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comScore's Got It Wrong ... Fix It!

Apple-watermelon-nerds

Apples and watermelons may be a good combination for Nerds, but terrible for analytics.

If you're in digital media measurement, you've probably heard this from your boss, "ComScore's got it wrong, our site has twice as many uniques. Have them fix it!"

Well, he/she is right; you probably do have twice as many. But guess what … in the end, it doesn't really matter [I'll explain why later], but first let's explain why they're different.

My favorite analytics guru Avinash Kaushik recently listed 7 common analytics mistakes and first on the list was ... "Never Compare Apples to Watermelons."

And one of the most common "Apples to Watermelons" examples I can think of happens in media measurement -- comparing internal metrics (Omniture, Web Trends, Google Analytics) to external metrics (comScore, NielsenNet, Compete).

There are 2 main reasons why this is a fruitless task ... let me count them.

1. Differences in the data source -- Most metric measurements are based off a specific data set. Typically it's the data the vendor or company has access to, has purchased or has built. Different sources will generate different results. Internal metrics generally rely on a javascript beacon that passes information. External sources don't have permission to drop a beacon on your pages, so they often use panel-based methods (large panels like Compete, or smaller targeted panels such as comScore).

Internal metrics depend on users' computers to accept cookies and run javascript. External metrics depend on mathematicians to extrapolate what 1 million people in a DMA do based off the actions of 200 monitored panelists.

2. Differences in the definitions -- a pageview is a pageview right? Well yeah, but what about reloaded pages, what about pages viewed by people not represented in panels, what about pageviews viewed from a mobile device? You can see how each source defines their metric by what they have the ability to count or estimate.

Great, then what's the solution?

Well, first is a discussion with your boss to help him/her understand that his competitors deal with the same 40% to 60% comScore metric discount that you do.

Second, measure yourself versus the competition based on same external metric source -- so that you're measuring "apples to apples". Then identify exactly how they compute their measurements and ensure your site is registered with all means possible. Adding tags to your site pages can aid a company like comScore or Quantcast in measuring your audience more accurately.

Third, measure your individual site performance based on the more detailed internal metrics. Focus on relative metrics like percentage growth, month-to-month and year-over-year. Focusing on magic number milestones can obscure recognition of true progress and serious problems.

As with most problems, there’s no black-and-white answer – but understanding the core issue is half the battle enroute to a more actionable strategy.

Filed under  //   analytics   avinash kaushik   comscore   google analytics   media   nielsennet   omniture   quantcast   webtrends  


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10 Examples of What Analytics Success Looks Like?

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?

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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’sData 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.

 

Filed under  //   Best Practice   action items   analytics   bryan eisenberg   clickz   comscore   google   media   seo  


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Good Sign for Video Advertising, Content

Why_people_watch_video_online

According to comScore, very insightful explanation of why people watch video online -- has much more to do with convenience than it does advertising avoidance. Download the Media Fragmentation presentation.

Filed under  //   advertising   comscore   media   video  


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Searching For 'Apples-to-Apples' Web Metrics

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The Interactive Advertising Bureau is quietly trying to change that, spearheading the creation of a gold standard for Web measurement.

“The limitations and the confusion are very disruptive to our conversation with the client,” said Chris Hiland, president of media networks at Geomentum, a hyper-local marketing unit of IPG. “When you see a different number on the ad server and a different number on a log-based server, you don’t have confidence, and that keeps spend rates down,” said Dave Morgan, founder of Simulmedia, a company that helps TV companies improve the effectiveness of tune-in spots. ... Local newspapers have it tough because panel-based measurement isn’t well-suited to local sites, resulting in erratic results.

That’s why Mark Contreras is a vocal backer of the IAB’s standardization effort. He’s svp of newspapers for Scripps, he said that third-party audience estimates for Scripps’ sites range from 30 million all the way to nearly 100 million.

-- Comment --
Pick your company -- NielsenNet, Comscore, Compete -- their web audience measurements all have their flaws. So this IAB initiative is a good start to address some glaring weaknesses. Take for example that panel-based systems virtually ignore the workplace audience, which is pretty darn important to digital media properties. Add to that Scripps' audience estimates that range from 30M to 100M (really?) for their sites, and you can see why advertisers say, "Uh, I'm not paying top dollar until I'm sure how many people I'm really reaching."

Filed under  //   IAB   advertising   analytics   compete   comscore   media   nielsen   scripps  


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