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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/transcend-tags-and-deliver-experiences/
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!
Below blog post is by Jennifer Cooper, Adobe's director of industry strategy in media and entertainment
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The fall TV season is making its shift to the holiday TV season — meaning, it’s time for TV broadcasters to thoroughly investigate their analytics to determine what’s working and what’s not. Seriously, just glue yourselves to your analytics.
Why? Because the viewing behaviors that inform your business vary significantly by show and by audience demographics. Some shows are performing better outside the C7 window than inside. Some — potentially many — consumers are viewing your shows via streaming video. It’s not enough to just know the industry trends. You need to know the extent to which industry trends manifest on your own sites and apps.
Some of your analytics-driven insights will align with the industry trends. For instance, data from Nielsen Total Audience suggests that younger audiences that are watching adult animated comedies will most commonly watch them via video on demand (VOD). Check your analytics to see whether this is true for you. Viewing behaviors at other intersections of content and audience are less predictable and must be surfaced directly via analytics.
Data from Nielsen Total Audience also strongly indicates that TV broadcasters can’t just assume that their shows will be watched most often via appointment-based viewing because “All programs experience lift above the Live plus 7 days delivery, although the degree of lift varies by genre — some by as much as +50%.” So, appointment-based viewing will be the least-watched for some shows.
There are plenty of things TV broadcasters can do to understand the latest trends in viewing behaviors. Last fall, I wrote about using data to answer questions like:
The questions remain the same, while the importance of the answers has grown.
Top Three Things to Look for
Following are a few things to look for when you’re viewing content ratings and census-based analytics.
1. Really Look at Your Digital Consumption.
Look at the numbers you have and factor them in as you’re putting the right programs in the right time slots. Just because you have traditionally scheduled a program on a specific day and at a specific time doesn’t necessarily mean that everyone’s going to come back. You may have many more people tuning in via TV Everywhere (TVE) and over-the-top (OTT) services this season versus last season.
2. Closely Examine Your Crediting System.
Make sure you’re correctly crediting your on-demand views in C1, C3, and C7 windows. For the views that you want to have credited to your linear content ratings, try Nielsen Digital TV Ratings (DTVR); for those you want credited to your digital-content ratings, try Nielsen Digital Content Ratings (DCR). Also, consider leveraging Adobe’s ability to pull in comScore analytics data with Rentrak and other things. In general, the more sources of insight into viewing behaviors you have, the better.
3. Intensely Study Your Personalization Capabilities.
With TVE and OTT services, a personalized experience can make the difference between attracting significant view time and loyal visitors versus no view time and bounced visitors. Gulliver Smithers, SVP product and technology for Crackle at Sony Pictures, recently stated that using a TV service without personalization is like dining in a restaurant where you don’t really like your food. You may not complain, but chances are, you won’t go back. If you want viewers to return, personalization is key.
In Sum
Overall, the wind-down of the fall TV season is a great time to look at these three things, because the viewing patterns that were established in the fall can impact your midseason replacement options as well as linear- and digital-content ratings for the next six months or more. Of course, it’s always worthwhile to care about digital consumption, crediting systems, and personalization capabilities. If you’re innovating in these areas, Adobe has tools that can help you.
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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/tv-broadcasters-time-get-glued-analytics/
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I have been sharing latest updates and news from the world of web analytics.
Do join: https://plus.google.com/communities/107286891358987483452
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Below blog post is by Nate Smith, Product Marketing manager for Adobe Analytics
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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:
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/
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Tutorial on how to create your own real-time adobe analytics dashboard.
It walks you through the basic fundamentals needed to run a Adobe Analytics real-time report. Then shows you how to build a working real-time dashboard with snazzy D3.js visualizations that you can load right now in your browser.
http://www.ryanpraski.com/real-time-reporting-adobe-analytics-api-tutorial/
Below blog post is by Jennifer Cooper, Adobe's director of industry strategy in media and entertainment
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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/
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Below blog post is by Jon Viray, Product Marketing Manager for Adobe Marketing Cloud
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The number of webpages and marketing tools has exploded. In 2011, there were roughly 100 different web-based marketing technologies, and now — just five years later — there are more than 3,800.
This explosion of web-marketing tools has given marketers a plethora of options when it comes to delivering compelling experiences, but these marketing tools have also given marketers a couple of unwieldy problems — more products that don’t work well together and more data to wrangle then integrate, for instance.
To develop an experience business, marketers need rich customer data — and there’s plenty of it available from companies’ very own websites. To capture this customer data, businesses use JavaScript tags that allow marketing tools, like Adobe Analytics, to find and store the data they need.
But, there’s a catch.
Bottleneck — Not a Scalable Solution
The availability of more than 3,800 web-marketing tools has ushered in a new reality. Setting up tags for your online marketing tools and managing them across hundreds of webpages is not something that can be accomplished manually with any degree of effectiveness.
With a traditional tag-management solution, you can streamline the process somewhat by using templates that simplify the deployment of these tools; however, even this is turning out to be a bottleneck instead of the scalable solution marketers thought it would be.
Data that flows through marketing tools should be integrated and immediately actionable. Instead, template tag managers place a wedge between marketers and the marketing tools they use by controlling when templates are updated and how they operate. Why should tag managers have ownership over templates that deploy third-party marketing tools? The answer is simple: they shouldn’t.
The Next Generation of Tag Management
It’s time for a new solution that will help marketers deliver exceptional experiences with real-time data that is both trustworthy and integrated. Adobe Cloud Platform’s Launch is a next-generation tag-management solution that enables brands to orchestrate and activate web-based marketing tools.
Launch, by Adobe, allows independent software vendors (ISVs) to build, manage, and update their own integrations that connect their products to customer experiences. This gives marketers easy access to a vast catalog of client-side technologies, enabling them to create compelling experiences more quickly than ever before.
Launch, from Adobe, will shift the way marketers gather and use data to deliver personalized, real-time experiences by:
1. Accelerating Time to Value by Simplifying the Deployment of Web Apps
Previously, Adobe customers who were using dynamic tag management had to search for the implementation codes of non-Adobe products. With Launch, marketers have one place from which they can browse, deploy, and configure marketing tools — whether Adobe-owned or not.
2. Delivering Compelling Experiences With Web Apps That Work Together
Launch, from Adobe, allows marketers to determine when marketing tools enter — or don’t enter — the customer experience. But, it also allows those marketing tools to take actions together and share data with one another.
Adobe Launch uses a marketer-friendly rule builder to determine what actions should be taken in each situation. This rule builder integrates the data and functionality of third-party marketing tags and tools by allowing extension authors to embed new capabilities — including events, conditions, actions, and data elements — into each part of the rule builder. Any marketing- or advertising-technology vendor can write a Launch by Adobe extension and build functionality onto the Adobe Cloud Platform.
For instance, let’s say a marketer wants to show a specific YouTube video based on anonymous data from Google Analytics and the customer’s actions on the webpage from Adobe Analytics. To accomplish this using Launch, a marketer would create a rule that states:
If a customer with a product affinity of “technophile” clicks on the “learn more” tab on a product page, then play a YouTube video that highlights the technical features that make that product great.
Because Launch, by Adobe, is built upon the Adobe Cloud Platform, three different non-Adobe marketing tools would be able to capitalize on its open nature by adding very specific capabilities directly into the Adobe Launch system. Doing this allows all three marketing tools to integrate as a single solution to deliver a more compelling experience.
3. Gaining More Accurate and Consistent Information With Unified Data
It’s not uncommon to have tags for 20 marketing tools on a webpage. Each tag generates data for a specific web app. Perhaps, three of those tags track revenue from the page. However, it’s also not unusual for each tag to capture revenue in a slightly different way, in which case, the three web apps that are tracking revenue are all using different data.
With Launch, from Adobe, you can define how your data — revenue, in this case — is captured and then point your marketing tools to that same correct data point. In fact, Adobe Launch listens to every byte of data that flows through it, allowing marketers and analysts to meticulously manage how data is collected, defined, and distributed across web apps. Launch empowers brands with trustworthy data to fuel the compelling experiences customers crave.
Transcend Tags and Deliver Experiences.
We once thought of tag management only as HTML and JavaScript that’s sole purpose was to put the tag on the page. Today, tag management is no longer about tags — it’s about composing the right data to serve great experiences. Since data is at the heart of tag management, selecting the right solution is critical.
It’s time to upgrade with a solution that’s completely open and extensible. With a flexible, yet sturdy, web foundation that can integrate, unify, and organize data, there will be more options for impacting and delivering on the top-notch experiences your customers crave.
Launch, by Adobe, will be available later this year. To remain up-to-date on the latest news pertaining to Adobe Launch and its release, click the “Stay informed” button on the Adobe Launch homepage.
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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/transcend-tags-and-deliver-experiences/
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There is no magical shortcut key, however, I’m going to reveal all my top resources I have used in my over 5 year Adobe Analytics journey.
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Long post, so better to read full blog post in here: http://www.anttikoski.fi/adobe-analytics-cheat-sheet/
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Trending Adobe Analytics Data After Moving Variables
Most of my consulting work involves helping organizations fix and clean-up their Adobe Analytics implementations. Often times, I find that organizations have multiple Adobe Analytics report suites and that they are not setup consistently. As I wrote about in this post, having different variables in different variable slots across different report suites can result in many issues. To see whether you have this problem, you can select multiple report suites in the administration console and then review your variables. Here is an example looking at the Success Events:
As you can see, this organization is in real trouble, because all of their Success Events are different across all of their report suites. The biggest issue with this is that you cannot aggregate data across the various report suites. For example, if you had one suite with “Internal Searches” in Success Event 1 and another suite with “Lead Forms Completed” in Success Event 1, combining the two in a master [global] report suite would make no sense, since you’d be combining apples and oranges.
Conversely, if you do have the same variable definitions across your Adobe Analytics report suites, you get the following benefits:
For all of these reasons, it is normally a best practice to have the same variable definitions across most or all of your report suites.
So, what happens if you have already messed up and your report suites are not synchronized (like the one shown above)? Unfortunately, there is no magic fix for this. To rectify the situation, you will need to move variables in some of your report suites to align them if you want to get the benefits outlined above. The level of difficulty in doing this is directly correlated to the disparity of your report suites. Normally, I find that there are a bunch of report suites that are set up consistently and then a few outliers or that the desktop website implementation is different from the mobile app implementation. Regardless of the cause of the differences, I recommend that you make the report suite(s) that are most prevalent the new “master” suite and then force the others to move their data to the variable slots found in the new “master.”
Of course, the next logical question I get is always: “What about all of my historical data?” If you move data from variable slot 1 to slot 5, for example, Adobe Analytics cannot easily move all of your historical data. You won’t lose the old data, it just is not easy to transfer historical data to the new variable slot. Old data will be in the old variable slot and new data will be in the new variable slot. This can be annoying for about a year until you have new year over year data in the new variable slot. In general, even though this is annoying for a year, I still advocate making this type of change, since it is much better for the long term when it comes to your Adobe Analytics implementation. It is a matter of short-term pain, for long-term gain and in some way is a penitence for not implementing Adobe Analytics the correct way in the beginning. However, there are ways that you can mitigate the short-term pain associated with making variable slot changes. In the next section, I will share two different ways to mitigate this until you once again have year over year data.
May you allowed marketing and promotional articles on this?
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I am sorry Ryan, only blog articles are to be promoted on this thread.
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KPIs for SiteCat when you are not an ecommerce-firm.
When you come across situations where there are no options for cart products, sale options to define the KPIs, now what? You are most likely to be a publishing or a content based firm.
Quick facts
Link clicks: Number of link clicks for any custom, exit or download links can measure the user engagement.
Download, view and launch buttons: Do not forget to implement your success event for click actions on the page. Expose an eVar to count the number of clicks on the important pdfs, zips and other files.
Unique Click event: When we want to attribute exactly one credit to each event depending on the business needs. To assure that only the first instance of a Success Event will be counted in Success Event and Conversion Variable (eVar) reports.
getPercentPageViewed plug-in: Provides SiteCatalyst to capture the percentage of a page (vertically) that the user has viewed.
Bounce Rate: Defines the quality of content and the need to dig deep, improvise the content, optimizing the page.
Exit Rate: A good way to understand which page in the process is the weakest link or not interactive enough.
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Click-Through Rates in Adobe Analytics
One of the more advanced things you can do with Adobe Analytics is to track click-through rates of elements on your web pages. Adobe Analytics doesn’t do this out of the box, but if you know how to use the tool, there are some creative ways that you can add click-through rate tracking to your implementation. In this post, I will share a few different ways to track click-throughs for both products and non-product items.
Product Click-through Rates
If you sell physical products, you may have pages that show a bunch of products and want to see how often each product is viewed, clicked and the click-through rate. In my Adobe Analytics book, I show an example of a product listing page like this:
If you worked for this company, you might want to know how often each product is shown and clicked, keeping in mind that this could be dynamic due to tests you are running or personalization tools. Luckily, this is pretty easy to do in Adobe Analytics because the Products variable allows you to capture multiple products concurrently. In this case, you would simply set a “Product Impressions” success event and then list out all of the products visible on the page via the Products variable like this:
s.events=”event20″;
s.products=”;11345,;11367,;12456,;11426,;11626,;15522,;17881,;18651″;
Then, if a visitor clicks on one of the products, on the next page, you would set a “Product Clicks” success event and capture the specific product that was clicked in the Products variable:
s.events=”event21″;
s.products=”;11345″;
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Before we start, lets understand the user metric definitions. New user are the acquired unique users this month. Repeat user are returned user from last six month. Retained user are the users this month which were also users last month. Resurrected user are repeat users this month that are not retained from last month but from some month prior to it.
Monthly Active Users = New users + Retained users + Resurrected users
Repeat Users = Retained users + Resurrected users
Read the complete article here Visitor Retention Analysis using Calculated Metric Function | LinkedIn
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