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/

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/

Below blog post is from Ben Gaines, Senior Product Manger for Adobe Analytics

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Visual Customer Insights with Adobe Analytics Activity Map

Growing up, I often enjoyed playing flight simulators on my family’s computer. My personal favorite was one that put the player in the cockpit of a powerful fighter jet called the F/A-18 Hornet. The Hornet was sleek and fast, and I loved to kick on the afterburners until my airplane disintegrated under the stress. But, my favorite part of the game was the simulated Head-Up Display (HUD). The HUD allowed you to find information about altitude, pitch, other airplanes, points of interest, and more — right on the windshield of the digital airplane. It was so much easier to process all of this information and have a productive flight with the HUD enabled.

Data Access and Interpretation on an Adult Level
That same, almost-effortless data interpretation — gained from not having to look away from what I’m doing to access it — that I enjoyed as a child applies to customer intelligence on the web as well. In April, Adobe Analyticsgained a brand-new approach to in-context analytics that allows marketers, designers, content owners, and others to view user-click and interaction data directly on the pages of their websites: introducing Activity Map. Activity Map is a browser plug-in/add-on/extension with support for all major desktop browsers. It runs right over the top of your website and makes your data come alive in vibrant color with visual overlays that draw the eye to areas of interest for your customers. For anyone interested in how users are interacting with content, links, A/B tests, and more, Activity Map provides you with insight right on the page and makes it much easier to come to an informed decision about how to optimize. It’s like having a grownup version of the HUD for your Adobe Analytics data.

Using a very simple example, let’s say that I use Activity Map on the Adobe.com homepage. (NOTE: the screenshot above is using fake data.) By putting this data right on the page, I can see exactly where people are clicking — as well as where they are not clicking. I might discover that links to the Community Forum are really popular, while links to another area of the site are not. Having this information enables me to give better placements to the links that people are actually clicking, moving them to the main body of the page. Better yet, I may decide to run a test to see whether that placement yields better results than the incumbent experience. An insight that pops off the page in Activity Map becomes an A/B test, which becomes a better experience for my customer.

Four More Reasons to Love Activity Map
Here are just a few of the reasons we’re so excited about the new Activity Map tool:

Different Customer Segments Respond to Different Content and Links.
Activity Map allows you to apply any segments from Adobe Analytics to your data in context. Maybe your loyal customers gravitate toward one type of content, while prospects prefer something completely different. Segmentation in Activity Map makes this distinction clear and helps you to provide the right experience to the right segment at the right time.

Better Metrics in Activity Map Produce Better Insights.
Of course, Activity Map still offers clicks as a metric, but you can do so much more by using any Adobe Analytics metric to understand the downstream impact of a particular user interaction on conversion. You could have links on your homepage that are clicked a lot but don’t actually produce any leads, revenue, subscriptions, or reader loyalty.

Live Mode Presents Users With Real-Time User Interactions.
Many of you told us that you wanted to be able to see user interactions in real time, so we added a “Live Mode” to Activity Map, which streams data collected from your site straight into Activity Map. If you’re a content publisher, you can not only see, but also immediately understand the most popular articles, videos, and photos over the past 15, 30, 60, or 120 minutes — with granularity as high as minute-by-minute — and then adjust headline stacks accordingly.

Integrated Pathing Helps Users Visualize Broader Customer Journeys.
We’ve integrated pathing data directly into Activity Map so that you can see not only what engaged people when they were on a given page, but also how they arrived at that page, and where they went immediately afterward. This adds to the on-page insights by painting a picture of the broader customer journey.

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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/visual-customer-insights-adobe-analytics-activity-map/

The Blog post below is from Jeff Allen, Sr. Director of Product Marketing for Adobe Analytics

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The Message is Maturity: Adobe Is a Leader in Gartner’s Magic Quadrant for Digital Marketing Analytics

“Gartner analysts call digital marketing analytics the core of successful digital experience.” And having the right tool for the job — a differentiator that helps support customer journeys across multiple channels and devices — is everything. Leaders today are imploring their analytics teams to provide more robust, cross-channel insights to allow for better understandings of strategic objectives. And they’re looking for technology that can keep pace.

In the second-ever Magic Quadrant for Marketing Analytics, Gartner placed Adobe as the overall leader in the combined categories of ability to execute and completeness of vision. With comprehensive integration, advanced segmentation capabilities, and market-leading innovation, Adobe Analytics helps make complex data simple for delivering powerful marketing insight — and then, quickly turning that insight into action. More than being informed, Adobe Analytics provides seamless integration for immediate action across verticals, and the vision is now extending to customer intelligence. Here’s a look at the strength of Adobe Analytics — a best-in-class, cost-effective, practical solution for the retail, financial services, B2B, and travel and hospitality industries.

Retail: Providing Flexibility and Functionality for Critical Reporting and Insight Discovery
For online retailers, tying metrics to products is critical — so, shouldn’t reporting be as flexible as possible? Having the ability to view any report by product (and vice versa) is smart; but placing limits on this ability decreases analytics opportunities. Adobe Analytics makes it easy for online retailers to discover revenue-generating insights while helping customers find the products they need. Through robust product-category merchandising and product-finding methods, accurate pathing analysis, and advanced cross-sell reporting, retailers can better understand their customers and put the right products in the right places at the right times.

Financial Services: Measuring and Influencing Customer Journeys for a Competitive Edge
Advancing digital maturity across financial-services institutions means being able to not only see the full lifecycle of the account application process, but also understand which marketing campaigns led to approved applications so that promotional spend is targeted and optimized to customers with higher lifetime-value propensities. Adobe Analytics is the only tool that allows financial-services organizations to see the customer lifecycle and associated product affinities by customer groups, which helps optimize revenue via its industry-leading feature set and connects online behaviors to post-website revenues and profits. Additionally, Adobe Analytics enables users to study cohorts’ share-of-wallet trends from different time periods to indicate whether website and app promotions are growing or declining with regard to relevancy, so that you can work toward increasing product adoption.

Business to Business (B2B): Connecting Highly Complex Customer Journeys
B2B and tech companies achieve digital success by associating all metrics with customer engagement over time. The customer journey typically involves an entire buying team and is highly complex — never linear and rarely contained to just one channel — and analytical insights must be based on this reality. Adobe Analytics is the leading analytics vendor for discovering high-value audiences and creating segments to fuel customer-touching engagement activities. Adobe Analytics customers can easily break down reports by any number of variables, build and customize on the fly to streamline lead-generation activities, or discover hidden opportunities with anomaly detection and contribution analysis. Since most of the success for B2B companies takes place offline, Adobe Analytics can connect online leads to downstream sales and revenue, helping to optimize campaigns and prioritize customer outreach by sales team.

Travel and Hospitality: Maximizing Customer Experience Every Step of the Way
With an intense customer-experience focus, the travel and hospitality industry faces unique challenges. Maximizing capacity and upsells to reservations requires a clear understanding of key variables such as product-search merchandising, reservation reporting, advanced booking, cross-selling, cost and margin analysis, post-purchase analysis, and booking loyalty. It is critical that reservation reporting be as flexible as possible. The ability to create an unlimited number of persona-based segments, model them, and compare them via machine-learning innovations (such as Segment IQ) is unique to Adobe Analytics. Additionally, Adobe Analytics enables travel and hospitality companies to associate all their custom metrics with the reservation process and provides the ability to break down any report by reservation/product and vice versa. With Adobe Analytics, you can build or customize any report you want on the fly.

Future Plans: What Adobe Is Doing for Customer Intelligence
Adobe was one of the pioneers of web analytics and evolved the market from web to digital analytics to marketing analytics and is now focused on customer intelligence. The recently released Gartner Magic Quadrant for Digital Marketing Analytics 2016 confirms this legacy, positioning Adobe as a leader — in both execution and vision — with a comprehensive set of marketing tools for users of all skill levels. Paired with cross-channel enablement and advancements in our user interface, our dream of democratizing the power of data is coming true for our clients across many verticals.

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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/the-message-is-maturity-adobe-is-a-leader-in-gartners-magic-quadrant-for-digital-marketing-analytics/

Below blog post is by Nate Smith, Product Marketing manager for Adobe Analytics

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What Mobile Consumers Want NOW — And How to Deliver!

I’ve been pondering the meaning of mobile lately — or, more specifically, what comprises a “mobile experience.” Does it revolve around the device? Is it the user’s location or context? Or, might it even be the service the user is trying to access? Recently, I counted 14 screened devices in my home. In addition, I counted two smart devices in my home that are controlled by voice rather than screens — definitely not the case a few years ago! And, I’m sure that’s just the tip of the iceberg in comparison to where we’ll be 5 or 10 years from now.

Interestingly, as the definition of mobile and the landscape it encompasses has evolved and expanded, consumers have ceased to view certain experiences, extensions, and capabilities as luxuries or nice-to-haves. Now, some of the most sophisticated, relevant, and high-tech mobile experiences are simply expected.

What Can Brands Do?
So, what can brands do to meet consumer expectations in a constantly changing mobile landscape? I think it comes down to managing three key expectations from your customers.

1. Brands Must Do More Than Know Me — They Must Value Me.
Today, consumers expect brands to know them and value them tremendously — so much so, in fact, that those brands be able to deliver meaningful, personalized experiences, touchpoints, and content immediately. It’s not a customer/brand touchpoint anymore. Today, it’s a spectrum of relationships. And, as brands, stakeholders, and marketers, we need to be all-in when it comes to cultivating and deepening those relationships, which means analyzing data through a customer paradigm and associating engagement at this level.

Nowadays, brand building is essentially a never-ending loop. The deeper we dive, the deeper customers’ relationships become and their expectations skyrocket — and the cycle continues.

2. Content Must Be Relevant!
Those personalized offers had better be relevant — and, I’m not just talking about the content being consumed! I’m also referring to how it is consumed. Consider this: Gartner conducted a study on how individuals consume content by device. Following are the results based on the average number of sessions daily and their typical lengths:

• Desktop Users — 4 sessions daily at 36 minutes each;
• Tablet Users — 12 sessions at 7 minutes each; and
• Smartphone Users — 19 sessions at only 1.2 minutes each.

When planning for the smartphone experience, eliminating friction to achieve target goals is critically important. A key component of mobile success is how you construct experiences for short bursts versus long sessions.

Here’s another example that highlights the need for integrating cross-channel data. I love golf — I’m not good at it, but that doesn’t deter me. When it was time to pick up some new equipment (because talent sure wasn’t elevating my game), I headed to a local sporting goods store and had a fantastic experience. The pro came right over and helped me select the right items to improve my game while keeping me comfortable and within my budget. Awesome. As a thank you, he even tossed in a great bag and a few packs of golf balls — also awesome.

When I was ready to check out, he asked whether I wanted to sign up for their email newsletters, promising I’d receive updates on sales and promotions. Of course, I did — I was thrilled he even asked. A week later, I received my first email — offering 25 percent off the driver I had just purchased. Because they didn’t have an integrated profile for me, my view of the relationship with this brand turned a little sour.

3. Do It All in Real Time!
A key component of success will be run-time actionability. That’s lovely marketing speak that means machine-learning algorithms will kick off engagement experiences by utilizing real-time data.

There’s a real contextualization to mobile, and location plays a key part. Your consumer could be using his phone while waiting for a flight, walking past a coffee shop, or watching a video — but, because of the nature of mobile, it’s a moment. And, once that moment passes, it may never come again. Utilizing machine-learning and automated actions by customer-engaging technologies will be musts for organizations that want to stay ahead.

Maximize Your Mobile Analytics.
Done right, analytics unlocks mobile value for your brand, allowing you to assess how users interact and engage with your apps as well as how those apps perform. You’ll be able to discover what mobile users find valuable and what misses the mark — both in a macro-audience view and on an individual (or segment) level. And, you can create hypotheses, launch tests, and develop ongoing iterative processes for optimizing your brand’s mobile experiences so consumers obtain the level of real-time relevance and personalization they crave. That also means greater engagement, added conversions, higher retention and advocacy, and more access to the data you need to continue repeating, expanding, and delivering even better, more meaningful relationship-driven experiences.

What’s Next?
Mobile is no longer a channel or platform, but instead, the nexus of a customer’s journey. But — and this is really part two of the conversation — mobile isn’t the entire journey. There are still websites, ad networks, and stores — all of which feed into the total picture. It’s what we’re talking about when we discuss cross-device behaviors — and, it’s the next frontier for all of us.

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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/mobile-consumers-want-now-deliver/

Below blog post is by Jennifer Cooper, Adobe's director of industry strategy in media and entertainment

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Answering the Call for an Audience-Acquisition Framework

Consider the age-old thought experiment, “If a tree falls in the forest, and no one is there to hear it, does it make a sound?” The same can be asked of even the best content in the world. “Content is king” only rings true if there is an audience there to “see and hear” it. While even modestly successful media companies will have some manner of audience to work with, today’s fierce competition for audiences, as well as their subscriptions and ad views, forces every media and entertainment (M&E) marketer to feed a constant cycle of acquiring, engaging, monetizing, and measuring audiences because these actions impact nearly every business’s key performance indicators (KPIs) for success.

A marketer’s ability to affect metrics — such as subscriber count, engagement frequency, time spent, or ad revenue — can make the difference in whether he or she gets that next promotion or bonus. Yet, moving these metrics in a significant way requires not only a formal approach to data-driven acquisition and retention, but also a technical capacity to execute.

Adobe’s latest whitepaper, Audience Acquisition Evolved: Acquiring and Engaging Audience Across Channels, shows you four things you can start on right now to prepare your team to execute a successful acquisition and retention program. In addition, it outlines a framework to encourage continual growth.

Following is a snapshot of the framework.

Onboard and Analyze
Data traits and behaviors are collected via analytics as new people engage with your ads, sites, and apps. In addition, analytics and personalization technology tell you what activities contribute the most to your KPIs.

Segment
Data from analytics, customer-relationship management (CRM), first-party data, and other data sources (including offline sources) is aggregated by a data-management platform (DMP) to form audience segments that can be used for targeting and personalization. These audience segments can be expanded using lookalike modeling, which identifies prospects with similar behaviors and traits that you can’t identify from existing first-party traits.

Reach and Engage
Once the segments are defined, leverage them in campaign-management tools that deliver optimal ad experiences to your most profitable advertising channels. Use technologies — including retargeting, dynamic creative, audience extensions, and programmatic buying — to take action with your audience data.

Personalize
Use audience data to personalize all the digital experiences that you manage across devices. Technologies — including A/B testing, multivariate testing, and video recommendations — can help you deliver the perfect experience for each person. These personalized experiences will increase people’s satisfaction levels and time spent as well as drive repeat usage.

In Sum
Audience Acquisition Evolved explores what the latest research tells us about how acquisition and engagement are changing in the M&E industry, what the obstacles are, and how technology can help you address those obstacles. You will also receive actionable tips to accelerate your data-driven marketing.

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Read the original blog post at -  https://blogs.adobe.com/digitalmarketing/analytics/answering-call-audience-acquisition-framework/