Posted by Jim Cain on December 5, 2011
There are a lot of terms that get badly abused – to the point where they are annoying to hear. A few personal examples would be the words ‘cloud’, ‘big data’, ‘guru’ and using the label “2.0” for anything other than a software release. The word “social” is border-line with me right now as well.
The word “dashboard” is not on my hate list, but it seems to be on a lot of other people’s. Everything has a dashboard now, from software products, to consulting deliverables (we do them weekly for our clients), even video games and LinkedIn have dashboards in them.
So, I get why the thought of another dashboard would make many people want to barf, but it doesn’t make me think they are any less vital to being successful with data.
A few points below that you should consider before you give up on dashboards (I had a great Karate Kid reference I was going to make, but I have been informed that I need to dial back on the 80s film references…).
The obvious point:
A dashboard you don’t love wasn’t built properly: A good dashboard is supposed to provide ‘at a glance’ understanding of something you care about, giving you the ability to have increased understanding you wouldn’t have achieved any other way. If you are indifferent to a dashboard, it sucks. Get rid of it and have one crafted to your exact needs.
Less obvious but critical points:
1) Dashboards create commonality of language and goals: Ever notice that sales and marketing people use different words to describe the same thing? Ever notice that they don’t tend to get along? A well crafted (and agreed on) dashboard has the ability to create significant alignment in an organization, not just between different departments, but between different levels of the org chart. In helping a senior stakeholder build an exciting and relevant performance dashboard, we are very educated on where to focus our analysis on their behalf.
2) Dashboards decrease “weaponized” analysis: In organizations without proper executive dashboarding (so most of them…), the lack of common language, goals and structure creates “analysis anarchy”. This means that execs often ask the analysis to provide reports and data to support an idea or initiative. We call these reports ‘weaponized’ because they are only being created to provide data support to help win an argument, i.e., “Build me a report that shows how marketing has been wasting money on leads for the last 6 months”. Competing on analytics is supposed to be an external activity, not an internal one. It’s very hard to weaponize your reports when the whole team ultimately works again an agreed on performance framework.
3) Good Dashboards maximize analyst value and contribution: the lack of structure around data consumption is the Petri dish that dumb questions grow in (would that mean ‘bad culture’?). Many of the ad-hoc questions that web analysts get are based on a lack of overall understanding about digital. We find that instituting an appropriate and valuable weekly performance dashboard cuts down on ad-hoc requests significantly, and increases the quality of the questions being asked. Good questions tend to be harder to answer; your analyst will still be 100% utilized, but purely on creating insights of high business value.
If you are making plans for 2012, and someone comes out against using a dashboard, realize that they are tired of the abuse of the term, not the value proposition.
Just call it something cooler, like a ‘executive performance visualization’. At the end of the day, a well executed dashboard can have both corporate and competitive effects that are far reaching.
Cheers,
Jim
Posted by Jim Cain on October 14, 2011
As we get closer to eMetrics NYC, and my presentation on Turning Executives into Analysis Believers, it’s time to add one of the final pop culture touchstones we talk about at Napkyn Global Headquarters.
A quick recap on past write-ups:
- Batman: The boss, not the analyst. A great executive-facing analyst knows who the hero of the story is, and works to empower them, not overshadow them.
- Doc Brown: Great analysts will hack together what they need from what they have, not just stay inside a given tool. They will also focus on the temporal nature of measurement, using the past and the present to predict the future.
- Columbo: Relevant analysis can’t exist in a vacuum. Constant interviewing of your internal stakeholders will help you learn their language and motivations, and ensure that your analysis is timely and relevant.
This week we are focusing on one of the least analytical and perhaps one of the most important of our pop culture references: Sam Malone from Cheers.
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Posted by Jim Cain on August 17, 2011
The good feedback continues on our series of pop culture references, so much so that I will be touching on this theme in a presentation I am giving at eMetrics NYC (click the logo at the end of this post to sign up, it’s an amazing event).
I’m awfully pleased that this series seems to resonate in the measurement community, because I know a lot more about TV shows from the 80s than I do about how eVars and event scripts work. And for those of you just tuning in, that’s the point here.
A good story, listened to by the right person, will trump a spreadsheet every time.
Now having the story be accurate, and earning the right to have the appropriate person listen, are hard to do. This week’s pop culture reference is a personal favorite of mine, and once again is a reference that I make continually at the office, especially when training new analysts on how to engage their new executive stakeholders through the Analyst Program.
Unfortunately, I also tend to have to lend them the first season of the show, because anyone under the age of 30 has never heard of Columbo.
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Posted by Colin Temple on August 5, 2011
Google Analytics has a design approach to web analytics software that differs from many of its competitors. Whereas some tools require you to pre-define anything you want to track (such as events, page names and campaign data), Google Analytics allows you to define these in the code or URL of a page, and simply accepts whatever data is thrown at it. This greatly cuts down on the cost, in both time and money, of implementing and maintaining a Google Analytics account. The ease of implementation has been a huge win for Google Analytics.
However, this philosophy comes at a price. Because it indiscriminately accepts any data it’s given, it accepts any data it’s given. The result is that, if someone with the right skills is feeling particularly malicious, they can vandalize and seriously distort your business’ data. There are two ways this can be done.
We’ve been aware of these potential issues for some time now, but we wrestled a bit with the decision of whether or not to post this. On one hand, we like to share our knowledge and, since this is a very real fact about Google Analytics, it’s good for GA users to be aware of it. On the other hand, we’re potentially teaching people how to mess with someone’s GA deployment. Ultimately we decided on transparency and honesty — after all, we’re also going to tell you what you can do to protect yourself from these. But we must begin with a caveat: we do not endorse doing anything like this. We offer this information so you can be aware of potential security risks with your own data, and take the necessary steps to protect your data integrity. We are strong supporters of the Web Analyst’s Code of Ethics, and though that code doesn’t say much about messing with others’ data, the idea is generally to be open and honest with data.
(Update: I should also point out that Google Analytics is not alone in being vulnerable to some of this. The approach to campaigns and ease of copying other data makes it easier than with some tools, I think, but those stem from Google’s strengths rather than weakness. I offer Google Analytics up because they don’t have a service level agreement for everyone, and hence it’s up to you to protect some of your data. Despite any vulnerability, I do want to be clear that Google Analytics is a fine tool and this alone is not cause for alarm, just something to be aware of when implementing this tool, and by extension, others like it.)
With that out of the way, here are the potential exploits we’ve seen:
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Posted by Colin Temple on August 2, 2011
I’ve been building up a technical post series on tracking social media hook-ups in Google Analytics. I wrote about tracking Google +1 Votes before Google automated it. After they unveiled new Social reports in GA, I followed up with an update on tracking Facebook Like buttons. Next on the docket: LinkedIn Sharing … because as analysts, to be ready to answer the tough questions, you really should be tracking everything.
The method of tracking for LinkedIn buttons differs a little bit from the others I’ve posted so far. Currently, LinkedIn does not provide a callback function that executes when an action is completed — there’s no flag in the code that says “visitor shared something, now what?”. Instead, we have to build our own JavaScript function that we can bind to an action. In order to do so, this example uses jQuery, a popular JavaScript library.
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