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25 Aug A look under the hood, Pt. 1: Code Composition

Task 1: Generate a Unique Tracking Code for New Campaign Initiatives This part looks easy on the surface, but it carries some hidden complexities. Generating a random string for every new initiative is surely no challenge for a computer, and robust tracking systems such as Adobe Analytics would have no difficulty marshalling all of those random codes on the reporting side. But very rarely will you see companies using that method. Companies generally come up with their own custom recipe for assembling tracking codes, which emerge as a daisy-chained string of descriptors, like these:
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23 Aug Manual data-sitting shortchanges you and your company

Too often, the analytics professionals you hired to provide insights and analysis end up spending their days plugging up holes and cleaning up spills. They came on board ready and willing to realize their potential and contribute to the success of the venture, and instead they’re doing work that manages to swing back and forth between tedious and frantic, and is anything but fulfilling. If they could spare a few minutes to look up from all the codes, they might wonder how they got stuck.
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18 Aug The Future Marketing Organization

Marketing OrgWhat is the optimal structure of the marketing organization of the future? That is the question I discussed today with a senior director for digital analytics at a Fortune 500 company. We agreed that the eventual answer is yet to be defined and could vary somewhat between large and small organizations. Even so, one thing is clear: the landscape is shifting quickly, with digital analyst roles proliferating and becoming increasingly specialized by channel. There is enormous variation in the new marketing structures currently taking shape, particularly in large marketing organizations.
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15 Aug Keeping the Trains running on time: A Case Study in Data Capture

Right at the end of the process of preparing its first campaign codes through Tracking First, Amtrak ran into a serious problem. The email pattern had been identified and selected with no issues, and the new codes and classifications followed suit. But when the landing page was entered for each of these email links, Tracking First’s interface lit up with errors. My phone rang, and the users asked me what they had done wrong.
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08 Aug This is not a job for humans

Manual Data EntryThe very last week that I worked as a web analyst for a Kansas City agency, a toxic email was thrown over the wall from the marketing side to ours. It was quickly passed like a hot potato until it landed in my lap. The ask: could we run a quick check on the campaign links they had prepared for a big release, just days away? The total number of links needing a “quick” check: 8,472.
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04 Aug Analytics and Marketing: Taming the Last Frontier

Not that many years ago, the field of data analytics was like the wild west, with stakeholders making their claims without considering how their interests should be governed within a wider community. But now, maverick analytics implementations are a dying breed. Tag Management Systems are here to provide order, allowing us to lay out standardized tags across our digital properties like so many row houses. From there, we can deploy the beat cops of Tag Auditing Solutions to patrol the streets and catch tracking anomalies early.
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01 Aug Analytics: the View from 30,000 Feet

Looking down from a height at the world of analytics code tracking and campaign reporting, it appears to be a swarm of complex interactions and elaborate interconnections. However, for all its involved architecture there are really only four ways to break campaign reporting. Hence there are just four things a company must check before each campaign launch: code composition, code classification, link assembly, and capture logic. These requirements are not difficult to follow on their own—but any misstep along the line will completely break the tracking.
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18 May Data Protection Plan

Adobe Summit in London, May 2016

Hours ago I wrapped up my latest speaking engagement: a co-presentation with Adobe’s Jan Exner. Jan and I have been working from two different ends of the same problem: the need for better structure beneath analytics implementations. For years he’s been pushing the idea on the development side, while I’ve been preaching it from the marketing/analytics side.
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07 Mar Everybody Hates Sub-Classifications…But Not Us

Since their inception, Sub-Classifications (aka Nested Classifications) have come to represent a hiss and a byword among most Adobe Analytics/Omniture veterans. Flat vs Nested Classifications Examples

Flat Classifications (left) are, as a reliable rule, better than Sub-Classifications (right)

In one of his OmnitureCare mailbag blog posts, Adobe Analytics guru Ben Gaines was asked about weirdness in Classification reports. With scarcely any details, Ben guessed that the Adobe client was using Sub-Classifications, and recommended they turn them off. Within that response, he launched a semi-explanation for/semi-diatribe against Sub-Classifications, ending one paragraph with the outburst: What’s the point?
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