Share your Analytics Blogs and Articles


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Hey Community Folks!

This space is created exclusively for users who write blogs or articles around Adobe Analytics and related technologies. You can feel free to post your genuine content around the product or related topics like Web Analytics, Mobile Analytics, Reporting, Data Analysis etc. If we like what you have written, we may well include it in our official Knowledge Base Articles and give you the due credit! If you have any questions before posting you can send me a private massage. 

Hope to see some great content here!




Community Manager


The Blog Post below is from Tim Waddell, Director, Product Marketing for Media & Advertising Solutions at Adobe.


Mobile-App Analytics Are the Key to Successful App Optimization

Some estimates say that as many as 60 percent — over 400,000 — of the apps in Apple’s App Store have never been downloaded even once! And, in a study conducted on data from over 125-million mobile phones downloading apps from the Play Store, the average app loses 77 percent of its users within three days after it’s installed. On top of that, 90 percent of the users stop using the app after a month, and only five users keep using any given app.

There is a clear need for app developers and marketers to come up with better apps and better ways to monitor their uses. They need to optimize their performances and capabilities.

While mobile app analytics can tell you a lot about what is happening with your app after the download, Forrester reported that only 46 percent of companies are using a mobile app analytics solution. This means that the rest (more than half!) can’t see what their customers are doing, primarily because they aren’t even bothering to watch. These companies are missing out on valuable conversations, relationships, and income, all because they lack data desperately needed to guide their business decisions — data that is readily available.

Following is some of the mobile app analytics data available today that can give you amazing insight into how your app is being used.

App-Acquisition Metrics
The mobile app marketer embeds campaign-specific tracking links in paid, owned, and earned media that can then be tied to the app once a user has downloaded and installed it. With that, they can determine which marketing activities lead to an app download and launch event. This gives the marketer the insight necessary to make informed decisions about how to adjust future acquisition and reengagement campaigns to drive download and launch rates.

App-Lifecycle Metrics
Insights into app behavior and customer preferences are critical if you are to understand whether your app is effective. Metrics such as app launches, crashes, days since last use, and average session length are just a few of the lifecycle metrics available. This data allows you to see patterns that could reveal why someone decreased his or her use of the app. With this information, you can encourage interactions, create loyalty, and drive conversions.

App-Store Data
Just knowing how many times your app was downloaded doesn’t help much. You can also discover the region, platform, category ranks, in-app purchases, royalties, rankings, and much more.

Cohort Analysis
The next step in app analysis, cohort analysis, looks at certain groups of users and follows their behaviors over time. You can infer the expected lifespan of the app, how upgrades affect engagement, and how early- versus late-adopter behaviors differ.

Location Services
One of the most powerful pieces of information that you have access to is your customer’s location, providing an unprecedented opportunity for personalization. You can help someone find a resource he needs or do location-based targeting using GPS and beacons. Sports stadiums and retail stores are exploring the power of beacons to deliver location-specific services to users.

Developing a great app is challenging, and you need data about how people are using it to assess its success and make it better. The key is measuring engagement, and mobile app analytics allow you to understand what factors attract your audiences to your content and provide you with opportunities to discover ways to deepen involvement.

It may sound cliché, but with the right mobile app analytics data, you can turn insight into action and understand what steps you need to take to create a great app.


Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/mobile-app-analytics-key-successful-app-optimizat...



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


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.


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



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The Blog Post below is from Nate Smith, Senior Product Marketing Manager for Adobe Analytics


Leave the Cookies in the Jar: Turn Insight Into Action With Adobe Analytics

With the Adobe Analytics Spring 2016 Release, Adobe is delivering more intelligent, automated tools that aid in the discovery and sharing of meaningful audience insights across your organization. The latest advances in Adobe Analytics feature several industry firsts, including a new people metric to understand how many actual people viewed content, purchased a product, came in via various marketing channels, or otherwise interacted with your brand.

We are all in a new online world that no one could have predicted just a few years ago. Organizations that don’t use analytics are quickly realizing that they run the risk of being left behind.

Users of the Internet come from all over the globe and have diverse interests, but nearly all of them have one thing in common: they desire seamless, amazing, relevant, personalized, and real-time experiences that connect them with your brand. If they don’t get that in the first few seconds of their visit, they are more than happy to visit your competitor.

Adobe is uniquely positioned to serve its clients’ data-analytics needs because it has a single, unified platform based on world-class security standards, and no capabilities are outsourced. The customer experience is consistent across all channels, and all digital assets are coordinated with ongoing marketing campaigns.

We All Need to Become Data Scientists

The key is, though, that our new Analytics release embraces and enables the new reality that is quickly taking shape — that we all need to become data scientists.

A powerful example of using analytics and embracing the customer journey to get the whole customer view is UniCredit Group, which is based in Italy. With more than 8,400 branches in 17 countries and 146,000+ people employed, it had a minimal online presence just a few years ago when it turned to Adobe Marketing Cloud and Analytics for the insights needed to understand its customers. After mapping the whole customer journey and making changes to the way they addressed customer needs, online users rose from 300,000 to over 3 million — with over 50,000 visitors per hour! UniCredit Group knew it needed to optimize the user experience and become a company of data scientists to understand its users.

Keep the Cookies in the Jar Where They Belong

The Web-based, user-friendly dashboards of today’s Adobe Analytics make that possible. Cookies just don’t cut it anymore. In the mid-1990s, a cookie was a reasonable approximation of a person, since most people had just one device. But today, the average person may have a desktop, laptop, work computer, tablet, smartphone, and maybe even a smart watch. Without using analytics, you have no link between the devices. The cookie crumbs you get with one cookie per browser will not get you the information you need to construct a 360º view of your customer’s journey at every touchpoint with your brand and on every channel. You have to dig deeply into the available data.

Another successful example of leaving the cookie in the jar is the leading online-investment firm, Scottrade, that uses Adobe Analytics to measure the impact of its ad spend across various channels, publishers, and social media sites. For example, through Facebook and Twitter initiatives, Scottrade has the opportunity to engage in ongoing dialogue with existing customers and with people who might not otherwise consider using an online brokerage firm. Interactive advertising analyst for Scottrade, Bill Dehlendorf, explained, “Adobe Analytics helps us measure the success of all our campaigns—Facebook, Twitter, and others. Through a single platform, we can monitor the performance levels of each channel and then adjust accordingly.”

Turning Insights Into Action

As a result, Scottrade has boosted the return on its digital strategies. Equally important, Adobe Analytics helped it boost productivity, freeing up 15 percent more time through automation and integration. “We spend a lot less time simply capturing and managing data and more time executing on campaigns that impact our bottom line,” Dehlendorf said.

Businesses that have moved toward a more automated data-analysis solution are seeing big returns on their investments. For example, let’s say you do an A/B test on a campaign, and the data shows that B is best and that it increased revenue by 20 percent. Why wait a week for the staff meeting to present the test and get approval? If you let the software — with the proper oversight — simply put version B into use, think of all that additional revenue you could make. Your marketers can always adjust the campaign based on real results. The new 2016 release of Adobe Analytics effectively puts a play button on your data.

Connect the Right Workflows to the Right Work

With the availability of highly detailed, easy-to-use data tools in the new release of Analytics — such as conversion and success metrics, real-time trend changes, the ability to see customer journeys before and after they visit your page, and instant segment comparisons — you can adjust workflows within your organization to bring the right people to the right tasks.

For example, your marketers — who know the details of your campaigns and are the best people to judge what data they need — push the buttons to collect and manage data and immediately implement the insights they gain. Revenue flows instantly.

Adobe Analytics, especially the new tools released this spring, gives you the power to make everyone in your organization responsible for the customer journey and allow an unprecedented opportunity to reorganize your talent into the roles best suited to maximize your ROI.

To provide the experiences that today’s customers expect, organizations are faced with having to gather lots of data from different sources in an attempt to get to know their audiences at every touchpoint and on every channel. Understanding the data needed to create that experience is very complicated, but because of Adobe Analytics, your entire organization can have access to the whole customer view. In an era of high-velocity change, using Analytics may be the only way to truly future-proof your organization.


Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/leave-cookies-jar-turn-insight-action-adobe-analy...



Community Manager


The Blog Post below is from Jared Lees, Senior Manager of industry strategy for financial services at Adobe.


Solve the Mystery of Your Audience With Advanced Analytics, Targeting, and Data-Management Tools!

Did you know that 69 percent of mobile users currently do some form of banking on their phones? Customers rely on you to provide them with optimized experiences that fit their preferences and contexts — but without jeopardizing their sensitive information. The good news is that customers are leaving hints everywhere regarding their needs and desires — such as why they’re calling your branch, how they use your mobile app, or what page they visit on your website.

Unfortunately, despite all of this rich information, financial institutions struggle to find meaning within their data. In fact, of the 83 percent of finance executives who say their firm’s data is their most strategic asset, 47 percent claim they don’t know how to employ it to drive value. These statistics make perfect sense. Old and siloed systems make it challenging to unify mismatched datasets that have been gathered from mobile devices, websites, branches, and call-center interactions. How can your organization thrive in this challenging environment? It all boils down to data-driven marketing. You have to transform your data into actionable intelligence and then wow your customers with rich experiences that keep them coming back for more. With new analytics and data-management capabilities, you can do just that. Where should you start? Keep reading!

Read Your Customers’ Minds.
Use data to create personalized experiences for your audiences. Customer interactions leave behind hints, creating digital fingerprints that can be analyzed for an abundance of information — right down to what your customers are doing or even how they’re feeling at that very moment. A recent survey found that 53 percent of millennial audiences claim that their banks don’t offer services that are any different from other banks. To differentiate your brand, leverage analytics to better understand your customer and context so you can offer the right product or service at the right time and personalize an experience that meets the needs of your audience.

Remember, when you create a relevant, personalized experience for your customer — one that is based on what your customers are “telling” you that they want — you build trust and brand loyalty.

Put the Pieces Together.
How do you obtain a complete picture of your customer when data is scattered into individually owned channels? You don’t — businesses must share customer information across their organizations and enable business units to collaborate with one another by creating teams of cross-functional experts from different parts of the business and enabling those experts to collaborate with one another. Sharing the same customer data across multiple channels creates a ‘platform’ where data can be aggregated into a single profile or segment ID. The goal is to unite various business units behind a single view of the customer and combine traits from customer-data sources to gain a more accurate, collective view of your customers.

Investigate the Customer Journey.
Data-driven marketing enables you to quickly communicate with your customers across all channels in a relevant manner. Now that you have access to connected, comprehensive customer information, the next step is to match the right offer or content within the context of the interaction and really impress your customer. Linking data from your online and offline channels is crucial to giving your customers the consistent, relevant experiences they desire. For example, let’s say that a customer is looking at auto-loan information on your website. Automatically sending him an email or direct-mail offer about auto loans is a great way to grab his attention and continue the conversation — and all automated based on his browsing behavior. The ability to personalize your customer experience is a vital factor standing between someone remaining loyal to your brand — or not.

Keep an Eye on Things.
Having an understanding of your customers’ behaviors and preferences is key, but it is equally important to measure performance and look for ways to optimize the customer experience. It is critical that you monitor marketing performance and your customers’ behaviors during their interactions with your brand, using analytics and data-optimization capabilities.

One capability to consider is anomaly-detection, which allows you to automatically see when an event doesn’t follow a set pattern. If your website bounce rate is increasing, the anomaly-detection feature will alert you. From there, contribution analysis can be applied to all of the factors potentially causing this particular issue so it can be fixed.

Additionally, advanced analytics, machine learning, and algorithmic attribution allow you to see how each marketing touch guides the customer’s journey toward conversion. The customer journey can be synchronized and personalized so every need is met at just the right moment. Experience metrics, solid reporting capabilities, and clean data keep you in step with your customer journey.

Act on Facts — Not Hunches.
Data-driven marketing allows you to eliminate the guesswork and act on actual facts. Respond to what you know about your customers’ preferences, interests, and behaviors. Bridge the gap between insights and actions so you can respond to your customers along any part of their journeys. Real-time analytics allow you to see how your customers are engaging with your brand in real time. This data is rich with possibilities and can be used to personalize content and optimize offers at the exact second your customer needs them. You can then analyze the data to determine what works and what doesn’t and quickly make the necessary changes. The goal is to constantly improve your marketing techniques while engaging your customers in perpetually enriched, real-time, personalized experiences.

Take Action!
You don’t have to rely on data scientists or the information technology (IT) department to decode the clues your customers are leaving you. Data-driven marketing tools are available to allow you to use your data to its fullest potential. Invest in the right products and capabilities — use advanced analytics, targeting, and data-management tools to blow your customer away with an immersive, personalized, real-time experience. It’s easier than you think.

To learn more about decoding your customer’s clues, read the white paper: Customer Clues. Solve the Mystery of Your Audience.


Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/solve-mystery-audience-advanced-analytics-targeti...



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The Blog Post below is from Raj Sen, Group Product Marketing Manager at Adobe.


Transform Your Business Into a High-Performance Machine with Data-Driven Marketing!

Imagine your company is a car. Your performance indicators — and the goals they support — are the big, beefy engine. But, the engine doesn’t run at its top performance without data, so you must get everyone in your organization on the same page. You need to share a clear vision of how data-driven marketing will enhance performance and make this sweet machine of yours hum. Let’s look at five ways your data-driven marketing can transform your business into a high-performance machine that blows away the competition.

1. Choose and Refine Goals and Key Performance Indicators (KPIs).
Your datasets are really only useful if they’re focused on your key metrics and the business goals they support — in other words, your engine. If you want to improve the power output of your car’s engine, you have to modify the ratio of air to fuel that’s going in, get it all to burn faster, and then dispose of the waste as efficiently as possible. The same is essentially true of your KPIs.

As you decide which goals you want to pursue, you can select the appropriate data you’ll need to support each goal. Then, use that data to move toward the completion of your goal and discard the stuff that doesn’t work. Manage intake. Use it effectively. Get rid of waste.

2. Use Your Data to Make Better Decisions More Quickly.
Decisions can make or break a business. Every day, thousands of decisions are made in your organization. Some are big, some are small — but all have impact. Put simply, data gives you the ability to make better decisions more quickly.

When you modify your car’s engine to improve its performance, you have to also make similar changes to the structure of the car — the transmission, the driveshaft, the powertrain — to support the added power. In your business, your ability to make decisions is the structure that provides you with the control you need to move your key metrics and achieve the goals they represent — and data enables this ability.

3. Create Real, Compelling Customer Experiences With Data-Driven Marketing.
Historically, the requirements necessary for actually pulling off customer-centric marketing were essentially nonexistent; but today, data-driven marketing can make the promise of customer experience a reality. Storage space and processing speeds were once serious roadblocks for all industries, but technology is doing more to empower customer experiences than simply clearing away legacy roadblocks.

Today, technology is answering questions that no one would have thought to ask several years ago. For example, more remarkable than the ability to store enough data is the ability to use that data selectively and with unheard-of precision. This precision is essential for creating the experiences your customers expect — because, at its heart, customer experience is about using the power and responsiveness of your organization to race more quickly and compellingly into the hearts of individual customers.

4. Focus Not Only on Tracking Spending, but Also ROI.
One of the crucial roles that data-driven marketing can play in your organization is to make sure you’re spending your money wisely. It’s vital to not only accurately track your spending, but also to actually earn a return on that spending.

When you’ve invested in building a serious muscle car, an important part of the equation is the control that comes from visibility. Data-driven marketing works like the clear windows and projected speedometers that improve visibility in a car. It allows you to make the most of your well-oiled business machine by helping you to see where you’re going now, decide where you want to go next, and understand your potential to get there quickly.

5. Trust Data-Driven Marketing to Be a Performance Boost!
It probably comes as a relief to many marketers that humans still have roles to play in the data game. But, automation and employees — data and people — are not independent of each other. They exist together in a mutual relationship, and if you’re doing data-driven marketing right; then data, automation, attribution, and every other technology or tactic should actually make those humans better.

Today, whole businesses thrive on nothing but dashboards to make data accessible to the lay worker. At the same time, analytics software is becoming increasingly more sophisticated in its ability to offer self-service and usable data.

This kind of universal interaction with data is at the heart of what makes data-driven marketing a performance boost for your business. If everyone in your organization is making intelligent, data-driven decisions, then you’ll get the most out of your machine.

If you’re looking to improve the performance of your business using data-driven marketing, you must keep your eyes open regarding what makes your engine run well. Data-driven marketing delivers real, tangible benefits. If you’re careful and thoughtful about how you implement it, it can measurably and demonstrably improve your business.


Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/transform-business-high-performance-machine-data-...




Scatter Plots in Analysis Workspace

Last week, I wrote about how to use the new Venn Diagram visualization in Analysis Workspace. Now I will discuss another new Analysis Workspace visualization – the Scatter Plot. This visualization should be familiar to those in the field and has been available in Microsoft Excel for years. The purpose of the scatter plot is to show two (or three) data points on an x/y axis so that you can visualize the differences between them. In this post, I will continue using my blog as an example of how the scatter plot can be leveraged.


The first step in creating a scatter plot visualization is to create a freeform data table. This normally means adding a dimension and a few metrics. I would recommend starting with two metrics that you want to see plotted against each other. Here you can see that I am looking at my blog posts sorted by popularity and also added Visit Time Spent:


Read the rest of this post on analyticsdemystified.com



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


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.


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



Community Manager


The Blog Post below is from Chris Wareham, Director of Product Management for Adobe Analytics


Adobe Analytics Drives Superior Video Analytics with Video Stream Measurement

Digital video isn’t the next big thing: it’s already here. As people continue to consume content where they want, when they want (TV Everywhere, or TVE, video viewing grew 107 percent between 2015 and 2016), it’s clear that optimizing and analyzing this experience is a must for any publisher or programmer. And with one of the largest broadcasting conferences, IBC, around the corner, Adobe is thrilled to announce our newest video analytics release, providing new and improved measurement for both content and ads.

Measurement is one of the major friction points when it comes to television consumption across devices. While traditional television ratings are a longstanding institution, and the foundation for major decisions for everything from programming to ad buys, the digital transformation currently happening simply wouldn’t be possible without standardized metrics. As video measurement grows increasingly important for marketers to drive major decisions, the significance of these metrics comes into focus daily. The ability to obtain data such as time spent, ad performance, device, geography, bounce rates, impressions, and more is now a crucial piece of the pie.

Adobe Analytics for Video offers brands a variety of benefits, including:

Lighter, simpler implementation: Implementations are 50–60 percent faster than before.
Greater flexibility: The SDK is much more flexible with respect to how the API calls are triggered.
Streamlined configuration: Enjoy easier control as all API calls are centralized in one place.
Error state recovery: Adobe’s Video Heartbeat Library keeps track of the current state of the playback and can automatically ignore any errors that may pop up. For example, if a buffer complete is sent without a previous buffer start, this won’t be included in the report.
Adobe has a strong footprint in the video analytics space, working with 10 out of 10 of the world’s largest media companies, 4 out of 4 of the world’s top broadcasters, 5 out of 5 of the largest cable companies, and 4 out of 5 of the top digital news sites. With more than 100 billion videos measured in 2015, this new measurement model will help marketers more clearly understand video engagement, faster.

One of the biggest challenges broadcasters and programmers face is getting detailed insights into viewing patterns. In the past, brands would pick how many server calls to send in for playback (i.e., every minute, every quarter of the video, or at the halfway mark and ending). While this approach provided insights for many brands, ultimately it presented a problem due to the lack of granularity, and the decision was often based on cost.
Adobe’s video analytics model measures engagement (time spent) with “heartbeats” pinged every 10 seconds during a video playback and/or during a live event. The initial start server call is sent directly into Adobe Analytics; however, all heartbeats are sent to a new processing layer, which aggregates those heartbeats until the viewer ends the session (i.e., completes the video, closes the browser, switches to a new video, etc.). When the viewing session is complete, a second and final server call is sent to the Adobe Analytics platform to complete the playback data set. The 10-second heartbeat measurement eliminates the blind spot and offers a much more thorough view of how content is being consumed.

By analyzing video streams, rather than just starts and stops, brands can gain a more complete picture of how content is being consumed. Moving away from simply monitoring milestones based on server calls, streams not only provide brands standardization across video performance metrics (such as video, ads, segments, and quality of experience), but also provide deeper insights into media consumption. Adobe also provides the ability to democratize video analytics—such as sharing video metrics with syndication partners for greater transparency beyond simply a brand’s properties. Additionally, stream-based measurement is the foundation data required for Adobe Certified Metrics, the standardized digital census data that Nielsen Digital Content Ratings and Federated Analytics require.


Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/adobe-analytics-drive-superior-video-analytics-wi...




4 huge time-saver tips for Analysis Workspace in Adobe Analytics

Nowadays, there are lots of Workspace tips and tricks available. Probably you have seen flashes of these in some Adobe videos or discussions, but want to anyway share these again, because these are so important tips and will save hours of your time in the long run of your analysis work.

1) Duplicate freeform tables
Without a doubt the best time-saver tip forever. I thought this was impossible and I wrote to Adobe’s idea exchange about this feature. Luckily, Eric from Adobe replied, it is already possible. Whaat? Could it be possible? Impossible is nothing for workspace?  You just right-click on the top of freeform table and it will give you option to “duplicate visualization”. Just click it and boom, you have duplicated freeform table.

Read rest of the tips and full blog post in here: http://www.anttikoski.fi/4-huge-time-saver-tips-for-analysis-workspace-in-adobe-analytics/