As mentioned in my post last week about Troy Polamalu, the Pittsburgh Steelers were mentioned 2.5 millions times on Twitter during the NFL football season (Sep 9^th, 2010 – February 6^th, 2011). More specifically, the term “steelers” was mentioned 2.5 million times per our data collection tool Rowfeeder. This term’s three largest days were 1/23/2011, the day they won the AFC Championship; 1/15/2011 the day they beat the Ravens in the divisional round; and 2/6/2011, the day they lost the Superbowl.

The below graph shows average daily mentions for the term steelers throughout the season and highlight the high volume times throughout the season.

It appears a bit skewed thanks largely to the fact that there were 380K mentions on the day that they won the AFC championship. You’ll notice that this dwarfs the day of the Superbowl where the term had 103K mentions. In the case of the Steelers a major win translated into almost 4x the amount of mentions that a tough loss does even though the magnitude of the game was much larger in the loss. What is also interesting is that the previous game, on Jan 15, when the Steelers beat the Ravens, it too had many more mentions than did the Superbowl. Thus, it’s plausible that in this case positive sentiment overwhelmed and drove the mention count upward as fans celebrated their team’s victories.

Let’s look at some sentiment for mentions on Jan 23rd.

• 35% of all mentions contain the phrase “GO STEELERS” or contain a smiley.
• 15% of all mentions contain the words “win” or “love” and reference steelers (not jets, bears, or packers, or go, or smiley)
• Less than 10% of all mentions contain any sort of derogatory phrase toward the Steelers.
• 40% of all mentions are too ambigious to determine true sentiment.

So, roughly speaking there was 5 times more positive sentiment than there was negative sentiment, which is pretty good in the realm of sports where you have very opinionated fans, and then you have fickle fans. A team like the Steelers seems to have a very strong fan base who positively reinforce their team.

The question then might be who is tweeting?

Let’s take a look at some location data for January 23:

Mildly surprising that PA doesn’t hold a larger market share of tweets, however this state has a smaller population (and also splits the population with the Philadelphia Eagles). It’s not surprising to see NY as the top state, and CA as the third state. In fact, as the secondary graph shows, essentially the top 5 states by population are in the top 6 of percent of total mentions. So really this is unsurprising data in my opinion.

An interesting side note: of the mentions with the term steelers, here was the breakout of mentions that also contained a players last name for the 1/23 game:

Mendenhall (RB): 2,489 (121 rush yds, 1 TD)

Roethlisberger (QB): 2,296 (10/19 completions; 133 pass yds; 2 INT; 21 rush yds; 1 rush TD)

Tomlin (coach): 1,591

Ward (WR): 1,132 (2 catches for 14 yds)

Pouncy (C): 1,150 (broke a bone in the first quarter)

Polamalu (S): 832 (4 tackles)

Taylor (DB): 773 (3 tackles; game changing Forced fumble)

Harrison (LB): 266 (5 tackles)

Timmons (LB): 61 (10 tackles; leading tackler)

William Gay, a defensive back actually returned the fumble forced by Taylor for a 22 yard defensive touchdown that turned the game in the Steelers favor. However, filtering on the term Gay, did not render usable data, and at the very most it returned only a very small amount of data in total.

So again, it seems that positive actions combined with increased importance of a game in sports generate a lot of positive sentiment for a team, and thus drives mentions upward, while negative outcomes tend to lessen the amount of mentions. Also, higher profile games tend to generate more interest from a larger audience. I would wager that if you compared the location data for the AFC championship with that of a regular season game, a larger portion of the mentions would come from the local area. I shall write about that in a future post.

NY Daily News - Robbins/Getty Images

Over the next few posts I will be analyzing some social data for NFL teams and players pulled from Twitter using Rowfeeder and Scoutlabs interfaces.

Prior to the start of the NFL season, Carlos and I pondered whether a player could have more prominence than a team on a social network. Or, if not as prominent, then how does a significant player’s social prominence compare to a team’s social prominence. Further, would a significant injury, or amazing play show up in social data? Would it follow real time? Would there be continued talk about said injury or play hours or days or weeks afterward?

Several factors we considered: was the player active on twitter (and have a verified account); did the team have an official and active twitter account.

This post will focus on Troy Polamalu. We tracked mentions of “tpolamalu” – his official Twitter handle and “steelers” – the team’s official Twitter handle. Data was tracked from 9/8/2010 (the Wednesday before the season “kick off” game) to 2/6/2011 (the Superbowl). So it’s pretty amazing to have data for a player and a team from the start of the season all the way through the Superbowl (considering the chances of selecting the right teams to follow is 1 in 16).

TPolamalu received 106,985 mentions over the course of the season. Pretty impressive for the Defensive Player of the year – Avg of 718 mentions/day (but more on this in a couple paragraphs). Steelers received 2,518,000 mentions. 2.5 MILLION mentions on Twitter. So I’m going to devote a little more time to the Steelers data set before providing some analysis, but I promise to publish that soon. Again, thank you to Rowfeeder for tracking this data for us!

For TPolamalu there is a definite trend of game days being the most significant days, and moreso, big games like the Superbowl and AFC championship. More minutely, it does appear that the majority of the mentions happen during game time on game day. I’ll have to append a heat map for reference at a future date.

Here are TPolamalu’s top 6 days of Twitter mentions:

1. Defensive Player of The Year (1/31/2011)(No Game) – 4,166 mentions
2. Super Bowl (2/6/2011) (Loss)
3. AFC Champion (1/24/2011) (day after Win)
4. Game Day (12/5/2010) (Win)
5. Game Day (12/12/2010) (Win)
6. Bigest Online Shopping Day of the Year (11/29/2010) (No Game)

Late November and into December is where daily activity really started to pick up, probably due to increased awareness of the team’s Superbowl run. But it’s also holiday shopping season. To that end, surprisingly, Cyber Monday is also a good time to talk about TPolamalu because on the biggest day of the year for online sales, because it was the term’s 6th most active day with 1,815 mentions. Maybe that’s why his jersey was the #1 nfl jersey sold this season!

Troy Polamalu suffered an injury in the 12/12 game and did not play in the 12/19 game vs. the Jets (they lost), the 12/23 game vs. the Panthers (win) or the 1/02 game versus the Browns (win). These days all saw much less traffic than the two games mentioned above in December (when Troy played). So out of sight leads to out of mind? Possibly. It definitely seems to answer our question of whether an injury can affect social data: yes it can. He suffered an injury on 12/12 which was his 5th most active day and there were plenty of mentions of his injury in the data, and then the following 3 weeks when he does not play his social mention traffic dwindles down closer to the average seen earlier in the year. (It be interesting to compare this to a player who played all games in the month of December and saw a continuously higher mention count than in the previous months! So look for that soon.)

Further, during the month of December, TPolamalu mention activity averaged 200 per day vs. approximately 50 during the months of September, October, and November on non game days (and non award recognition days).  Daily average stayed approximately the same in January/February when taking out the two peak days in those two months. So, TPolamalu played 3 games each in September and October, and 4 games in November versus 2 games in December, 2 games in January, and 1 game in February, yet his mentions for the month are much more populous in the latter months. So it seems evident that as the team built towards a Superbowl appearance, and Troy was being recognized for his accomplishments, his social prominence grew significantly even when appearing in less games.

In summary: for Troy Polamalu, news of his personal recognition as the best NFL defensive player of the year, and witnessing his injury caused recognizable spikes in his social prominence. More important games such as participating in the most watched television show in US history also led to a higher mention rate. His absence from the football field seemed to lessen his social prominence. Cyber Monday also seemed to cause a spike in TPolamalu’s mentions, probably due to a larger volume of internet traffic in general. But as prominent  a player as Troy Polamalu is, his social prominence is only 4% of the Steelers (this will be an interesting comparison to Peyton Manning and Tom Brady’s social prominence which will come in a later post).

My next post will compare some of the similarities and differences between TPolamalu’s mention data and the mention data of Steelers.  As well, in a future post I will break down some hourly and possibly even by the minute details where Troy made a significant contribution, or was injured and compare this to mention data for the Steelers as a whole.

Image hosted on the Denver Post

For the past two years, I’ve posted something about the Superbowl, however neither we’re very data driven. Two years ago, I wrote about branding during commercials. Last year I wrote about how brands were beginning to use social media as an alternative to the traditional paid media channels. This year’s Superbowl was truly all access, mostly due to the effect that social media has continued to have on our society.

To this end commercials were even geared toward a more social perspective. Groupon.com advertised several commercials explaining the benefits of group deal buying. Many brands again took to the social space ad launched campaigns there. Foursquare even had “the superbowl” as a top trending location to check into. However, after checking in I was disappointed to learn that my location was not close enough to the actual Superbowl to earn points or a badge.

Several brands attempted to create a tie in between traditional media and social media. Specifically, Audi and Mercedes-Benz. Each launched a twitter campaign with the hope of creating a trend. These campaigns were actually divulged well before the Superbowl, so I was able to collect some data on them. (Data for this article is from RowFeeder and from Lithium)

Audi

Audi claims to have been the first company to use a hashtag in a commercial. As such this was their campaign. I believe their intentions were good and I’m surprised that more brands have not used a hashtag in their commercials. They are quite abundant in online media, so it only seemed a matter of time before they become a regular occurance in traditional media. That said, Audi’s execution of the plan was poor and thus led to a poor showing in the results.

Audi’s recent ad campaign has been directed at Mercedes and it’s seemingly stuffy clientele. A play on the children’s story “Goodnight moon” was in a commercial that aired during the AFC and NFC championship games two weeks ago. It was well received. It’s commercial that aired on Sunday was also well received, as they made good use of a cameo by Kenny G. However the campaign itself and the use of the twitter hashtag, were convoluted and not quite connected to the campaign. They chose the term #progresseIs and it was show very briefly between the “end” of the commercial and before Kenny G appeared on screen.  To clarify, this is spelling “Progress Is”, not “Progress Els”. Audi’s mission for this current campaign is that their cars are for people who are living a more progressive lifestyle. So I can see the relevance, but I could write an entire blog on why this is a terrible hashtag. I can also see why they chose to capitalize the “I”, but again, the point here is pretty evident –poor execution on their campaign.

The data tells a very interesting story.

In the days leading up to the Superbowl, @Audi averaged roughly 50 mentions per day, until the story about their campaign came out on 2/3. On this day, Audi  is mentioned 446 times on Twitter. #progressIs has no mentions until 2/2 where it has 29 mentions (someone with some inside knowledge I assume!) Then on 2/3 when the story broke this hashtag had 722 mentions and became a trending topic (the hashtag ending “els” had an additional 229 mentions on 2/3). On Superbowl Sunday @Audi had 1,131 mentions compared to 113 mentions of “progress Is” and 29 mentions of “progress els”.

So it wasn’t a complete loss for Audi. They did manage to create some buzz for their brand at the very least. And the author who broke the story of “progressIs” managed to create a ton of buzz for the hashtag.

Mercedes-Benz

Mercedes-Benz is arguably a more recognizable brand than Audi, thus it was not surprising to find that it averaged 1,800 mentions a day on Twitter for the week leading up to Superbowl. So the campaign by Audi, was seemingly just a small chink in the armor. However, while their execution of generating Twitter buzz may have had a slightly better result, the data seems to show that the execution may have been just as marginal. Mercedes-Benz attempted to host a ‘tweet-race’ in which four teams competed in a race based on how many tweets they received. Mentions of “mbtweetrace” were 2,995 on 2/3 when the story broke (the event had actually been going on for several days before the story however). 2/4 saw another 2,550 mentions, however the mentions fell off dramatically by Saturday with only 296 and on Superbowl Sunday there were only 91 mentions of #mbtweetrace.

That said, the individual teams which were “fueled” by Twitter mentions of their specific team names, or Twitter handles actually saw much more traffic than the race hashtag itself. There’s an interesting geo-location aspect here as well, since the teams traveled from four different locations across the country. The team from L.A. received nearly double the amount of mentions as did second place from NYC and almost triple the amount of mentions as the teams from Chicago and Tampa. None of these teams received significant mentions on Superbowl Sunday (150 mentions for the team from L.A., but every other team was well below 100 mentions).

So, in all I think there was some evidence of a bump in brand awareness on Twitter for these two brands, but moreso for Audi than Mercedes. However, as evidenced in both campaigns, a better execution will need to happen before another brand tries to influence a hashtag via traditional media. At the very minimum an easier hashtag should be used and it should be made more prominent in the traditional advertisement.

Coming later this week: tracking a team and player Twitter mentions for the entire season through the Superbowl.

Image credit: http://www.shavingstuff.com/pictures/Straight_Razor.jpg

Occam’s razor states that “the simplest explanation is more likely the correct one.” As an analyst I’ve tried to live by that principle as often as possible. However I think it’s time to take it a step further.

The simplest way to get the simplest answer is most likely the correct way to answer it.

I feel this is especially true in analytics. If your “analysis” time consists of this: 25% planning your research, 50% figuring out how to pull the data, 20% pulling the data and finally 5% analyzing it, then I feel that you are doing it wrong! However, this may not be your fault. Maybe you do not know any better. Maybe you have no choice because your analytics provider is inadequate. Either way, the time for change is now.

Do you know your analytics program like the back of your hand? You should. While I will contend that a Web Analytics certification should not consist solely of being an expert on using a platform, you should know your platform inside and out. In fact, it would do you some good to know a little about each of the major platforms out there. If you are an analyst at an agency, you probably have the luxury of at least occasionally using multiple analytics services. Most platforms offer some sort of certification program that will get you to at least an 85% understanding of their complete product, and should make you an “expert” of that platform.  If you are an employee at a company and only have access to one platform, you can very easily inquire about other platforms at a WAW or WAA event.

• Knowing your analytics package alone can help you determine the simplest way to find the simplest answer.
• Identifying what your analytics package lacks will help you figure out new ways of obtaining or slicing your data to get at your answers.
• Utilizing more than one resource for analyzing and conveying will help you to generate more thoughtful and useful recommendations

Is there a consistent problem that you run into where you have to perform special actions in the analytics platform to generate the right data? Consider downloading a raw data dump and write a macro in excel that will manipulate the data into the proper fashion that you need to answer your question. Further, if you import your analytics data into an in-house database, but get stuck on how to create a proper output there are plenty of data visualization reference guides that can help you create easy to understand, but comprehensive charts.

Does your boss require a power point presentation for every analysis? Templatize the PowerPoint and write macros so that the data is easily inserted from excel into PowerPoint. Further, try creating a robust excel document that will cater to the things that your boss typically requires in your analysis and present the analysis in excel to her or him. You might surprise her with how clean the report looks and how much more presentation can fit on the screen or sheet of paper through excel.

The point is, simplifying what you do so that you can focus on output rather than input will give you exponential amounts of time to drive the output home with the decision makers so that your insights lead to real and actual change in a shorter amount of time. Just because it’s a simplified approach does not make your output any less actionable. In fact if you start allowing your “analysis” time to be: 25% planning your research; 10% figuring out how to pull the data; 10% pulling the data; 30% analyzing the data and finally 25% creating your final output, you should have a much more profound and insightful analysis. I will admit that I don’t know if that is the exact formula for success but I believe it is better than my previous example above.

I’d love to hear more of your “simplification” tips for figuring out short cuts in your analytics program, easier ways to pull data, easier ways to massage the data, and easier ways to create an actionable output.

Have you ever lost money in a vending machine?  Even more tantalizing is when you put money in, make a selection and then said selection gets stuck?  No matter how hard you shake and bang the machine your selection hangs on for dear life.  They’ve added a theft shield in the bin so there’s no way you can stick your arm up there to snag the selection.  Your only choice, if you are lucky, is to call the 1-800 number and give them your info and wait 6 weeks for your $0.75 check to arrive in the mail so that you can go deposit it and be vindicated.

In a lot of ways, the life of a web analyst parallels the above scenario.  Sometimes, you make a recommendation based on data that you’ve pulled for an analysis and it falls on deaf ears.  No action is ever taken upon your recommendation.  Other times, your recommendations are heard, and the feedback that you receive is that this is great insight and the creative team is going to take action to make the necessary changes.  The problem is, the creative or development process can sometimes take weeks or months to complete.  (Depending on the size and efficiency of your company)

If you are like me, you need instant satisfaction.  So weeks or months just won’t do, much like getting a check for $0.75 six weeks after it was lost in the vending machine doesn’t really rectify that disappointed feeling you get when your selection teeters on the edge of your wits.  However, more important than your need for satisfaction is the needs of the customer.

You pulled customer data and made a recommendation based off of this data.  Data tells you what the customers are doing, or possibly what they are not doing but you want them to do.  Thus your recommendation is based off of the customer.  It’s possible that you have qualitative information to support your analysis.  So the recommendations are based off of what the customer is telling you and thus if there’s an issue that needs to be addressed it can’t wait weeks or months.

Of course all of this depends on the context of what you are reporting on.  If you are reporting on a one-off project that won’t be live again for another few months, then sure, the changes can take a few weeks to take place.  But if you are reporting on a new feature that went live on your site and you discover something major that needs to be changed, your creative or development team needs to be able to react quickly.  Typically, small companies can react fairly quickly and make changes, but large companies seem to be more cautious and make absoulutely sure there’s no issues with something before going live.  This can be very frustrating.

I’d love to hear your experience with this be it with a small, medium or large company.

With the failures in adoption of Google Wave and Google Buzz, I think its time to question whether Google can really be considered a thought leader in the social universe.  When you think about it, Google started as a very anti social website.  The original appeal of Google was its simplicity and minimalistic look.  Google had the opportunity to become a more social website when it created iGoogle, but it unfortunately peaked before “social” was a concrete idea.

I think iGoogle could be a good portal for a social forum, similar to what Yahoo tried to do with Yahoo 360.  iGoogle would be great because you would have multiple apps to find interesting things to share all in one page, and at the same time you could utilize Google search.  You could then have access to search results that also contain social links thus furthering the social cycle while at the same time, allowing Google with an opportunity to add to possibly add to their bank account.

This could probably be a gold mine for Google if they would just take advantage of it, but instead they think they can come up with other forums that sound good in theory but fall short in practice.  So, you heard it here.  Google is best at being anti-social, and not so good at being social.

I recently attended the Coremetrics 2010 client summit.  My role there was dual purpose.  Officially, I was there as an advanced Coremetrics user for the company that I work for.  As a three time attendee of the conference, my main goal was to make sure that my co-attendees enjoyed themselves and gleaned some good information specific to their role at our company.  Unofficially, I attended the conference as a published author of a web analytics book and co-owner of the website on which you are reading this post.  My main goal in this capacity was to continue making contacts and crowd source the topic of the next book that Carlos and I will publish in January.

The gist of the Coremetrics conference is this: keynote speeches, breakout sessions on specific web measurement and web marketing topics, meet and greet with a multitude of vendors, showing off new features of the new analytics tools, and socializing between clients.  The gravy of the conference, as is with most conferences, is the time available for socializing and bouncing ideas off of each other.  I balanced this time between being a web analyst for a large company and engaging my peers as a fledgling thought leader in the web analytics arena.

As you might have previously seen on this website, we’ve published a poll of four different book topics for you to choose from.  We’ve done some crowd sourcing over the multitude of social media forums and have had a good response from our friends and followers as to what book they would most like to read.  I felt that it would be a brilliant idea as I was chatting with my peers at the conference to give them the opportunity to peruse the four book options and make their voice heard.  So I set out to this task in the midst of enjoying the rest of the conference and learning some brilliant new marketing and analytics ideas.

It was interesting for me because most people at the conference recognize me from my company name, but not as many knew me from my previous book.  Such is life sometimes.  It definitely added an interesting perspective for me and for the peers that I spoke with.  Most analysts it seems, are content with their single job and don’t necessarily take it upon themselves to b ranch out.  For me, writing a book and keeping up with a web analytics blog has allowed a great outlet for me to expand my analytics knowledge while at the same time, allowing me to share some of my knowledge with my readers.  If you are reading this I hope it is because you are like me and are seeking additional knowledge and are not satisfied with just doing your job.

If you have not attended a web analytics conference, or any type of web marketing conference, I encourage you to do so.  Specifically, if your analytics provider is hosting a conference, there is a mint of information you can glean off of the presenters and your peers alike.  It might be very minute and tangible such as how ad retargeting works, or it might be more topline and holistic like why tagging matters, or why segmentations helps better identify what your customer is doing on your website.  As well, if you are like me and you want to make a bigger name for yourself, attending a conference is great for making acquaintances and garnering a following.

“Crafty” analysts will often ask, “If you could only have one metric, what would it be”.  I have a hard time answering this because I think it’s a dangerous proposition.  When you only look at one metric you don’t get a holistic picture of your website.  For instance, I’ve heard practitioners say, “Bounce is not important”.  By itself, no, it’s not that important because you don’t really know what the metric is telling you.  I’ve also heard, “Conversion is the only metric you need to worry about.”  Again, not true.  If my conversion is up +25% month over month, why?  I need more info.

Pairing metrics is crucial to analysis.  If you don’t, you’re simply regurgitating a data point to your listener.  You cannot glean actionable insights from a single metric.  Further, you can cause unwarranted panic if you just speak about a single metric.  “Our Average Order Size dropped -20% last week!”  “Oh man!” … “Oh my gosh, what does that mean?”

So now you ask, “Ok, what metrics do you recommend that I pair together?”  It can definitely vary depending on what you are trying to determine, but here are some of my more frequently used pairings:

• Traffic, conversion, AOS, and then by segment (new / return; organic / paid, etc) – mostly used when analyzing total site (ecommerce sites)

• Bounce, time on page, traffic and then by marketing source and by browser for top 5 entry pages – bounce segmentation can indicate if a certain traffic source is not being directed to the right page on your site, and as well can tell you if you might have some technical issues with a particular browser

• When measuring a video engagement: traffic to area, video category total starts, video category total completions (and thus an overall completion rate); top viewed videos by starts; top completed videos; videos viewed per visitor.  Also depending on your analytics provider you can get more specific such as pauses, average completion percentage (i.e. how many completed 50% of video or 75% of video) etc.

There are tons of metric pairings that help give you deeper insight into your projects.  My philosophy is to ponder whether the glass is half empty or half full, if I feel that it’s half empty, I look for other metrics to glean additional insights; if I feel that it’s half full and I’ve already dug deep enough, I stop before I succumb to paralysis by analysis.  Again, my key point is using one metric to analyze something is a dumb idea.  So don’t do it.

I recently had surgery to remove a “floating” bone fragment from my Talus bone in my ankle.  Once removed the goal is to have the blood cells re-grow bone tissue to fill the gap area.  Thus my doctor ordered me to stay off my foot for 6 weeks.  So my options were crutches, or one of those fabulous new inventions – the knee scooter.  I’m a fairly athletic and still young guy, so I chose crutches.  I had also used crutches ten years ago, when I originally had broken the bone.

 Here are my impressions of using crutches so far:  1) its frustratingly hard to get to where you want to go; 2) you are limited in what you can do for yourself; 3) you wish that everyone would cater to your needs; 4) you get tired of telling people “what happened”.

 So how would I relate that to Web Usability insights?  Let’s break them down one by one.

 It’s frustratingly hard to get where you want to go.  The golden rule of web usability is to make it easy for the customer to reach the intended goal.  When you design your website make sure that you have a clear path for the customer to follow.  Make sure that your navigation is evident and consistent.  Colors and photography can make or break the first and last impression of your website, so make sure that what you use is pleasing to the general audience.  As well make sure it speaks to your audience: are you catering to business professionals? Doctors? Moms? Etc.  The biggest thing to remember is that a cool navigation bar may not be what the customer wants to use to get to the end goal, so make sure that your site is quick and easy to use and that you are always directing your customer to the end goal and not taking them away from it.

 You are limited in what you can do for yourself.  Again, having a clear function unit and clear navigation will help turn your visitor into a customer.  Have an evident onsite search placement and utilize a good search query vendor.  It’s one thing to have an onsite search placement; it’s another to return good results for a search.  You should have a dedicated person monitoring the results and tweaking as needed so that you can ensure that your top searched on terms are returning positive results and ultimately leading to a conversion.  Product recommendations and reviews are also helpful to visitors who aren’t sure of what they want or need.  Hover-view over images on thumbnail pages also reduces browsing and allows for one less click the customer has to make.  Persistent shopping bag is a great feature in that when you add an item you have the option to go to your shopping bag or continue shopping and adding more (again reducing the pogo sticking from product page to shopping bag).  Advanced sort and filter options on view all / thumbnail pages – while some customers enjoy browsing through 100’s of items others like to narrow their search instantly, having these advanced features will enable that ability.

 You wish that everyone would cater to your needs.  It’s hard for you to design a website that meets every single visitor’s wants and needs.  However, you could take the approach of something like iGoogle where you allow the customer certain customizations that apply only to their account.  Such options might include navigation preferences; certain features turned off such as product recommendations or persistent shopping bag; font or background color changes.  Another thing to consider is your customer loyalty / retention program.  As a frequent shopper of certain sites I appreciate getting special shopping events exclusive to preferred customers, as well as cash back or rewards programs.

 Finally, you get tired of telling people “what happened”.  I shouldn’t have to repeat myself, and I certainly shouldn’t have to log into a site every time I visit.  Further, I don’t like visiting sites that I have to re-set my preferences every time I go to it.  Your site should have a cookie system that remembers its visitors log in info and further keeps its settings.  These settings might include: video auto play vs. not auto play; sound on / off; view 25 vs. view 100; etc.  There are certain times when I don’t mind repeating myself, such as when I want to purchase something.  I don’t necessarily like to store my cc info with a site, however I recognize that many people are comfortable with this.  Either way, it is a best practice to ask for log in credentials when beginning the checkout process (which is hopefully being hosted on a secure server).

 So there you have it.  Some practical usability insights that you may or may not have already considered.  Most of usability is just using common sense and thinking like a customer.  Some usability takes a little more insight.  I encourage you not to stop with just the above advice.  There are plenty of books on Heuristics that will take you to an even deeper level.  You can also buy our book User Driven Change, which will give you some great actionable ideas for website optimization taken from a customer perspective.

Last week, Coremetrics, Omniture and WebTrends announced features that allow their respective users to measure certain aspects of Facebook.  My review of these announcements, so far, indicates a parallel product from these companies.

Omniture announced a partnership with Facebook that will allow customers to refine their Facebook ad campaigns. Utilizing their Search Tool “Search Center Plus”, Omniture customers will be able to compare Facebook ad campaign metrics alongside other media channels and increase their ad spend on the social network.

Coremetrics announced that they have been able to partner with Facebook to utilize their Impression Attribution tool,  which can record something as passive as an ad impression on the Facebook site and, utilizing cookies,  tie it back to the customer activity on your website.  As well the data is set against your other ad campaigns so that you can compare and contrast.

Finally Webtrends’ announced (technically Webtrends’ announcement was the week prior to the others) that they have a way to “scrape” data from Facebook, Twitter etc, using an API and can tie the data against other ad campaign data.

Sounds a little redundant doesn’t it?  That’s because for the most part it is the same thing.  The key here is that Facebook has finally opened itself up to these companies to allow the respective API code into their system.  My understanding is that this API has been working for Twitter measurement for some time now.  The ability to do the same type of tracking that you can tie into your main analytics program is a big step forward in Social Media measurement.

Its important that Facebook is allowing these partnerships.  It’s too bad that they didn’t make the announcement themselves.  Not that Web Analytics needs validation from social media (I’d say Web Analytics is more commonly accepted as a company need than social media in most businesses today, but that might not be the case tomorrow!)  It is important that all three companies have announced a product that will help with social media measurement and that the product is fairly similar.

I’m interested to know how analysts will use these tools to analyze their respective clients’ social media engagement.  These announcements show that social media tracking is an important piece of web analytics and should be an important piece of your social media campaign.  I’m glad that the big boys in the web analytics world are taking social media metrics seriously.  My only concern is that the analysis stops here.

Engagement is only once piece of social media measurement but it is a big piece and right now seems to be the most tangible aspect of SM tracking.

My hope is to follow up to this article with a side by side comparison of the Social Media dashboard / report for each vendor’s system.

Would love to hear from anyone utilizing any of these three companies’ social media tracking tools on what you like and don’t like about the tool.