Recently, I sat down with one of our newer clients, the customer intelligence director for a global hospitality brand, to find out more about the data challenges faced by his organization. In Part 1, we discussed the chief data challenges faced by his organization, and in Part 2 we discussed the value of data quality more generally.Q: I’d like your sense of what’s next for the Future structure of the marketing organization.A: I started saying this about five years ago: “Give it 10 to 20 years, and we won’t be talking about analytics anymore, we’ll just be talking about business.” I think that’s where we’re slowly going, and where we need to go -- a world where intelligence drives business. The purpose of analytics is to know our customers better, so we can serve them better. And really, that should be everyone’s goal. We just use different tools in pursuit of that.
Recently, I sat down with one of our newer clients, the customer intelligence director for a global hospitality brand, to find out more about the data challenges faced by his organization. In Part 1, we discussed the chief data challenges faced by his organization, and the disconnect between knowing that things are “trackable,” and knowing what that actually means.Q: In defense of marketers who are struggling to keep up: the marketing/tech landscape is moving very quickly. A lot of marketers are feeling like they’ve been caught with their pants down, with all they’re expected to suddenly know.A: Things have moved really fast, especially in the tracking space. The funny thing is, we take all this tracking for granted now. But if you actually look around at the number of companies that are effectively using tracking, and how long they’ve been doing it, there aren’t many companies that are truly using tracking codes the way they’re intended to work. They’re not truly using tracking code data, they’re using these long strings instead.
Recently, I sat down with one of our newer clients, the customer intelligence director for a global hospitality brand, to find out more about the data challenges faced by his organization. Our conversation covered a range of topics. It’s a candid picture of the current marketing/analytics landscape, and we present it here in three parts.Q: Thanks for taking the time to talk! Let’s get right into it. What are the major challenges you face, with regard to marketing data analytics?A: The biggest challenge right now is data integration, which has two main aspects. There’s an issue with being able to track data accurately across time -- in other words, setting things up so that newer data can be consistently compared to older data -- and there’s the chief challenge, being able to integrate the data generated by various platforms: DCM, AdWords, Facebook.
In September 2017, Tracking First released its first major product enhancement, a connector that allows clients to port data from any source to any target. I sat down with founder Craig Scribner to learn more.JR: What was the impetus for the recent product development?CS: More and more our clients are having a less hands-on experience with the tracking codes produced inside their analytics systems. Back in the old days you could manage all your tracking codes with spreadsheets, and you could have different breakdowns, from the most granular to the most abstract, that were comprehensible for a human.
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.
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.
Have a look at this image. Sound familiar? Web analytics has held out the elusive promise of being a set-it-and-forget-it kind of thing. “Set up your reports, and the data will fill itself in.” That promise has largely held true -- for every part of web analytics except Marketing. That’s because with marketing, the web page you have today isn’t the one you had yesterday. There’s constant change: new information, new deals, new parameters. What everyone wants is a system that runs itself. Otherwise, as the figure shows, you spend all your time making sure the reporting is right. Spending time on data correction takes time away from the analysis that will really help the company. It’s a necessary evil. Wouldn’t it be great if we could get marketing data to the same set-and-forget kind of place as the rest of our web analytics?