media seo analytics | push2digital

It's a good question, "What is the best day to publish content?"

It depends on your content, target audience and approach ... basically your digital strategy [if you don't have one, check out this post on building a web measurement model].

WHAT ARE YOU LOOKING FOR?

Let's assume you're a media site that generates 20% to 30% of your traffic from search and another 10% to 20% from social. That's a pretty good chunk of your audience acquisition that depends on others (ie. Google, Facebook, Twitter etc.)

So what if you could obtain greater exposure by analyzing what days generate the most referrals? Good start huh, because if you average 50 FB referrals on Mon., 62 on Tue., 64 on Wed., 48 on Thu., 52 on Fri, 22 on Sat. and 18 on Sun. -- that tells you something right?

It does, but not entirely.

To get a clear picture, you have to factor in how many pieces of content you're pushing out on those days. If you're publishing 95 stories on weekdays and 32 stories on weekends, that's significant. Therefore you want to know the referrals-per-story.

WHERE’S THE OPPORTUNITY?

Dan Zarella published a study on the ideal time to submit blog posts that states the ideal Twitter retweet sweet spot is Friday @ 4p ET.  He also claims that Facebook sharing is highest @ 9a ET and spikes significantly on Saturday.

This confirms data I've seen that stories published on Saturday generate approximately 60% more Facebook and Google referrals per story than those published during the week. Sunday stories show @ 25% more Facebook and 40% more Google referrals per story. The problem is that these spikes are often masked by the total number of referrals which are typically lower on the weekends.

HOW TO MEASURE REFERRALS PER STORY?

Your results may vary, so you should review your own metrics and build this formula. The trick is to compile total number of stories published for the year and break them down by day. In Excel you can apply a formula =WEEKDAY(A1) [A1 is your first date] to convert that date to a simple day of the week. Then you can apply a filter by clicking the header of the Day of the Week column you just created, click Data Tab and Filter button. That will allow to group your yearly data by all the Mondays, Tuesdays, etc. If that sounds confusing, read this post on using Excel's WEEKDAY function.

Once you have the year's stories published and referrals broken down by day of the week, you can build your weekday referral rate. Repeat for each day, and repeat for each source (Google, Twitter, Facebook or any other key referral source.)

(Monday Facebook Referrals / Monday Stories Published = [Monday Facebook referrals per story])

OPPORTUNITY FOR ACTION

The takeaway here is not, "don't publish on weekdays", but that there is a greater opportunity to be shared and ranked on the weekends, Saturday in particular. And content published that is geared towards a Facebook morning audience or Google topics could do significantly better during this time frame. It’s not a simple task, but it’s not rocket science either and worth the time, especially if you can generate more audience with no real extra work – just a smarter choice of publish times and content topics.

Most media groups, by now, understand how important the use of keywords, title tags, bread crumbs, topic clusters are to exposing their content to the widest possible audience. 

But as with most good ideas, knowing what to do and executing it are two very different things.

That’s because identifying the proper keyword terms to target, selecting the proper category [which drive your bread crumbs], linking to content that’s directly related to your new story can be time-consuming and labor intensive.

Anyone who works in media can tell you – Content may be king, but speed to market is often the Judge.  That’s why when it comes to properly optimizing a story vs. getting it out – the keywords, tags and links can be left on the cutting room floor.

But there is help. New tools and APIs are emerging that leverage natural language processing that automates not just a keyword search, but a true understanding of what that content is about. TextWise is one such company offering APIs that provide automated content analysis that can return the story’s appropriate category, metadata, title tag, topic tags as well as match it to other relevant content.  Plus the API calls are free to a point, @ 20K per day, and can be purchased beyond that level.

If you’re not API-savvy, there’s a widget for Similarity Search that’s plug-and-play, as well as a WordPress plug-in.

With tools like these, content creators can start to move from the good ideas that live on the “if I have time” list, to a process that executes good ideas every time.

Read a great post this morning which I’ll reference in a moment that speaks to the reason data-rich companies are still not flourishing with this information.  It [data] is available in many tempting flavors – free, paid, borrowed, mobile, real-time, visualized, raw, aggregated, curated and so on.  But why then is not magically ringing the cash register?

How do I know if all that data is even making a difference? In other words, what are the metrics for my metrics?

“Huh?” you say.

To put it more clearly, how do I measure my analytics efforts themselves. What signs do I look for that my data-driven strategy is making an impact?

What does success look like?

Well, I’d say the golden Holy Grail conversion goal is … are you ready for it … here it comes … “action.”

Action -- could come in different shapes and forms and may not register on a monthly report but it’s prompted by insights, information from data analysis [notice I didn’t say data gathering]. And you must recognize it in all its forms so you can strive for it and then celebrate it when it occurs.

And it could look like any of these:

1.       You discover all your site pages are not tagged properly in comScore and correct it

2.       You discover a competitor is increasing market share in a new vertical, and greenlight a beta test in that same vertical

3.       You discover the bios page on your site generates 22% of your visits and expand, promote and elevate that section at the expense of under-performing content

4.       You discover more people are entering your site from your story level page than your home page and start A/B testing to reduce the bounce rate of your story level pages.

5.       You discover 20% of labor resources are spent on a site section that generates 10% of your visits but no revenue, no conversions, no repeat visits and simply kill it.

6.       You discover that your peak audience arrives between 10a-2p and shift the schedules of your web staff to produce more from 7a-10a.

7.       You discover that users to your home and garden section click on ads 3x more often than any other section of your site and notify sales.

8.       You discover referral visits from Google spend twice as much time on site as visitors from Drudge and Twitter and review/rewrite all the page titles on site to increase search referrals.

9.       You discover referrals from a related site convert at a higher rate than any other visit and set up a meeting to partner with that site.

10.   Or, you gather your execs, stakeholders, clients into a single room and ask, “What is the one most important action a visitor to our site can perform and how does it drive our business?” and you don’t leave the room until you agree on it. That’s your No.1 priority … and that’s where you measure intently … analyze relentlessly … and act boldly.

Now back to that post, Bryan Eisenberg’s “Data Rich, Optimization Poor” drives home the same thought – data, and even analysis without action – is lip service.

“There's no profit from having a web analytics report; you make money from making changes and experimenting based on the insights available from the data. In order to do web analytics correctly, it needs to generate a to-do list for you.” 

Amen, brother. Action is where it’s at.

Talk about actionable analytics, not only did SEOMoz make a bold move by displaying post-by-post analytics for the author, but to the general public. Their Open Analytics uses Google Analytics' API to pull it off.  In so doing, the SEOMoz team gives a glimpse of the increasing value of analytics that go beyond Excel charts and all the way to the end user. Nicely done.

Now that we have feasted on healthy portions of Osama Bin Laden news for more than a week. What did we learn about coverage of a worldwide event like that?  Two compelling columns point to a strategy and a trend of how our appetite for the various flavors of news can be measured.

First is Danny Sullivan’s insightful piece that touched on the “nuggeting of news” and how blogs and some mainstream media pursued the story in bite-size pieces and were rewarded by Google with more frequent and higher SERP positions. Is it an overt chase for pageviews? Absolutely. Is it a devious new blogger tactic? Hardly, it’s been a media mainstay since the telegraph.

“It was effectively doing what news organizations and wire services have long done, a “write though,” constant updates to a story. Chasing pageviews too? Maybe. But also part of what is native to some news organizations.”

– Danny Sullivan

The second piece, the Pew Research Center's analysis of Bin Laden coverage, was even more interesting and referred to a study that focused on which story angles garnered the most coverage and where those angles were more prevalent.  What was the No. 1 theme on Twitter, Facebook? Humor, followed closely by conspiracy theories and hoaxes.  

Credit: Etan J. Tal / Wikipedia