Our January WAW was a group discussion. Attendees filled in the blank in the statement:

By the end of 2016, when it comes to digital analytics, I’d like to be able to say ______________.

We spent 45 minutes discussing the thoughts shared by various attendees, which are summarized below.

Build R Knowledge and Apply It

The attendee felt like he had nearly universally heard, “It’s a steep learning curve…but totally worth it once it all clicks,” so he’s going to try to make it over that learning curve and see if he can get the tool clicking for him (and, he hopes, in a way that he can use some of the same scripts across multiple clients. This led to an “R vs. Python” discussion, as well as a minor diversion into “Tableau vs. Domo.”

“Solve” Referral Spam

Everyone working with Google Analytics is fighting referral spam, or, really, data quality issues writ large. This led to some very-near-to-cbusdaw references:

• Dr. Augustine Fou’s presentation from our November 2015 WAW
• The referral spam filter wizard that our very own Jason Packer developed
• Did someone mention Jason Packer? Well, yeah, he also recently did a pretty fascinating of measuring the impact of ad blockers on Google Analytics…and pushing that data to Google Analytics.

Despite the temptation to do so (because it was discussed), none of the links above have monkied-with campaign tracking parameters included.

Convert All Clients to Use a TMS

Rather than 2016 being the fifth consecutive “Year of Mobile,” how about making it “The Year of the TMS?” This was the third thought that was in the technical weeds, but we chatted about the value that a tag management system can deliver (and the lingering ill effects of TMS vendors initially leading with “no need to work with IT!”). We also discussed that a TMS is still just a tool. It can be a mechanism to think about and develop better data governance, but it doesn’t automatically handle data governance without some process development and on-going rigor!

Get Stakeholders to Use the Data They Get

The Analyst’s Dilemma: I built it…but they didn’t come. The two points attendees made here were:

• Lead with “insights” rather than “the data” (full disclosure: the scribe/author of this post has a gag reflex he has to fight when platitudes use the “i” word…)
• Include stakeholders in the measurement planning process (throwback WAW! February 2011 presentation was on campaign measurement planning)

“Figure Out” Facebook/Social Media Analytics

Oy. We were getting pretty ambitious by this point.

Figure Out the “Magic Number” for Each Stakeholder

What’s a magic number? In baseball, it’s the combined number of games a team needs to win or another team needs to lose in order for a team to win their division.

That is not what this attendee was referring to. Rather, it was a very neat little way of saying, “KPI:” figuring out what one metric is most critical for any given stakeholder, and then making sure it’s being measured and reported accurately.

Get a Better Understanding of Data Collection

Things used to be “simple” — a log file. Then page tagging (client side JavaScript) data collection came along. And then social media. And mobile. And now a drift back to server-side data collection. It behooves the analyst to have a good handle of where the bits and bytes are flowing and how they’re being grabbed and recorded.

It was a lively discussion overall!