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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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Below blog post is by Jon Viray, Product Marketing Manager for Adobe Marketing Cloud
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Transcend Tags and Deliver Experiences
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.
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:
- You can look at a report in one report suite and then with one click see the same report in another report suite;
- You can re-use bookmarks, dashboards, segments and calculated metrics, since they are all built on the same variable definitions;
- You can apply SAINT Classifications to the same variable in all suites concurrently via FTP;
- You can re-use JavaScript code and/or DTM configurations;
- You can more easily QA your data by building templates in ReportBuilder or other tools that work across all suites;
- You can re-use implementation documentation and training materials.
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.
HOW DO I RE-ALIGN?
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.
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″;
Visitor Retention Analysis using Calculated Metric Function
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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