This guest post from Jennifer Yacenda of Starwood Hotels examines how both practitioners and managers can use dynamic tag management (DTM) in different ways.

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Managing analytics nowadays continues to be an evolving job, similar to the very first day I started my career in this field as a college intern. At times, it’s overwhelming, but secretly (or not so secretly), I love it. Every day is a new day with new challenges, new tools to learn, new deadlines to meet, and new questions to answer. Our world is becoming increasingly digital, and that introduces a whole new set of challenges. Since the digital world moves so quickly with such a high volume of information, our time feels compressed and much more precious. Taking some time to think about how you invest your time is critical to success, especially in analytics. As a director of analytics, this key to success is relevant for both (1) setting the right implementation strategy and (2) focusing on the right datasets that drive the most impactful insights. We own the full cycle of analytics, and it’s more important than ever before to carve out time for thinking across the spectrum of our work.

The luxury of an overnight test, as described in “A Short Lesson in Perspective,” resonates with me as a digital analyst — it’s clear that analytics and the creative process go hand in hand. This overnight test, as described from an advertising executive’s perspective, starts with (1) a raw brain dump of ideas, scribbles, and inspiration; followed by (2) ideas that stand the test of time by marinating; (3) a morning follow-up session to revisit and filter ideas, eliminate losers, and highlight winners with the end goal of delivering (4) a finalized creative concept for a campaign. With analytics and marketing-technology implementations, the decisions to use a prop or an eVar or to fire it on page load or on the next page become parts of maps that litter my office walls and whiteboards to outline our customers’ journeys in the language of variables. DTM gives us the canvas on which to develop our vision, to revisit the approach when the time is right (after experimentation), and to deliver something that makes sense for our business. DTM allows us to take that necessary step back — like an artist takes a step back from the canvas — to see the bigger picture.

Just Like Art, Implementation and Tracking Requirements Are Subjective.
When thinking through the implementation process of a new tracking project, there are a number of steps in the works before it even comes to our queue. Our business’s digital, brand, and marketing teams leads are in various phases of their own planning processes for new functionalities, new microsites (featuring that new brand program), or new landing-page redesigns. At some point — often without a ton of advanced notice — we’re asked to be the judge and juror on success. A stakeholder may come to us with the simple request, “I need tracking” but not provide any guidance. We’ll often receive a set of wireframes or a development site where we’re expected to poke around and develop a tracking strategy. As artists and implementation experts, we’re asked to think through it all on our own. Tracking can be an elusive concept, and DTM has become a tool that truly helps us start the creative process where we draw up projects and develop the right information-picture over time. It provides flexibility that we have never had before.

Implementation and tracking strategists quietly weave the intricate patterns of measurement throughout our digital ecosystem, collecting key pieces of data to derive answers about our consumers. It takes a combination of thinking, philosophy, business acumen, and curiosity to understand 1. What the business is building (what’s success mean to them), 2. What the customer will experience (what actions will they take), and 3. What questions will analysts need to answer (what’s the data structure look like). We also need to know — or at least think through — whether our strategy is within budget depending on server call implications.

Artists Need Time to Do Their Best Work
Like advertising execs — whose timeframes for developing creative concepts have shrunk in the digital world — most analytics teams have rapidly growing numbers of requests that flow through the organization since “digital” also means “more measurable.” With advances in technology, time is that much more of a luxury. Allotting time to think is a challenge as more channels develop, consumers create more data, and more executives understand the value of data. Simultaneously, small analytics teams — those at the most basic levels — are staying the same size but also being asked to (1) make sure that data is collected in a meaningful way and (2) interpret the results, drawing out valuable insights for their organizations. How is an artist to work under these conditions?

Despite being forced into this world of doing things faster, as measurers leveraging DTM, it’s clear we found a way to slow down time and employ the overnight-test approach to our tracking strategy. At the same time, DTM gives us more flexibility and agility than ever before. I remember the days of being beholden to the hard dates of the information technology (IT) release schedule. There was a certain fear that we couldn’t get anything wrong, that we had to be spot on. I remember implementing Adobe Recommendations, missing a case-sensitive “I,” and missing out on 6 months of using a product. Those days are gone. DTM has allowed us to apply fixes without the wait.

Enter the heroics of DTM to save the day and help us add and change things so quickly. We’ve been able to save the day on more than one occasion with quick DTM updates. We’ve been able to add tracking to robust internal applications with little development work or ramp-up time from our different development teams. DTM has allowed us to make friends and build bridges in unexpected places within the organization. How do you put a value on that?

The implementation of marketing technologies is a balancing act, one that will become more difficult as we go.

DTM, as a Tool, Is Powerful — Adopting Tag Management as a Culture Is Difficult!
As an analyst, as a leader, and as a human being, I have the instinct and desire to say “Yes!” to all of the requests from business owners who are looking for ways to measure their products as well as their decisions. They’re looking for data to help make more informed decisions. With everything becoming more digital, answers are now more knowable (assuming the right talent is in place). Growing parts of all organizations are turning to analytics for the first time — looking to learn something from data, to make better decisions. As a realist, I know we do not have enough resources in place.

“DTM has allowed us to make friends and build bridges in unexpected places within the organization. How do you put a value on that?”

That being said, while DTM enables us to say YES to tracking more projects with its relative ease and simplicity, it also reminds us that we must LEARN to say NO at times. We simply don’t have enough analysts or server call budget to keep up with the requested amount of data we could capture. DTM allows us to work so quickly and to do so much in new places and new channels. But, the increasing requests make it more and more difficult to take a step back and truly gain a sense of the full picture. With a limited staff, how do we document everything? How do we understand or communicate our entire implementation? How do we keep track of all the variable maps? What is our backup plan?

We gain efficiency by tracking more across more channels and driving more value. Unfortunately, our increase in efficiency and effectiveness hasn’t translated to an increase in budget to hire more folks to manage and govern this valuable asset. And, we haven’t seen budget increases in respective IT teams or quality assurance (QA) to make sure analytics is included in all parts of the release cycles. We’re now working with more teams than ever before — mobile app teams, marketing teams, and internal application teams. We have more frequent release cycles to monitor in case something breaks or something new hasn’t been tracked. We have more last-minute requests. But, because we’re moving so quickly across so many teams, things can be lost in the shuffle without the proper resources and oversight to ensure documentation is in all the right places while still moving at scale speed.

Wrapping Up
There have always been challenges facing analytics teams. DTM has fundamentally changed the way analytics teams function — more flexible, faster, more platforms, and less reliance on IT as well as allowing us to do more, think on our feet, and paint better pictures about our customers. However, it does not solve all of our problems. It gives us time and flexibility to think through things in this crazy-paced world we are now living in. But, the culture still exists in which analytics teams are small and strapped for resources. We answer more and more requests while tracking more things, which makes it challenging to ensure our time and energy is focused on the right priorities. DTM is an important step in the right direction, but it’s just a single step in the overall process.

As we elevate our implementation techniques, we must be sure we are elevating all parts of our analytics practices and business cultures — we need to develop tools and define processes that also elevate our governance, documentation, and communication to the same level.

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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/dynamic-tag-management-helps-analytics-teams-beat-clock/

The Blog Post below is from Trevor Paulsen, Product Manager, Analytics Data Management at Adobe.

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The Power of Segmenting and Why Specificity Matters: Introducing Segment Comparison

Segmenting is a core strategy that is crucial to any marketer’s success. As not all customers have the same characteristics or behave in the same manner, it’s increasingly important to employ different marketing tactics for each distinct group. While traditionally segmenting has been thought about quite simply in regards to age, gender and even geography – as our threshold for data-driven marketing continues to increase, the definition of segmenting has shifted as well.

Let’s use Pixar movies as an example: while one might think that their cartoons are just geared to children, in reality their movies appeal to a variety of different groups including kids, parents, couples, teenagers. The messaging and movie promotion go far beyond just simply getting a five-year old to laugh. Pixar is smart in their approach: aside from traditional advertisements on children’s programming, the movie is also positioned on shows geared towards adults such as Ellen (as they did with Finding Dory), and promoted on social channels with specific storylines that are geared toward a group.

With the massive amount of customer and behavior data at our disposal, it’s even more important to identify the key characteristics of audience segments that are most significant to a brand – to better understand the behavior that drives more positive interaction, sharing and conversions among different groups of customers.

At Adobe Summit, we introduced Segment IQ to the world – and we’re now excited to announce the first live feature within that category: Segment Comparison for Analysis Workspace. First in a series of audience analysis and discovery tools within Segment IQ, Segment Comparison intelligently discovers the differences between your sets of target audience segments through automated analysis of all your metrics and dimensions.

In speaking with customers, we saw analysts spending an incredible amount of time comparing various segments with each other in order to understand the actionable differences between them. Segments often overlap with each other or have non-obvious differences lurking deep within the data, and uncovering these insights is like picking a needle out of a haystack – sifting through these cascades of data manually to find the most significant differences is often impossible.

With Segment Comparison, marketers and analysts can gain new visibility into which segments are most important to their businesses and why, so they can acquire and convert customers much more efficiently—saving time and budget.

The best part is that all of this is done with a few clicks of a mouse. Check out this short demo to see it in action.

Segment Comparison allows brands to complete a comprehensive segment analysis within just minutes, and compare every single dimension, metric or data point between any two segments automatically discovering the most significant differences between each. In initial testing with customers, Segment IQ is one of the most popular features we’ve released, and we’re thrilled to see how it expands from here in helping to create highly targeted marketing strategies that resonate with segments based on customers’ unique behavior.

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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/power-segmenting-specificity-matters-introducing-segment-comparison/