Changing the Business of Relying on Marketing Analytics




  • — May 28, 2017


    Stop me if you’ve heard this one: a digital analyst, with a background in web development and marketing, takes a role heading up web analytics for a Fortune 500 company…and finds himself in the midst of chaos. The business wants to know how their marketing campaigns are performing, and they keep pestering IT for a more nuanced analysis. Meanwhile, tech wants normalized, better-quality data, and labels the lack of these inputs a “marketing problem.” Enter the analyst, trying to steer marketing in the direction of better data capture and IT toward a better understanding of marketing’s challenges — all while advocating within the global organization for a greater focus and investment in the very data capture and analysis that these stakeholders have grown to mistrust.


    If you’re an analyst with enough tenure, it’s likely that you know someone who has walked this knife’s edge. Or maybe you’ve done it yourself. It’s the predicament that one of our customers (we’ll call him Tony) found himself in, after relocating his family from the bay area to the midwest, to take a role heading up web analytics for a major manufacturer.


    The company was launching a new website, and it seemed like the right moment to address the fact that their marketing was relying increasingly on campaigns via social networks, but doing a poor job of tracking their performance on social media beyond clicks and likes. Direct purchasing through social was rare, and there was virtually no mechanism for linking social clicks to subsequent buying behavior on the company’s website.


    With the business pressuring IT, this organization came to us for a streamlined tracking code management solution. After running a trial campaign through the website relaunch, they quickly found that the data picture measuring social media’s impact on overall web traffic became much clearer. Lovely Adobe reports, with correctly classified tracking codes feeding them, began to reverse some of the internal doubt that had existed about whether the company could rely on marketing analytics to guide strategy.


    Fast forward a year into their implementation, and the business decides to end its reliance on Adobe and move completely toward Google Analytics. This confers some advantages, but also presents a new set of challenges, including the loss of access to Adobe’s Classification technology, which allows tracking codes to be grouped into different levels of abstraction.


    Many people in Tony’s company, including those who made the decision to switch to Google, lack an understanding of classifications and the benefits they provide. At the same time, these executives are now accustomed to seeing reports that result from classified data, with comparative analysis on a number of variables that impact a campaign’s performance.


    It creates some frustration for Tony. “What I want from Google Analytics is the level of analysis that we had with Adobe Analytics. Google has just introduced dimension widening, which should help, but the way we mimic Adobe’s classifications is a bit cumbersome. We’re using the 4 or 5 default UTM parameters to try to capture many more than 5 campaign attributes. Ideally, we would use each parameter to represent a single point of data.”


    Asked about the solutions that are helping, Tony says, “It’s a relief to have a resource like Tracking First for code creation. It helps to make code creation simple and consistent, which does save us a lot of time. If we were fully using column widening, we could use it more like SAINT, making each parameter represent a single value.


    “An additional challenge is that not everyone has the expertise to look at a data report and understand the information it presents,” says Tony. Over time, with training and internal advocacy, he expects that the company will come to rely more heavily on their analysts. “Everyone understands that we need accurate metrics, but they don’t understand how to get there. I want to move the needle in terms of the established KPIs, putting a laser focus on the things we care about with regard to social media and the web, and revenue. If we’re all looking at the data together, with a common understanding, we can make a collective decision about how to move the business.”


    He adds, “Half the time I feel like I’m educating the business about how to think about and understand data. People want to understand it, because they can see the value it will add. Making sure there’s clean data, tagging things correctly, that’s all the foundational stuff that gives me the time to do that internal educating. There would be no time to do that if I were just spending my time making sure the data was clean and the process was followed.” We’re glad we can help. Clean data and consistent campaign tracking remain an issue for many marketing organizations. How is your team tackling the challenge?

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    Author: Joseph Riddle


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