Driving Vertical Content Recommendations

One of the recurring patterns I’ve run into with web content, illustrated here with the upside down triangle, is the inverse relationship between traffic and value.   The areas of a site where traffic is high, value tends to be low and vice versa.  The pattern reflects a basic dynamic: high traffic generally indicates breadth of content appeal while high value generally indicates specificity of audience that advertisers are willing to pay a premium for.  A more specific audience….tends to generate lower traffic.

The inverted relationship is not invariably true; there is high traffic, high value content (and unfortunately low traffic, low value).   But it is a recurring tendency.   And the more that content narrows within a site, from a broad overall positioning to specific topic verticals, the more the triangle visual will apply.

This concept relates to another, the importance of maximizing monetization within each site visit.  In a previous post, Is Increasing Visit Frequency a Realistic Goal? I’ve laid out some public domain Quantcast data to show that the visits per visitor dimension of loyalty has less variability across sites than the pages per visit dimension.    Visits per visitor tend to fall into a more narrow range most likely because of the mind-bogglingly enormous set of possible destinations on the web.    It’s just hard to squeeze another visit per month from a site visitor; getting another page or two per visit is a lower hurdle.   To monetize most effectively you’ve got to monetize them when you’ve got them.

The logic and mathematics of recommendation algorithms are beyond me.  But based on the theories above I believe they can be key to driving increased loyalty along the path of least resistance, getting another page or two from the visitor on the occasions when he/she happens to visit.

Furthermore, recommendations that drive the visitor deeper into the triangle, into content verticals that appeal specifically to a visitor’s profile and command higher value, are worth more than recommendations that drive visitors across the top, to other broadly appealing but lower value content.   The more recommendation algorithms can achieve this goal the more effectively they can monetize for the publisher.

Along these lines, here is a link to a cool visualization from the site Online Behavior that shows how a page can be personalized for a specific visitor:

“A visitor arrives to a website from a search engine using search keywords including “health”.  Why not display a personalized version of the page based on the visitor’s interest?”

Not a recommendation algorithm per se but an example of how a specific visitor could be driven to higher value content that specifically appeals to his/her profile.


Is Social Media Driven Traffic Less Engaged?

Outbrain released a study in April on the referral sources driving traffic to content pages, in terms of percent of referrals and the quality of the referred traffic.   They describe the dataset as 100 million sessions from over 100 premium publishers using their services.

When traffic quality is assessed by page views per session, search is the strongest traffic source followed closely by content sites with portals and social networks trailing.   Looking at an inverse measure, bounce rate, social networks and portals show the most one-page-and-out behavior, followed by content sites and then search…the least bouncy.    Looking at hyper-engaged sessions, defined as 5 pages or more, content sites lead, followed by search with portals and social networks trailing.

So…it would seem that social-media driven traffic is less engaged than traffic from other sources.   But I think there’s more going on here than meets the eye, as I’ll note on the other side of these charts from the Outbrain report.

I don’t think this finding is really about loyalty.   It’s about how specifically each of these traffic sources drives users to the exact content within the site that’s of interest to them.

When people enter content pages through search they may be searching for the site per se, using search as a proxy for typing in the URL.   They’re likely to come through the front door of the site,  the home page.   Multiple pages per session through search may not indicate loyalty but rather a fumbling about trying to find the specific content on the site that’s of interest.   In contrast, when they come through social networks they are being directed to a very specific piece of content referred by a friend…they go directly there, read it and bounce away.

The site experience may, in fact, be superior for social networks even though the loyalty metric looks weak.   And it may be a desired outcome for the publisher if that one page is deeper in the site and commands higher premiums than more generic content near the front.    Not all page views are created equal.    The value of social networks may not be sheer tonnage of page views generated but rather more targeted page views…driving visitors more directly to the pages that the publisher most wants visitors to consume.

Though loyalty (or lack thereof) looks the same for social networks and for portals, I would bet there’s a critical difference.   When visitors go one-page-and-out after being referred by a portal they are likely bouncing off the home page.    When they go one-page-and-out after being referred by a social network they’re likely bouncing off a specific post or article, some of the site’s more premium content.

We’d have to dig deeper into the data to prove my case….

But that, I think, is the story behind the story of these charts.

Is Increasing Visit Frequency A Realistic Goal?

For the content sites I’ve worked on there’s often been the following mantra on the business and editorial teams:

We want to our site to be part of our users’ lives.   We may be a quick, entertaining mid-day mental snack, but one our users can’t live without.   We want them to come back (practically) every day.

But there have been a number of times that I’ve run into the following pattern…a pattern that makes me wonder about the soundness of this goal.   I’ve reproduced it here using Quantcast data that’s in the public domain, starting with site ranked number 22 (Huffington Post) so as to exclude the very top-ranked utilities and running down to number 89, excluding sites that are not quantified or block access to their frequency data.   There are 32 sites on the chart – the point is that I wasn’t cherrypicking.

Quantcast Loyalty Data For 32 Highly-Ranked Sites - 6/28/2011

The chart breaks the number of pages per monthly visitor into two components, page views per visit across the x axis and visits per visitor across the y.   These are the two components of loyalty, how deep do people go into the site when they visit and how often they come to the site.

The striking thing is that all the sites fall into a narrow range on the visits/visitor axis.   Almost all fall between an average of 1 and 4 visits per month.   Of the 32 sites there are a couple of outliers..to all of about 4.5 and 5.5 visits per visitor per month (those would be Tumblr and Drudge Report).   The pages per visit axis has the wider range, with the majority of sites in the 1-10 range and outliers into the low teens, one into the 20’s (Tumblr, 4share and Drudge Report).

The admitted flaw here is that I’m working with averages.   If you break down the average of 1-4 visits a month and look at the distribution of visits across visitors there are sure to be segments that visit the site every day, several times a day.

But my bet, looking at the averages, is that those highly loyal groups, in terms of visit frequency, will tend to be small, perhaps infinitesmal.  For the most part the online world is so noisy, there are so many options at people’s disposal, that it is difficult to generate visit frequencies to content sites of more than once a week or so.   The bigger driver of loyalty, the measure that creates more of a difference between the more sticky and more bouncy content sites, is how deep visitors go on each visit.   I believe the pattern implies…at least for content sites…that it is the pages/visit aspect of loyalty, the within session aspect, that deserves relatively more analytical and editorial focus.