How much of the money your company spends on advertising and marketing goes untracked? Or suboptimally tracked? Do you know? Does anyone in your organization actually know?The digital marketing industry is suddenly awash in new technologies that allow companies to optimize their marketing spend by refining attribution, to the point where each step along the customer journey (in somes cases including analog or offline touches) can be measured and assessed for their impact on revenue.But the best optimization and attribution tools in the world can’t help you derive real insight if the initial tracking data you used is messed up. Likewise, if the tracking data you’re using can’t be looked at holistically -- for example, if you can’t directly compare performance from one platform to another because your Facebook campaigns don’t use the same tracking conventions as your DCM campaigns...your ability to derive real insights for your organization is limited, at best.
Every once in awhile, we get a question about how Tracking First is different from Adobe’s inbuilt Classification Rule Builder (CRB). It’s a good question, and a pretty easy one to answer. The simplest and most important thing to say is this: use of Tracking First and Adobe CRB is not an either/or kind of a thing. In fact, a best practice would be to use both. The main dIfference is whether your tracking codes will be prepared and described before the campaign goes live (using Tracking First), or only after the campaign goes live (using just Classification Rule Builder).If you’re going to use Adobe CRB, it’s important to keep in mind that you need to take care that your ‘regular expression’ (aka your RegEx) does not overmatch. In other words, you must not use too broad a brush in your matching logic. If you do, you run the risk of inadvertently destroying or overwriting your previous rules -- creating values for classifications that never should have been created. In designing your rules, you have to think not only of what data matches your logic, but of what might accidentally match, and of what doesn't match. You can ruin good data accidentally by using a logic expression that isn’t constrained enough.
Tracking First interviewed Dominic Tassone of the Indegene Encima Group for this two-part series focused on the unique campaign tracking challenges faced by marketers in the pharmaceutical industry. Part one covered the challenge, and part two explores how pharma marketers are tackling it.Tracking First: Thanks for your helpful explanation of the unique tracking challenges facing pharma marketers. Can we talk a bit about the regulatory environment that impacts drug advertising, and how they work with it?DT: Pharma and medical device companies need to be very careful, particularly about how they market to consumers and to a lesser extent to physicians. All drug marketing has to pass medical, legal and FDA reviews. The regulatory hurdle creates another trickle-down of complexity, like requiring different collateral for consumers and practitioners. The drug companies have to be transparent and consistent with messaging to practitioners, while simultaneously working to create demand or stimulate interest on the consumer side.
Tracking First interviewed Dominic Tassone of the Indegene Encima Group for this two-part series focused on the unique campaign tracking challenges faced by marketers in the pharmaceutical industry. Part one covers the challenge, and part two will explore potential solutions. Tracking First: What makes the challenge of marketing analytics in the pharmaceutical industry unique?DT: Within pharma, you find all the usual challenges of tracking digital marketing that any team faces, compounded by an unusual level of added regulatory complexity. The core problem facing any team is keeping all of the tracking codes and parameters used for click tracking organized. This gets very complicated when you have lots of different marketing channels. And it gets more complicated when you start talking about multiple agencies and multiple channel owners, or different agencies for different channels, or potentially multiple agencies within one channel.
This past weekend, my 15-year-old was mowing the grass in our yard -- a Memorial Day tradition for generations of American teenagers. About half way through the job, the lawn mower died. It turns out he had used the wrong fuel for the engine. Though it was taken from a can that was sitting in the garage next to the mower, it was fuel that was intended for use in a chainsaw. Not only did using the wrong fuel cut short that day’s mowing -- it appears to have burned the motor out, permanently.The experience reminded me of the much-discussed challenge in marketing analytics of “garbage in, garbage out.” We are at a stage in the marketing automation revolution where we have a multitude of sophisticated tools. They can handle audience segmenting, attribution tracking, re-targeting and micro-targeting, allowing us to use consumers’ past behavior and preferences to predict their behavior to the finest level of detail and market to them just when they are at the point of considering a purchase.
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.
It was a staple of the cartoons from my childhood: Seated on a river bank, an eager fishing enthusiast casts a line into the water and begins reeling in the line, imagining trout for dinner. Cue the laugh track -- what breaks the surface of the water is a sodden old boot.And so it is with marketing teams, enjoying the newfound freedom being pitched to them by various ad platforms. These platforms emphasize their ease of use in launching new campaigns. “You don’t have to wait for internally-generated Tracking Codes to deploy your marketing,” they say. “You can get the data you need with no hassle.” And marketers respond to it, because it’s mostly true. The vast majority of campaign tracking codes are no longer generated by human analysts, but by the Facebooks and Doubleclicks of the world. Within their ecosystems, these platforms accurately track and monitor, dutifully feeding data into the tag manager.But this presents a challenge to marketing analytics, one that can sneak up even when the tag management system is humming perfectly. When it comes time to analyze performance holistically, it works against your integrated marketing picture to have outside ad platforms creating cloned variations of codes that were carefully designed by the analytics team. Marketing teams don't realize that in reaching for "freedom," they’re also pulling in a lot of noise.