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Quinnipiac Assignment 01 – ICM501 – Ratings and Recommender Systems

Ratings and Recommender Systems

Unlike the offline world, the Internet is chock full of ratings and recommender systems. Why? Because metrics are everywhere. On YouTube, you know how many people watched a video, and who made it to the end. On WordPress, you know where your readers came from. On Facebook, you are constantly being served the likings, joinings, and friendings of your friends. Plus you have likely provided any number of cues about your preferences, your age, your gender, your marital status and/or sexual preference, and your location, among dozens if not hundreds of other data points. This includes everything from indicating you are a Red Sox fan to watching a cooking demonstration video to its end, to listing your college graduation year on LinkedIn, to joining a group devoted to German Shepherd Dog rescue, to reviewing a book on GoodReads about bi-curiosity. With all of this data, attempts are made to get a clear(er) picture of a person. With the picture comes an effort at predictability.

Amusingly, as I’ve been writing this blog post, to prove the point, the WordPress Zemanta plugin is currently serving me pictures of German Shepherd Dogs and a number of articles about them, allegedly related to this post. But, surprise! This post isn’t really about German Shepherds at all, this image notwithstanding.

Quinnipiac Assignment 01 – ICM501 – Ratings and Recommender Systems
German Shepherd Dog from 1915 (Photo credit: Wikipedia)

Close But No Cigar. Not Even a Kewpie Doll

Just as Zemanta screws up, so do plenty of other sites with recommender systems. Spotify, Pandora, and other music-matching sites seem to fairly routinely not get it. In September of 2013, Forbes reporter Amadou Diallo wrote about a search for a perfect playlist. In his article, Diallo compared iTunes Radio, Spotify, and Pandora, by using various seed artists to create playlists. The matching algorithms were given Stevie Wonder, Herbie Hancock, and The Alabama Shakes. Diallo concluded that Pandora had the best matching algorithm, but there were definite flaws with all three.

To my mind, a pure computer-driven search is a misplaced notion. One of the issues is of categorization. For musical, film, book, and other recommendations, it’s all only as good as how it’s categorized, and often goods are poorly organized. Consider Johnny Cash. A country artist? Sure. Male artist? Of course. He came from a particular time period and his work was generally guitar-heavy. And then, late in his career, he threw a curve and recorded a cover of Nine Inch Nails’ Hurt. If recommender systems had existed when he released it, the song would have dented the algorithms, perhaps even fatally.

A further issue with recommender systems is that they seem to treat people’s preferences like computer problems. E. g. if you like, say, movies that involve the American South, history, and a strong male lead, you might be served, under a movie recommender system, both Gone With The Wind and Midnight in the Garden of Good and Evil. Yet one is a classic romance, whereas the other is a nonfiction work. Even if perfect granularity is achieved, and all of the seemingly relevant data points are hit, recommender systems still aren’t necessarily truly up to the task.

As J. Ellenberg says, in This psychologist might outsmart the math brains competing for the Netflix Prize. Wired (2008, February 25). [Link] “Of course, this system breaks down when applied to people who like both of those movies. You can address this problem by adding more dimensions — rating movies on a “chick flick” to “jock movie” scale or a “horror” to “romantic comedy” scale. You might imagine that if you kept track of enough of these coordinates, you could use them to profile users’ likes and dislikes pretty well. The problem is, how do you know the attributes you’ve selected are the right ones? Maybe you’re analyzing a lot of data that’s not really helping you make good predictions, and maybe there are variables that do drive people’s ratings that you’ve completely missed.” (Page 3)

There are any number of thoroughly out there reasons why people like or dislike something or other. Some are far from quantifiable, predictable, or replicable. They can’t be scaled to the entire population, or even one of its segments. Do we prefer a particular song because it reminds us of a point in our life that is no more? Do we avoid a film because it’s where we took our lost love on our first date?

Going Along to Get Along

Another issue with recommender systems is that people can often be persuaded one way or another. The Salganik and Watts study is rather interesting in this regard. These two researchers presented subjects with a number of unreleased songs and asked them to rate the songs and also download whatever they liked. Certain songs rose to the top of the charts (just like we normally see on Billboard, the Hot 100 and the like) whereas others were clunkers that fell swiftly. When the researchers switched the presented numbers, showing higher ratings for the stinkers and lower ratings for euphony, test subjects changed their minds. All Salganik and Watts had to do was convince their test subjects that this was the right outcome.

Salganik, M. J., & Watts, D. J. (2008). Leading the herd astray: An experimental study of self-fulfilling prophecies in an artificial cultural market.Social Psychology Quarterly, 71(4), 338–355. [PDF] “…over a wide range of scales and domains, the belief in a particular outcome may indeed cause that outcome to be realized, even if the belief itself was initially unfounded or even false.” (Page 2)

Are these instances of undue influence? Self-fulfilling prophecies? Test subjects wanting to appear ‘cool’ or go along with the majority in order to increase personal social capital? And where are ratings and recommender systems in all of this? Are they measuring data? Or is it, like is the case with the Observer Effect, that the very acts of observation and measurement are skewing the numbers and generating false outcomes?

Or is it, perhaps still the case, that there’s no accounting for taste?

Enjoy Johnny Cash (but only if you want to).

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Analytics Quinnipiac Social Media Social Media Class

Quinnipiac Assignment #12 ICM524 – Final Project (Journalism)

Should Journalism Be Data Driven?

For my final project for Quinnipiac University’s Social Media Analytics class, I created a short presentation about journalism and data. This video is available on YouTube.

My essential question was whether data and story popularity should be drivers for journalistic choices. Those choices are everything from what to put on a ‘front page’ to what to bold or italicize, to where to send scarce (and expensive) reporter resources, to what to cover at all.

Popularity Breeds Contempt

For news organizations looking to save some money, it can be mighty appealing to only cover the most popular story lines. News can very quickly turn into all-Kardashian, all the time, if an organization is not careful. For a news corporation searching for an easier path to profitability, hitching their metaphoric wagon to the popularity star might feel right. After all, and to borrow from last semester’s Social Media Platforms class, they have buyer personae to satisfy. If all of their readers or viewers or listeners want is to know the latest about Justin Bieber or Queen Elizabeth II, then why shouldn’t a news organization satisfy that demand?

But there is a corollary to all of this.

Quinnipiac Assignment #12 ICM524 – Final Project (Journalism)
Journalism is going to survive. I just don’t see how the businesses that have provided it will survive – Clay Shirky @cshirky #openjournalism #quotes (Photo credit: planeta)

News organizations often have dissimilar foci. If I am reading, say, the Jewish Daily Forward, I am looking for news, most likely, about either the Jewish people or Israel, or at least for stories which are relevant to either of these two not-identical (albeit somewhat similar) entities. Hence a story about the Kardashians, for example, is not going to fly unless it can be related somehow.

Ethics

Dovetailing into all of this is journalistic ethics. Shouldn’t journalists be telling the stories of the downtrodden, the oppressed, and the forgotten? I well recall the coverage of Watergate as it was happening (even though I was a tween at the time). I’m not so sure that many people today appreciate the sort of courage that that really took.

What is the future of journalism? I feel it has got to be both. There must be a combination. News organizations need to show profits just as much as all other businesses. But that should not come at the expense of their responsibilities.

This was a great class, and I learned a lot. My next semester starts on August 25th.

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Analytics Quinnipiac

Quinnipiac Assignment #11 ICM524 – ICM Top 5

ICM Top 5

The Quinnipiac Assignment called ICM Top 5 was a look at trending topics on Twitter, Facebook, and elsewhere, in an effort to determine what was really big.

As would be expected, the biggest news story, both in traditional news spreading and via social media sharing, was the situation in Gaza.

Gaza

ICM Top 5
English: Benjamin Netanyahu (Photo credit: Wikipedia)

I chose a news story about Benjamin Netanyahu talking about Hamas (according to him) violating cease fires.

I had wanted so much to avoid tweeting or blogging or otherwise amplifying the signal around the Gaza situation. But the assignment more or less forced my hand. It was simply far too large a news story to ignore. I am still less than thrilled, and have been attempting to avoid promoting any of the rather incendiary rhetoric I have been seeing in my news feeds (from all sides, I might add).

Central America

My second choice trending news topic was about Central American children fleeing persecution and ending up at the United States-Mexico border, plus all of the reactions that have been going along with that. This has been a particularly compelling news story here in Massachusetts, as Governor Deval Patrick has been trying to determine whether the Bay State can and should accept some of these children.

Ebola

My third choice for a trending news topic was the Ebola scare. With an American angle – there are a couple of Americans who have succumbed to the virus (these were people who had worked in places like Liberia) – the story was a good one to follow. It is evidently being followed around the world although the heaviest concentrations of hashtags are in the Sierra Leone area of Africa.

Films

For my final two choices for trending news topics, I decided to go a lot lighter and instead followed the release of trailers for the new Hobbit (Battle of Five Armies) and Hunger Games (Mockingjay) films. The Hobbit trailer, at least during the time period I was looking at, was the more popular of the two.

The assignment was fascinating. Journalists often see themselves as champions of the underdog, telling the stories that are otherwise not heard. But news organizations are commercial enterprises. If a topic is trending, it often behooves them to try to ride that wave.

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Analytics Google+ Quinnipiac Social Media

Quinnipiac Assignment #10 ICM524 – Google’s Monopoly

This week in class, we prepared HTML code with semantic categories and we also wrote about Google’s monopoly.

My essay is reproduced below, in its entirety.

Google’s Monopoly

Introduction – Ma Bell and Her Demise

We in the United States have been down the monopoly road before.

I well recall the telephone company being a monopoly. We were told, back when I was studying economics in High School, that it was a “good” monopoly. The teacher said that it was just the way that communications ran, and that it all made sense. The technology all went together. Installation, repairs, number assignment and indexing, and recordkeeping all went together perfectly.

Then came the 1980s and a court order to break up the Bell System. Apparently this “good” monopoly wasn’t so good after all. I had moderately high telephone bills then. Also, I was living in a dorm but we were still responsible for our local and long distance bills. I even recall standing on a line to get a landline telephone and sign a contract.

In 1984, Bell was broken up into a few regional holding companies and I had moved to an apartment in Delaware. My telephone bills, particularly for long distance, had climbed. Then later in the 1980s and into the 1990s, there would be all of these commercials for long distance carriers. But the prices remained high.

Fast forward to today. My bill is pretty close to what it was when I attended school in Delaware. But I don’t just get local and long distance service; I also get Internet and cable. For nearly what I was paying when the phone system was in the regional holding company stage thirty years ago, I get considerably more for my dollar. Breaking up Ma Bell ended up, after some initial chaos, saving me money and getting me, the typical consumer, much better services.

Google and Analytics

Let’s look at Google.

As Steve Ballmer of Microsoft puts it, “This [search] is a scale game because the market for advertising is auction-based economics. If we have exactly the same quality of algorithms but less scale in search advertising we get less revenue per search than Google which means they have more money to pay for distribution on Samsung or Apple.Rumor is they pay each $1 to $3 billion a year for distributing their search products. We have to generate volume to step up.”

It’s pretty bad when even Microsoft says you might be a monopoly.

Is Google’s attitude toward analytics driving some of this? After all, they offer it for free, and they strongly encourage website owners (commercial and noncommercial) to make use of it. But much like a man in an unmarked van offering candy, it seems to come at a price. A great analytics system definitely makes more online businesses successful. And what do successful and/or ambitious online businesses do? They buy search. And they buy apps. They click on ads and convert more, and then those ads can be sold for more. And that’s where Google makes its billions – Google websites and Google member websites. The analytics program seems to be yet another great advertisement for Google.

Furthermore, a great, free analytics package definitely inclines one to think more favorably about Google. Microsoft, on the other hand, feels like it is bribing Bing users by offering rewards. Yet when Google offers better search placement in exchange for using Google+, it doesn’t seem so disingenuous. After all, what’s Google’s slogan? Don’t be evil. What’s Microsoft’s? Where do you want to go today? It is still positive, yes. But it’s not specifically assuring a customer that no harm is intended. Is that a requirement? It might very well be, given today’s skeptical consumer culture.

Google lulls the website owner into a comfortable sense of security, that a small business can be better analyzed and make more money, if only you could rank higher in searches! Except they’re selling the same bill of goods to that website owner’s competition. What happens when everyone is perfect at search? Then it’s more money for Google, as website owners buy more paid search to try to get back on top of the heap. The analytics package rather neatly tells website owners where they’re failing. The subtle hint is – buy search and you could improve again.

It’s Not a Monopoly If you’re Really That Good

There is one corollary in all of this. A superior product or service should always rise to the top, given the free market. Consumers naturally are going to seek out better products and, when price is no longer a factor, then quality is going to be the main driving force behind usage, with convenience being important as well. Is Google a better service than Bing or Yahoo? Maybe. It’s bigger, yes. But is its size defining its superiority? As Ballmer stated above, it’s a scale game. Search Engine Watch says that Google has just over 2/3 of all searches. Bing held the second spot with 18.7%. Yahoo had 10%. The remaining 3.7% was divided between Ask.com and AOL.

A site that enormous is going to, by definition, have considerably more money to throw around. This will result in the hiring of better engineers, more development, more frequent updates, and more innovations. Right now, it just seems like Google has the best product. It does not seem to be actively trying to require usage of its services (unlike Microsoft, which bundled Internet Explorer with its PCs and was court ordered to stop doing that). An active attempt to require usage of goods or services would be a violation of the Clayton Antitrust Act. Google has been careful to not stray into Clayton Act territory. Yet if it continues to crush its competition, it may end up there anyway.

Conclusion

Google is offering the best search experience. It’s also offering the best free analytics package, which strongly encourages businesses to put their advertising eggs into the Google basket. Being better is not a Clayton Act violation. But I think Ballmer’s got a point (although of course he’s also got an agenda). The scale is so wildly out of proportion that almost anything Google does essentially promotes it as a monopoly. Much like Facebook, Google is the category killer.

Monopoly
Theodore Roosevelt

Perhaps the United States government needs to step into both areas, and put on the brakes a little on this kind of wild growth. It’s not your father’s monopoly anymore, but it sure seems to be a monopoly all the same. And the last time one that was this big was broken up, it resulted in an eventual win for consumers. Maybe it’s time the heirs of Teddy Roosevelt took an axe to Google.

References

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Analytics Quinnipiac

Quinnipiac Assignment #09 – Semantic Search

Quinnipiac Assignment #09 – Semantic Search

For the ninth week of class, we talked about semantic search, the semantic web, and semantic SEO. I had read a bit about rich snippets before, but this lecture and the readings began to really bring that home for me, finally.

Quinnipiac Assignment #09 – Semantic Search
Semantic Web “Layercake” (2006) (Photo credit: Wikipedia)

The Semantic Web is defined by Amanda DiSilvestro as being, “… a set of technologies for representing, storing, and querying information. Although these technologies can be used to store textual data, they typically are used to store smaller bits of data.”

Essentially what happens (and should happen a lot more, as webmasters continue to implement these markup protocols), is that similar sites will identify themselves similarly. Perhaps that’s an overly simplistic way of describing that, but the bottom line is that all writers, say, will identify themselves as persons. Consider the above paragraph. How does Google understand that Amanda DiSilvestro is a person? You might scoff and say, “that’s obvious!” To you and me, yes. But not to computer software, not yet. After all, what if her surname was something that, to Google, might be more ambiguous? What about the Harrison Ford character in the film, Witness?

Quinnipiac Assignment #09 – Semantic Search
Cover via Amazon

His name was John Book. But a john has multiple connotations, and a book of course is literary art. But Google does not understand that that’s a person, unless, of course, someone tells the search engine that.

So semantic search and markup ends up as essentially a means of teaching Google about ambiguity. In the current state of technology, we have to be the ones to add the ambiguity and the fuzzy thinking. Machines can’t, yet.

Practical Application

I felt so interested in, and energized by, this topic, that I installed a new WordPress plugin (called RDFace) to try inject some semantic entity classifications of my own into this blog.

So thanks, Quinnipiac!

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Analytics Quinnipiac SEO Social Media Class

Quinnipiac Assignment #08 – NESN SEO

Quinnipiac Assignment #08 – NESN SEO

Once again, I reviewed NESN. But this time, it was in order to understand a few basic SEO (Search Engine Optimization) choices that their management had made.

Programmatic Decisions

I strongly suspect that NESN has some form of fancy programming behind their online page creation. NESN SEO just seems to be way too good.

If I were to guess, I would say that their program (possibly developed in house) scrapes the title of a submitted article, wraps it in H1 tags and copies it to the meta descriptions. That same article title is the basis for that particular page’s custom URL. Hence the article, A.J. Pierzynski Designated For Assignment; Christian Vazquez Joins Red Sox is connected to the following custom URL: http://nesn.com/2014/07/a-j-pierzynski-designated-for-assignment-christian-vazquez-to-start-wednesday/ The page title is: A.J. Pierzynski Designated For Assignment; Christian Vazquez Joins Red Sox | Boston Red Sox | NESN.com. The meta description for that same page is: The Boston Red Sox shook up their situation behind the plate in a big way Wednesday. Manager John Farrell confirmed to WEEI‘s “Dale and Holley” that the team has designated veteran catcher A.J. Pierzynski for assignment and promoted 23-year-old Christian Vazquez from Triple-A Pawtucket. Finally, the keywords were: a.j. pierzynski, christian vazquez, christian vasquez, boston red sox, red sox catcher, a.j. pierzynski released, a.j. pierzynski dfa, red sox prospects, christian vazquez promotion, christian vazquez red sox.

Quinnipiac Assignment #08 – NESN SEO

Double quotation marks truncate meta descriptions. This meta description was no exception – in Google search, it simply reads: “A.J. Pierzynski Designated For AssignmentChristian VazquezJoins … Sox shook up their situation behind the plate in a big way Wednesday.” (Note: the bolding comes from Google itself).

The Power of Programming

NESN SEO programmatic work (if that’s what  it is) was just great. Pages are named properly. The URL structure is organic and easy to follow. The meta descriptions are generally excellent (the double quotation marks in my sample were probably the doing of the article writer. Perhaps the program should be refined to replace all instances of double quotation marks with single marks?) and are enticing to human searchers because they are written by professional writers.

With a programmatic solution, NESN can get this work done quickly and turn around better online product for more abbreviated deadlines. Having the computer system do this does not require writers to master SEO beyond the basics of naming their articles properly and making sure that the keywords in the titles show up with those articles.

Even better, any time the theory of SEO changes, there only has to be one change made at NESN. Simply (probably not so simple!) tweak the program to accommodate any changes, test it, and roll it out. All without missing  a deadline.

Conclusion

NESN continues to impress. NESN SEO is great. NESN.com is a well-crafted website. No wonder it’s an advertising cash cow.

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Analytics Quinnipiac

Quinnipiac Assignment #07 – A Crash Course in SEO

Quinnipiac Assignment #07 – A Crash Course in SEO

This week’s assignment was to either write an essay or record a video about a problem that a company was having with being found online.

Quinnipiac Assignment #07 – A Crash Course in SEO

The company chosen was the Miami Seaquarium, which I have never been to, but apparently they are located near Key Biscayne.

The specific task was to find a way to attract Internet searchers to their dolphin swim adventures.

Quinnipiac Assignment #07 – A Crash Course in SEO

With information about their competition, I found a way to showcase their keywords, and those of their competitors. The tool (and it is free, which is even better) is called MozBar. It allows you to look a little bit under the hood on websites. While I am also able to right-click any website and just select “view page source”, the MozBar laid things out a lot more comprehensively. The tool calculated the percentage of verbiage on that site, versus coding.

The thing that leaped out immediately was that the site did not have any keywords!

Quinnipiac Assignment #07 – A Crash Course in SEO

Without keywords, they were inadvertently making it more difficult for people searching on Google to find them. They also did not seem to realize that their site (which really is beautiful) is barely readable by search engines. Search engines like Google, Bing, Yahoo! and others can really just read verbiage, numbers, and special characters. They do not yet have the ability to read images and truly comprehend them. You and I look at a picture of a dolphin and we know what it is. Even people wholly unfamiliar with dolphins can figure out that they are animals of some sort. But search engines are completely lost. Further, the site had a lot of great verbiage, but it was all a part of the images. It was, e. g. pictures that said things like dolphin swim. But there was no alternate text to cue in the search engines.

How do you fix these problems? My essay (which I will not reprint here, as the grade is still pending) goes more into depth but there are two easy, low-hanging fruit actions that the webmaster can take.

  1. Research keywords and add them, and
  2. Add alternate text to every single image on the site.

There are a lot more things that can be done, but those two are quick and fairly easy. And, psst, they work!


 

You can find me on

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Analytics Quinnipiac

Quinnipiac Assignment #06 – NESN Key Indicators

Quinnipiac Assignment #06 – NESN Key Indicators

This week, our video assignment was about  Key Performance Indicators. Once again, I chose NESN (the New England Sports Network). They are admirably open about their online metrics. I love how they never seem to shy away from revealing all.

What was perhaps most amusing about this particular video was when I checked out NESN’s listed demographics and came up with a buyer persona.

My typical buyer persona turned out to be – ta da! – Spoiler Alert! – my husband, Jay Siegel.

Why?

NESN Typical Buyer Persona

Quinnipiac Assignment #06 – NESN Key Indicators

NESN’s audience, by far, was dominated by men. Their age group was mainly within the 25  – 54 age range, although that was not anywhere near as dominant as the gender imbalance. Finally, their geographic placement was mainly clustered around the New England and New York areas.

What was rather fascinating for me was that the biggest American state for NESN viewership isn’t in New England at all. It’s California. But that is, perhaps, more a function of California’s gigantic population than anything else. California accounts for a good fifteen percent of the American viewership of NESN. Massachusetts holds the number two slot, with ten percent. New York is third, with nine percent. Hence the New England/New York combination is already greater than that of California.

Unfortunately, Chartbeat did not show (on their free report) any states beyond the Top Five. But it would not shock me if the Top Five were rounded out by at least one or two of the other five New England states, and other Northeastern states, such as New Jersey, or Maryland. The map rather clearly indicated a bias in favor of the Northeast.

Conclusion

I continue to be pleasantly surprised at what a great choice NESN has turned out to be, for class assignments!

 

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Analytics Quinnipiac

Quinnipiac Assignment #05 – Basic Web Analytics

Quinnipiac Assignment #05 – Basic Web Analytics

Instead of creating a video, this week we wrote essays about basic web analytics.  I covered Maps of India and NESN (again). Below is my essay about NESN.

Company Brand Overview

New England Sports Network (NESN) is a regional television channel with a wide and varied social mediapresence and an emphasis on New England sports, although national and international events are also covered. The industry is cable (Xfinity) media; their home page is: http://nesn.com/, which is a WordPress blog.

The company’s Twitter handle is @NESN (https://twitter.com/NESN). Their Facebook page is at: https://www.facebook.com/NESN. Their Google+ page is at: https://plus.google.com/+NESN/posts. Their Pinterest board is here: http://www.pinterest.com/nesn/. Their Tumblr blog is here: http://tumblr.nesn.com/.

This report will cover certain quantitative metrics for NESN, in an effort to understand whether their online campaigns and presences are providing fullest value. I will concentrate on the channel’s website and will only touch upon their social presence on various platforms.

Company Business Objectives

For NESN, their objectives appear to be to draw offline traffic to their television programming, and to increase clicks on advertisements found peppered throughout the website. The objectives for their social media presences appear to solely be to direct traffic back to the website, although a secondary objective is probably to increase offline viewership for the television channel.

Website Overview

NESN’s home page changes; advertisements and stories evolve from day to day and even hour to hour. The basic layout is of a top menu with drop downs, with a banner ad just beneath it. The live blog is in the upper left corner (it has the largest news image on the page), with top stories also available above the fold. A second ad is in the upper right corner, with a video just below it. These videos mainly seem to be interviews and short highlights; there are video ads interspersed in there. I believe these are similar to, if not the same as, the ads that a viewer would see on television.

Scrolling below the fold, just below the videos, there is a static list of website sponsor logos. There are more links to stories (all story links have an image) and then there are, on the right, links off the site which go to Zergnet, an entertainment website. Circling back, the center has News Max headlines (and links), and on the left are more video ads. Below these, there are more links to stories. There’s a long vertical skyscraper ad on the right, yet another video ad on the left and then, at the very bottom, there are links to various sports topics (e. g. horse racing), NESN’s sources, and even their social media pages. Interesting enough, their Pinterest page is not listed; perhaps it is new.

The entire website is overlaid over yet another ad as the background image. I counted nineteen advertisements: the overlay, the top banner, three videos, the upper right corner, the twelve sponsor logos, and the skyscraper. This does not include various smaller banners, such as one for Red Sox Nation which contains the Dunkin’ Donuts logo. This total also does not include the links to Zergnet and News Max.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
NESN Home Page

 

Twitter Overview

The Twitter page shows a rather plain background and a branded logo being used for an avatar. Recent tweets are listed chronologically and there does not seem to be a chosen highlighted tweet. There are no advertisements on the Twitter home page itself. Tweets are a mix of programming news, images, and links to videos and less timely content, such as an interview with Ted Williams’s daughter which could have conceivably been tweeted any day this month. NESN has 164,000 followers.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
NESN on Twitter

Facebook Overview

The Facebook page (this image is a little older, but the design has not changed in the past two weeks) has a branded background image and logo for an avatar. Wall posts vary, and can be photos, status updates, or sports opinion pieces.  NESN has 222,000 likes.

Quinnipiac Assignment #05 – Basic Web Analytics
NESN Facebook page June 3, 2014

Google+ Overview

The Google+ page had the same plain background as on Twitter. NESN has just under 31,000 followers.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
NESN on Google+

Pinterest Overview

There were twenty-one pin boards.  But NESN has fewer than 220 followers! This figure is comparable to my own following on Pinterest, and I don’t have an advertising budget. However, I suspect that’s more due to the demographic disconnect (Pinterest is overwhelmingly female; sports fans are predominantly male) than anything else.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
NESN on Pinterest

Tumblr Overview

The Tumblr blog appeared to be a feed from the website. I cannot tell how many followers they have.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
NESN on Tumblr

Audience

Compete.com’s most recent data for NESN was for April. The most interesting trend was to see the number of visitors spiking in October of 2013 and then April of 2014, probably due to the Boston Red Sox capturing a World Series trophy and then the Boston Bruins being in the NHL playoffs. There were nearly a million unique visitors in April.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
NESN analyzed by Compete.com

As would be expected, according to Chartbeat, the site’s visitors geographically cluster around New England. However, there are also somewhat substantial numbers of viewers in California and Illinois. After the United States, the audience countries drop off dramatically, with Canada having only a 3% share of the audience.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
Geographic placement of NESN online audience

According to Alexa, the average visitor views over two pages, however, the bounce rate is high, at nearly 80%. Time on site is less than two and a half minutes; presumably this is to quickly check scores and top stories and move on if the audience member fails to see anything new.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
Alexa analysis of NESN site visitors

 

Acquisition

Chartbeat’s data was current, and showed that visitors came from a variety of traffic sources. Internal traffic was highest – although visitors were still bouncing off. Direct acquisition was the next-most common source of visitors, with links trailing a bit behind that, and then search. Social was dead last.

The top landing pages were the World Cup live stream and then the home page. After that, was a page about trade rumors about Carmelo Anthony, and then a more in-depth story about the World Cup.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
Chartbeat analysis of NESN visitors

 

 

Chartbeat’s view of NESN’s traffic sources showed key words and phrases. From the below screen shot, the most frequently-searched terms clearly had to do with the World Cup or Boston plus either the Bruins or the Red Sox. The mix of new visitors to returning was about 40% to 60% of all visitors, respectively.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
Chartbeat analysis of NESN.com traffic

Behavior

Chartbeat lists top pages. Combining these with search, we can get an idea about landing pages. Searches for the World Cup are drawing the audience to the live stream. The second-most visited page is the home page, understandable for a site where the second-most common means of acquisition is direct clicking, and the third is linking.

Exit pages are more difficult to gauge but, since the top links are generally to home page ads, my assumption is that audience members are clicking on the ads and, therefore, are perhaps making a conversion, but they are also leaving the site.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 05 – ICM 524 Basic Web Analytics
Chartbeat top pages for NESN

 

Results

Possible Ratings Boost

If NESN is using its online presence in order to bolster its offline television channel ratings, the cause and effect is unclear. According to Sports Video.org, April 2014 ratings were very high. However, those ratings seem to have been connected much more intimately to how the Boston Bruins were doing in the Stanley Cup playoffs, versus NESN’s campaigns on its blog and varied social media platforms. Per the article, “NESN earned a 12.7 average household rating in the Boston DMA [Designated Market Area] (20 share) for Tuesday’s [April 22] 3-0 Bruins win over Detroit, which marks the best Game 3 rating in NESN history and the second best rating for a game that was not in a series clinching scenario. The only game that was not a clinching scenario that garnered a higher rating was a double overtime Game 5 vs. Montreal in 2011, which averaged a 12.9 HH rating. The 12.7 HH rating on Tuesday now stands as the 10th best Bruins playoff rating in NESN history. NESN’s highest-rated Bruins game ever was Game 7 of the 2012 Eastern Conference Quarterfinals against the Washington Capitals (4/25/12) which garnered a 19.6 HH rating (31 Share) in the Boston DMA.” (Emphasis mine)

Advertisement Monetization

Fully monetizing the website is clearly a major objective for NESN. How successful is it? Probably the ads found above the fold get the most clicks. Would ads for Dice (a jobs website for techies) and the plain text ad for SEO firms get a lot of clicks? The Ray-Bans ad might do better, as it’s less techie-centric. But these ads don’t seem to be targeted to the audience. As for the ads that show up with the videos, if these are sufficiently similar to the commercials seen on NESN’s televised broadcasts, then potential buyers might be too fatigued with these messages to bother clicking on them.

What are clicks worth to NESN?

A visit to NESN’s advertising sales site (there is a tiny link at the bottom of the website’s home page) shows the channel boasting a reach to an audience of 4.5 million, mainly throughout the New England region. But these sales are for either advertisements on television or sporting venue sponsorships at Fenway Park or the Boston Garden. However, the contact page does include a means of requesting information on advertising on NESN.com.

So I repeat – what are clicks worth to NESN?

The Chartbeat data shows hundreds of daily clicks on advertising links. If a click is worth one-tenth of a penny, then 200 clicks makes a measly twenty cents. Multiply that by 365 days and the campaign is a disaster, at $73/year. So that is not what NESN is dependent upon.

Far more likely, NESN is dependent upon advertisers renting space on their Home Page, on their banners (both large and small), and as filler in between short video clips. The most recent article I could find on NESN’s rights fees was from 2002, and that showed NESN bringing in a cool $60 million in rights fees. After three World Series championships and the purchase of the Red Sox by John Henry, et al (the Red Sox own a controlling share in NESN), that figure has undoubtedly skyrocketed.

Clicks are nothing to NESN. The rights to the rental of space on the blog are where it’s at. No wonder the presences on Pinterest, etc. are fairly small – none of the followings on social media come anywhere near the 4.5 million reach boasted by the advertising department.

Conclusion

NESN has not come anywhere near tapping the fullest potential of social media, when it comes to audience acquisition and conversions. But right now, given their enormous offline presence, they don’t really have to.

Yet.

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Analytics Quinnipiac

Quinnipiac Assignment #04 – Media Convergence

Quinnipiac Assignment #04 – Media Convergence

Once again, we did not have to prepare a YouTube video. Therefore, instead, I am going to reprint one of my essays, in its entirety. This one is about media convergence. As media (print, television, Internet, etc.) all becomes deliverable on one piece of hardware (generally a smartphone or an iPad), and one is advertised or copied or shared on another, should our metrics and means of measuring reach, etc. on these platforms also diverge? And what does that mean for the future of measurement?


Media Convergence

Wishing and Hoping AKA The Past

Back even before television was three channels, data was gathered via Nielsen ratings. Nielsen started in the 1920s but didn’t really get into media analysis until the 1942 radio index. In 1950, it was followed by the television index. (Nielsen, 90 Years, http://sites.nielsen.com/90years/). By 2000, Nielsen had gotten into measuring Internet usage.

Throughout most of this nine-decade period, media was siloed. Radio was analyzed one way, television another, etc. But it was mainly counting. How many people watched a show? How many listened to a particular radio station? With 1987’s People Meter (Nielsen, 25 Years of the People Meter, http://www.nielsen.com/us/en/newswire/2012/celebrating-25-years-of-the-nielsen-people-meter.html), an effort was made to gather more granular data, and to gather it more rapidly. However, Nielsen’s efforts were still confined to extrapolated samples. Was their sampling correct? In 1992, the People Meter was used for the first time in an attempt to measure Hispanic viewing habits. But even in 2012, the total number of people meters in use was in a mere 20,000 households. Were the samples representative? It’s hard to say.

Here and Now AKA It’s Better, But ….

Social media qualitative measurements, including sentiment analysis, are an effort to understand viewer, user, and listener behaviors. Nielsen and the like measure quantifiable information such as time on a channel (or page). But qualitative measurement goes beyond that, in an effort to understand why people visit a website. Topsy, for example, measures the number of positive and negative mentions of a site, product, service, celebrity, etc. Yet a lot of this is still quantitative data. Consider Martha Stewart as a topic of online conversation.

Adventures in Career Changing | Janet Gershen-Siegel | Quinnipiac Assignment 04 – ICM 524 Media Convergence
Martha Stewart on Topsy, June 9, 2014

 

All we can see are numbers, really (the spike was on the day that a tweet emerged claiming that Martha Stewart had a drone). This is still counting. There are no insights into why that tweet resonated more than others.

Media convergence is mashing everything together in ways that audiences probably didn’t think were possible even a scant thirty years ago. But now, we watch our television shows online, we are encouraged to tweet to our favorite radio stations, our YouTube videos become part of television advertising, and our Tumblr images are being slipped into online newspapers. All of this and more can be seen on our iPads. Add a phone to this (or just use an iPhone or an Android phone instead of an iPad), and you’ve got nearly everything bundled together. How is this changing analytics? For one thing, what is it that we are measuring? When we see a music video on YouTube, are we measuring viewer sentiments about the sounds or the images? When we measure a television program’s Facebook engagement, is it directly related to the programming, to the channel, to viewer sentiment about the actors or the writers, or something else? What does it mean to like or +one anything anymore, when a lot of people seem to reflexively vote up their friends’ shared content?

I believe that our analysis has got to converge as our media and our devices converge. After all, what is the online experience these days? On any given day, a person might use their iPad to look up a restaurant on Yelp, get directions on Google Maps, view the menu on the restaurant’s own website, check in via FourSquare, take a picture of their plate and upload it to Instagram, and even share their dining experience via a Facebook photo album, a short Vine video or a few quick tweets. If the restaurant gets some of that person’s friends as new customers, where did they come from? The review on Yelp? The check in via FourSquare? The Vine video? The Facebook album? The tweets? The Instagram image? Or was it some combination thereof?

Avinash Kaushik talks about multitouch campaign attribution analysis (Avinash Kaushik, Web Analytics 2.0, Pages 358 – 368), whereby customers might receive messages about a site, product, service, etc. from any number of different sources. On Page 358, he writes, “During the visits leading up to the conversion, the customer was likely exposed to many advertisements from your company, such as a banner ad or Affiliate promotion. Or the customer may have been contacted via marketing promotions, such as an email campaign. In the industry, each exposure is considered a touch by the company. If a customer is touched multiple times before converting, you get a multitouch conversion.” Kaushik reveals that measuring which message caused a conversion is an extraordinarily difficult thing to do.

With media convergence, the number of touches in a campaign can begin to come together. Facebook likes can be measured for all channels. Tweets can be counted for whichever messages are being sent on Twitter, whatever they are about. Will attribution be any easier? Hard to say, but if the number of channels continues to collapse into one, will it matter quite so much in the future?