for publishers to acknowledge the reality of Web advertising by addressing two deeper questions:

1. Can I reach sustainability faster by aggregating advertising across sites or building a smaller organization? -- Limited choice shoehorns audiences into large groups, but the Web disrupts channel lock-in by allowing individual consumers to find material on their own terms. Big organizations are in trouble because the transition from limited channels to distributed channels means audiences are smaller (ie: 1 million vs. 10 million, 100,000 vs. 1 million, etc). There's still significant value in reaching 1 million people, or even 100,000 people, but smaller audiences attract less advertising revenue. So the challenge is to either scale businesses down so audience size, advertising dollars and sustainability even out, or, aggregate advertising revenue from a large number of targeted sites. Both options are arduous, but both are also realistic. Finding and maintaining billions of page views per month is not (the New York Times being the exception here).

2. Can I diversify beyond advertising? -- Ad-only Web models are inherently flimsy because the thing advertisers want is the thing most Web sites can't attract: huge crowds. A lot of lip service has been paid to the Web's targeting argument -- and in Google's case, that's proven effective and lucrative -- but the analysis from Fine and Liew shows that advertisers still can't shake that "big crowd" mentality. So if that's the reality, advertising needs to become one revenue stream among others.

Folks like Mike Masnick, Clay Shirky, Kevin Kelly and Chris Anderson have addressed these "other" revenue steams at length (all are recommended reading), but the abridged analysis of their work generally comes down to one word: scarcity. Digital content is not scarce. It's easy to find, distribute and copy (even if publishers lock it down). Because of this, audiences don't often equate "digital content" with "pay." Publishers can fight consumer expectation by creating artificial scarcity (DRM, pay walls for general content), but that same energy is better directed toward products that are naturally scarce: things that solve a problem (recommendations, education), offer an experience (readings, concerts, trips, conferences), grant access (consulting, POD for out of print titles), save time (curated information), and offer value on an individual basis (customization). All of these are outside publishers' comfort zones and none are guaranteed to catch on, but models that work in conjunction with the digital world offer a better shot at sustainability than those built on artificial limits and unrealistic audience sizes.

Related Stories:

• Clay Shirky: "The Newspaper Industry and the Arrival of the Glaciers"
• Kevin Kelly: "Better Than Free"
• The 26th Story: "Tribes author Seth Godin discusses free content and the publishing industry"
• Redefining Professional Content and Accepting Digital's Limitations
• Finding Balance Between User Experience and Web Ads
• Levels of Quality and Revenue Streams
• Web Analytics Primer for Publishers

Web Analytics Primer for Publishers

Mac Slocum
September 2, 2008 | Permalink | Comments (3) | Listen

Web content allows for a level of tracking and analysis unseen in other forms of media, but I get the sense some publishers are a little hazy when it comes to the established analytic measurements. This primer touches on the main measures I've used in my own efforts, but it is not exhaustive. I encourage other analytics folks to chime in with their thoughts and techniques in the comments area.

A few notes before we get into it:

• Note #1: If you check stats religiously and you're a whiz with your analytics tools, this post will be elementary and quite dull. You're better off perusing the excellent conversations at Webmaster World.
• Note #2: The term "hits" was outdated in 1999. I won't be using it here and I implore you to avoid this word -- and anyone using it within a Web traffic context -- at all costs.

With that out of the way, let's dive in ...

Visits -- When you access a specific Web site, that counts as one visit. If you leave and return, that usually counts as a second visit. I say "usually" because most analytics tools use a timer. For example: If you leave and return to a site running Google Analytics within 30 minutes, one visit is logged. But if you return after 30 minutes, a second visit is added to the tally.

• Caveat -- "Visits" should not be equated with "people." Even with a timer in place, it's possible for a single person to rack up multiple visits to your site.
• Recommendation -- Track visits over a period of months, not weeks. Long stretches will reveal the overall growth of your site and your audience.

Unique Visitors -- Unique visitors represent individual visitors to your site (in theory). This is an important metric because it gives you a sense of your audience size.

• Caveat -- Analytics tools rely on cookies to track unique visits, but cookies can be deleted or rejected by the user. There's also no way to differentiate between people using the same Web browser. Public terminals, lab computers and family PCs will all register as single users.
• Recommendation -- Limits on privacy (a good thing) and technology (not so good) prevent analytics tools from achieving the 1:1 visitor tracking utopia. For the foreseeable future, the unique visitors metric offers the best approximation of audience size. Just make sure bosses and advertisers understand the limits.

Page Views -- A page view represents a single view of a single page under a certain Web domain. If you click to another site and then click back to the original site, you'll log another page view. If you refresh the page you're viewing, another page view will be counted.

• Caveat -- A single visitor can log dozens of page views, especially if they've got an itchy refresh finger.
• Recommendation -- Page view figures should be used for general analysis. Their real value comes from the manual parsing of page view data. Close examination will reveal popular pages and topics, which can help guide future editorial efforts.

Pages Per Visit -- The Web's built-in context makes it possible to attract visitors with one piece of content, then present them with additional material on the same site through related links, embedded links, recommendations, etc. A high pages per visit average (3+ pages is quite good) means visitors are interacting with your content. A low average means visitors are viewing one page and quickly moving on to other sites.

• Caveat -- Want to see how the pages per visit average can be manipulated? Visit any major media site and look for the photo galleries. Placing a single photo on a single page and then encouraging users to click the "Next" button is an easy way to boost the pages per visit number. Pages per visit is also influenced by traffic spikes. If you receive an inbound link from a popular recommendation site (Slashdot, Digg), you'll likely see a huge increase in page views but a dramatic drop in pages per visit. Most visitors from these sites look at one piece of content and then move on to the next popular destination.
• Recommendation -- Like most analytics measurements, the pages per visit average should be examined over multi-month stretches. Traffic spikes should be disregarded -- not ignored outright, just disregarded in this case. If you see the average go up by a full page over the course of 3-6 months, you're doing something right.

Average Time on Site -- The more time users spend on your site, the more you can assume they're engaged with your content and your brand ... and your sponsors' brands. Given the hyperactive nature of Web browsing, holding visitor attention for a full minute or more is considered a success.

• Caveat -- As the Google Analytics FAQ notes, some visitors leave unattended browser windows open. Analytics tools make no distinction between an engaged viewer and a distracted viewer with messy browsing habits.
• Recommendation -- Analysis over a multi-month period is the best use for this measurement (sound familiar?). Consistent growth = good. Consistent decrease = bad.

Again, this primer is the tip of the analytics iceberg. There are many related topics worth further discussion and inquiry, including search engine optimization and Web advertising models.

There's an interesting shift that's also worth monitoring. Some publishers are looking beyond site-based statistics to gauge their overall reach across social networks, recommendation engines, RSS, mobile applications and other distributed platforms. Douglas McLennan, the founder and editor of ArtsJournal, touched on this topic in a recent interview:

I've come to the realization that ArtsJournal is not just a Web site anymore. Only 25 percent of our users ever come to the Web site, the rest get it through newsletters. We have 35,000 newsletter subscribers. Others get ArtsJournal through "newsbeats" that we provide on other Web sites. Some people get ArtsJournal through RSS feeds. In the course of an average day, there are 45,000 to 50,000 visitors -- people who use Artsjournal every day. The unique visitors per month is probably 250,000. We probably get 500,000 to 600,000 visits a month and a few million page views. So ArtsJournal is not huge by the scale of large Web sites, but it's substantial.

We may eventually see Q scores -- or a variation on that concept -- integrated into future analytics toolsets.

Related Stories:

• Google Analytics FAQ
• About.com: "Web Analytics Basics: Learn to Measure Your Web Site"
• Avinash Kaushik: "Data Quality Sucks, Let's Just Get Over It"
• Matt Belkin: "Unique Visitors or Visits - which metric should you use?"
• Joe Wikert: "The Booksquare on ePublishing"
• TOC DVD: "Search Engine Optimization for Book Publishers"
• Digital Experiments and Useful Analytics Must Go Hand-in-Hand