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Antti_Ko

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Antti_Ko

Antti_Ko

07-10-2016

Basics of pages, marketing channels and tracking codes in Adobe Analytics

Sometimes it’s good to go back to basics. I’m sure for analysts using Adobe Analytics this blog post might be bit boring, but maybe you should show this to your friendly marketing manager who might not be so famialiar about the basic concepts of Adobe Analytics. I could write a book about these basic features of Adobe Analytics because there are so many possibilities to do different kind of settings for your AA variables and marketing channels etc.

Adobe Analytics is powerful tool, but with superfeatures comes some complexity. Actually, I got the idea to write this post from Adam Greco’s “different flavors of success events” posts. You can read those in here (part1) and in here (part2). Hopefully more to come. Don’t you just love Adam’s posts? Those are always just pure diamonds and useful stuff you can use yourself.

I was thinking to test all those different event allocations too with my blog and make a small post based on the results. But you know me, when I get started with a small testing, I always get so many “ah, oh” moments and want to tell more about that and this too. I did a journey on my site and let’s see what kind of reports we get when looking marketing channels, tracking codes and page reports.

Read the rest of the blog post in here: http://www.anttikoski.fi/basics-of-pages-marketing-channels-and-tracking-codes-in-adobe-analytics/

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KristiB1

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KristiB1

KristiB1

10-10-2016

Great article on Reporting window allocation and event assists in Adobe Analytics from Annti Koski

http://www.anttikoski.fi/reporting-window-allocation-and-event-assists-in-adobe-analytics/

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TanmayMathur

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TanmayMathur
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18-10-2016

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.

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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...

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TanmayMathur

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TanmayMathur
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23-10-2016

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

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New Adobe Analytics Capabilities Make Powerful Insights More Accessible

Behind every great digital experience is robust data. Each time a consumer launches an app or puts an item in a shopping cart, a piece of data is created. Brands that are able to gather all of this and make sense of it can engage their audiences in ways that are intuitive and highly personalized. As consumers become increasingly selective about how they spend their time across digital channels, data is the secret sauce to draw in new customers and retain existing ones.

The tools we provide in Adobe Analytics bring together Adobe’s creative heritage with a robust data platform, to not only help brands analyze data and uncover insights at the click of button, but to also become better storytellers in driving action across their organizations. With Analysis Workspace, users have a visual editing platform to deliver, discover, and visualize insights and curate them to share with the organization.

Today we are announcing new capabilities in Analysis Workspace that furthers our mission to democratize analytics.

Flow Exploration and Fallout Analysis

The first step to delivering great consumer experiences is having an understanding of how people are navigating your digital channels and where they are hitting stumbling blocks. A new Flow Exploration capability within Analysis Workspace let’s brands visualize customer movement through digital experiences, showing the steps taken from entry point through to conversion or churn. Segments of users can be created based on usage patterns. A cohort of customers who are bundling related items, for instance, can be engaged with content on other suggested pairings.

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The new Fallout Analysis in Analysis Workspace allows brands to easily drag, drop, and rearrange steps along the user experience to better understand at what point users are disengaging, in addition to insight around where they go after the fallout. With this data available, brands can implement the necessary adjustments to not only retain users but also improve the experience and drive more loyalty. Analysts can also create audience segments from users who stay in the funnel, or those who fall out, at any stage for remarketing and personalization.

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A home improvement retailer, for example, might see that, on their mobile app, users who have to leave the shopping cart to view more items abandon purchases at higher rates and don’t return. This insight can be leveraged to re-design the cart experience as a floating interface that remains on the app screen.

Getting A Faster Start

Organizations are increasingly pushing every team member to become more data-driven in their decision-making. Given that, tools must appeal to the most novice user while still serving the needs of the most advanced analysts. We all know how difficult it is to stare at a blank page, which is why we are introducing new starter projects in Analysis Workspace. These will provide a more natural ramp-up for those trying Analysis Workspace for the first time. With out-of-the-box answers to common business questions across the web and mobile apps, as well as specific templates for vertical industries including Retail and Media & Entertainment, no one should have to be a data scientist to leverage insights to improve their work.

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Seeing The Forest for the Trees

In this release, we are rolling out a series of new visualizations, as well as enhancements within Analysis Workspace that will provide users more tools to curate and present insights in ways that resonate most with stakeholders.

Time-series analysis: Within line graphs, users can now forecast expected future outcomes or automatically detect data anomalies and run contribution analysis in a single click to determine the cause of unexpected performance. A financial services company could tap into this to determine the cause of a spike in credit card applications during a typically slower month, for example.

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Histograms: In a classic bar chart, each bar shows an individual value. A histogram is different in that it presents distribution. This is useful for brands as they’ll be able to pinpoint the most valuable and least valuable segments of customers, as well as the distribution of a certain behavior. A clothing retailer, for instance, can identify that most shoppers spend between $25 and $50 and turn that into a key segment for holiday promotions.

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Date comparisons: At the push of a button, users can now compare data year over year, month over month, or day over day. All of this is presented in a single graphic to visualize the change, while serving up data points around percent changes as well as raw values. This can better inform everything from inventory to campaign planning.

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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/new-adobe-analytics-capabilities-make-powerful-in...

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AdamGreco

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AdamGreco

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AdamGreco
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24-10-2016

Analysis Workspace - The Future is Here

One of the great things about Analysis Workspace is that it begs you to keep driving deeper and deeper into analysis in ways that the traditional Adobe Analytics reports do not. I have heard Ben Gaines talk about this as one of the reasons he loves Workspace so much and he is spot on. Ever since it burst onto the scenes, those who understand Adobe Analytics have realized that it represented the future of the product. The only thing holding it back was the fact that some key types of reports were unavailable, forcing users to continue to use the traditional Adobe Analytics reports.

However, this all changed yesterday. I believe that October 20th will go down in history (at least the history of Adobe Analytics geeks like me) as the day the world changed! On this day, a host of great new Analysis Workspace visualizations were released. These include:

While this may not seem like such a big deal, let me tell you why it is a huge deal. I believe that these additions represent the tipping point in which Adobe Analytics end-users give in and decide that Analysis Workspace is their primary reporting interface. While I have seen some of my clients dive head first into Analysis Workspace, I have also seen many of my clients “dip their toe in the water” with Analysis Workspace, but fall back to their comfort zone of traditional reports. It is my contention that this will no longer be possible and that Analysis Workspace will become the default going forward. Of course, this will take some time to learn the new interface, but the advantages are so compelling at this point, that those not making the shift will risk becoming Adobe Analytics dinosaurs.

Read the rest of this blog post on analyticsdemystified.com

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TanmayMathur

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TanmayMathur
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24-10-2016

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-gart...

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TanmayMathur

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TanmayMathur
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27-10-2016

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

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Empowering Organizations With Smarter Analysis

As we talk with people — from thousands of companies all over the world — about their efforts to drive growth through smarter, data-informed decisions, a few clear trends emerge. First, analysis tools must make it easier for everyone in the organization — from top to bottom — to obtain insights. Second, and relatedly, analysis tools must assist all data consumers with achieving more relevant insights by bridging the gap between Big Data and human intuition with machine learning and other “smart” capabilities.

I’m excited to be part of the team that is realizing the vision of these two themes. The Adobe Analytics Fall 2016 release, available now, includes a handful of new features and capabilities that will directly help you drive better decisions through “smarter analysis,” aided by powerful machine learning within Adobe Analytics. In the rest of this post, I’d like to walk you through what our team has done to make your analysis tools smarter.

There’s a lot of great stuff in here, so grab a coffee, and let’s get going. By the way, everything I share in this post is available today in Adobe Analytics.

Intelligent Alerts
You can now receive an early-stage “heads-up” that something truly significant is happening in your business. We have updated our built-in email- and SMS-alerting capability to use Anomaly Detection as the default mechanism for determining whether to notify you of a spike or dip in a key metric. Anomaly Detection looks at your historical data to determine an expected range of values for a metric, and now it also takes seasonality and major holidays (including Black Friday) into account. This means that you can expect no more false-positives in your alerts — if your traffic always decreases on the weekend, you won’t be alerted every single Saturday morning. Alerts that you set up based on Anomaly Detection will be triggered only when there is a statistically significant spike or dip.

Another huge improvement here is that you can “stack” alerts. Let’s say, you have six different metrics that a certain team is interested in. You can set up a single alert that includes all six metrics and set it to be sent to everyone in the given user group. This carries several advantages. First, you will only need to manage one alert instead of six. Second, if all six alerts happen to spike simultaneously, the recipients will only receive one email instead of six, meaning it cuts down on what we might call “alert fatigue.” Third, by sending to a user group, new employees who are added to that group will automatically begin receiving these alerts; similarly, employees who move out of that group won’t need to be manually removed from the alert.

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You can set up alerts a few ways. You can always go to Components > Alerts to create a new alert or manage existing alerts. But, you can also right-click just about anywhere in Analysis Workspace to set up an alert based on the data point you have highlighted. That’s my preferred way, because it preconfigures the alert for you and allows you to stay in your workflow without leaving Analysis Workspace.

Take special note of the “Alert Preview” window in the upper-right corner of the Alert Builder. This view lets you know how many times the alert you’ve configured would have been triggered based on your recent data. By observing how often the alert would have triggered, you can adjust your anomaly thresholds or other criteria so you are not alerting your users too often.

Distribution of alerts has also been improved. The email you’ll receive looks a lot nicer, and you can send alerts by both email and true SMS. International telephone numbers are supported, and you’ll want to enter the country code as well (as shown in the screenshot above).

Automated Anomalies in Analysis Workspace
If you’re like most of us, you value anything that saves you time. This effect is probably multiplied in the world of data, where separating signal from noise can be difficult for even the most polished analyst. That’s why I am so excited about improvements to Anomaly Detection, as we bring this powerful machine-learning technology into Analysis Workspace.

Adobe Analytics has featured Anomaly Detection since late 2013. But to this point, it has only been available for daily data, and it has been confined to a report in Reports & Analytics. With this release, any hourly, daily, weekly, or monthly time-series data in Analysis Workspace — whether in a table or a line graph — will automaticallyshow anomalies based on your historical data and predicted trends.

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Create a freeform table, using date as my dimension, and I immediately start receiving insights into statistically significant spikes or dips in my metrics. Add a line graph, and anomalies are called out as hollow data points on the graph. Hover over any of these points in the table or on the graph to gain more details about the anomaly.

As a bonus, if you are an Adobe Analytics Premium customer, you can right-click on these data points to run a Contribution Analysis, which scans hundreds of thousands of values of dimensions to find the likely causes of an anomaly — directly in Analysis Workspace, so you can embed the why along with the what in your projects.

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In keeping with the idea of automated insights, there is nothing you need to do to turn this on or to activate this feature — just start building time-series data tables and visualizations, and away you go!

Histograms
Averages (means) are good for quick snapshots, but as any analyst will tell you, they often hide tremendous insights behind their single-number façade. Histograms, which we’ve added as a visualization in Analysis Workspace, tease out those insights by showing the distribution of your audience across buckets (“bins”) representing escalating tiers within any metric. This makes it much easier to identify high- and low-value segments and market to them accordingly.

To use a histogram, just drag it from the collection of visualizations onto one of your panels. It will ask you for a metric, which you can also supply from the left. The histogram will bucket your visits or visitors according to how much/many of the selected metric they had. For example, if I use revenue as my metric, by default, it will bin my visitors by how much revenue they had. Using the advanced settings, I can adjust the number of bins, the size of each bin, and the starting bin (primarily, so I can choose whether to include visitors who had zero of the selected metric).

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The distribution of revenue per visitor in my dataset is mostly normal; however, there is a bit of an uptick on the right side, so the group of customers who are spending $600–700 is larger than I might have expected. If I want to analyze that segment further, I can click the dot in the upper-left corner of the visualization and choose to show the data source. In the data table that is revealed, I can find this segment and begin to explore it directly in that data table. I can also drag it to the top of the panel to apply it as an ad-hoc segment, so I can add other data tables and visualizations that will help me better understand this group of customers who are behaving interestingly.

Conclusion
I’m sure you can see how we are advancing our goals to empower your organization with more recommendations powered by machine-learning intelligence and advanced analytics, but these features, and the benefits they provide, are just the start for us. We’re excited to continue our journey in helping you turn your company into a truly brilliant enterprise.

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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/adobe-analytics-fall-2016-release-empowering-orga...

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TanmayMathur

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TanmayMathur
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01-11-2016

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

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Making Insights Easier for the Enterprise

In my last post, I covered the aspects of the Adobe Analytics Fall 2016 release that make Adobe Analytics“smarter,” aiding your analysis with machine learning and intelligence. This is one of the most pressing needs we encounter, as we speak with people from large and small organizations all over the world.

In this post, I break down the features in our most recent release that make it easier for users of all experience levels to generate insights from within Analysis Workspace. And, as with my previous post, everything discussed here is available today in Adobe Analytics.

Customer Journey Analysis
One of the first pieces of feedback we received after we released Analysis Workspace was that you wanted more insight into the customer journey. You explained that you need to understand how your app users and site visitors are progressing through their digital experiences, so that you can remove barriers from the conversion process to optimize revenue-generating opportunities. I’m happy to report that we have added two customer-journey visualizations — Fallout (which includes Funnels) and Flow — to Analysis Workspace (the alliteration was entirely unplanned):

  1. Fallout — Fallout is designed to help you analyze each user’s progress through clearly defined paths (or funnels). When you know the exact set of steps that you want to analyze, Fallout is for you.
  2. Flow — Flow, on the other hand, is more exploratory, allowing you to expand and contract your view to examine different ‘branches’ and repeatedly ask, “But, what happened next?”

You can add both Fallout and Flow to any Analysis Workspace project from the left rail where you will find them in the visualizations area. After placing them on the canvas, you can begin adding touchpoints in the forms of dimensions, values, segments, and/or metrics.

One of the great improvements to pathing with this release is the ability to use Custom Conversion (eVar) values as touchpoints in addition to more traditional dimensions like Page, Site Section, Video Name, and more. The Fallout visualization also allows you to use metrics as touchpoints. Here’s an example using a combination of eVar values, page names, and metrics to create a funnel (with the right-click menu expanded as well).

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You can also mix and match dimensions in the Flow visualization. Following is an example that shows entry pages along with the internal search keywords that followed from those entry pages. Not shown is the ability to hover over any of these branches to see them highlighted, calling attention to the path you’re investigating.

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Included in these customer-journey visualizations are rich segmentation functionality. As you probably expect, you can apply segments to any of these visualizations. However, you can also right-click anywhere to build a new segment based on the path you have defined, so you can use that segment elsewhere to better understand the users who follow (or don’t follow) specific paths. One of my favorite features of the Fallout visualization is the ability to add multiple segments directly to the visualization — by dragging and dropping them into the header — to compare how different segments fell out of these funnels.

Entire blog posts could (and probably should!) be written on just these two new customer-journey visualizations, so I recommend playing around with them and trying out everything they can do. Remember that right-clicking reveals access to a bunch of additional options you can use to extend the power of these new tools even further.

Starter Projects
As mentioned above, roles in the organization that may have ignored data previously are finding that they can no longer do so. But, analysis can be difficult, overwhelming even! There are so many ways to define success — and so many options for visualizing and digesting customer insights — that it is sometimes difficult to know exactly where to start. Curation in Analysis Workspace helps solve this problem by limiting thousands of dimension, metric, and segment choices down to the few that matter to a given team, but it still relies on the analyst to create these projects.

Enter stage left, “Starter Projects” in Analysis Workspace. Starter Projects are easy-to-use templates that Adobe has designed and built around specific areas businesses question such as “Content Consumption,” “Mobile App Performance,” “Acquisition,” and more.

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Any user of Analysis Workspace can launch a starter project and be presented with a standardized set of visualizations that address the topic selected. And, since they are in Analysis Workspace, they come with the ability to do additional breakdowns, comparisons, curation, sharing, and more.

If I were a product manager for a mobile app, I’d be very interested in understanding app retention — in fact, this might be one of the key areas on which I am focused. But, it would be difficult for me to understand app retention by building my own project from scratch. Instead, I can now come to Analysis Workspace and launch this handy Starter Project. If I need to do some customization — add a new visualization or apply segments, for instance — I can do that. I can even save my changes as a new project and share it with the rest of my team so that they can check out the progress we’re making toward our retention goals as well.

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These Starter Projects are also pre-curated to the dimensions and metrics that are most relevant to the business question at hand to prevent users from being presented with too many customization options when they first launch one of these templates.

There are 15 Starter Projects to choose from today — with many more coming soon in these and other role-based categories. This is just the beginning of our efforts to help you expand the wise and simplified use of data in your organization.

Permissions Improvements
As you may have seen in a previous announcement, this release also includes major improvements to permissions in Adobe Analytics as well as across Adobe Marketing Cloud. Within Adobe Analytics, admin-level users will notice a handful of changes.

Perhaps most excitingly, you can now set permissions on Custom Conversion (eVar) dimensions. In the past, you could grant or restrict access to any conversion metric but not to these dimensions. This change gives you greater control over data access, ensuring that only the right people can see the data in your conversion dimensions.

This change also moves access to various Adobe Analytics tools — such as Ad Hoc Analysis and Report Builder — into custom groups so that you can manage 100 percent of permissions in one place rather than be required to jump back and forth between pages in the Admin Console to control access to these tools.

Ultimately, this update sets the stage for better user management in the future — all across Adobe Marketing Cloud (as well as Creative Cloud and Document Cloud) — through the Adobe Enterprise Dashboard.

Analysis Workspace User Interface (UI) Enhancements
Last, but certainly not least, we made a number of improvements to the core of Analysis Workspace itself. You’ll notice significantly better in-browser performance. Right-click menus, the Segment Builder, and other components of Analysis Workspace load much faster, as do breakdowns you perform.

We’ve refactored the Segment Builder and the Metric Builder so that they use the same left-hand rail as Analysis Workspace — with dimensions, metrics, and segments aligned vertically; and the ability to obtain search results that include all types of components that can be added to your segments and metrics. This not only makes it faster and easier to find the components you are looking for, but also makes segment and metric creation more efficient.

We redesigned date selection in Analysis Workspace to make it more like the calendar in Reports & Analytics. You can now select both the start and end dates from the same calendar rather than have separate “start date” and “end date” calendars.

And — perhaps my personal-favorite, sneaky-cool change to Analysis Workspace in this release — when selecting dimensions, metrics, segments, and time ranges from the left-hand rail, you can now click the “Actions” menu to tag, favorite, approve, share, and/or delete what you have selected. This makes it so much easier to manage your segments and metrics (among other things) while you’re working within Analysis Workspace. You no longer need to go over to the Segment Manager or Calculated Metric Manager.

internal-image-6-making-insights-easier-for-the-enterprise

Conclusion
We’re excited to continue delivering on the promise of Analysis Workspace by making it even easier for organizations to drive better decisions through data-informed insights. The Adobe team will continue working to empower you and your colleagues with simpler experiences throughout Adobe Analytics.

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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/adobe-analytics-fall-2016-release-making-insights...

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TanmayMathur
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04-11-2016

Below blog post is from Nate Smith, Product Marketing Manager for Adobe Analytics

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Bridging the Divide Between Digital and Non-Digital Marketing Engagements

We all have people in our lives to whom we only speak and interact with at work. They’re nice people — we enjoy working with them. For whatever reason, we just haven’t gotten to know them outside of the office. While we know some things about these people — how they structure their emails or whether they prefer iOS or Android devices, for instance — we don’t really know who they are or what they do outside of work. As a result, it’s unlikely that we’d be able to piece together complete profiles of these people, let alone predict the choices they would make in given situations. The only people you truly know are those with whom you interact in all facets of their lives.

To a large degree, the same is true regarding your customers. If you don’t understand the full spectrums of their interactions with your brand — online, offline, and through every possible channel — you don’t have complete pictures of their behaviors, traits, and preferences. As such, you can’t really know whether they’re satisfied with your brand, much less anticipate what would make their experiences with your brand even more positive.

Marrying Digital and Non-Digital Touchpoints
Digital marketing data often comes from a number of channels — email, social, web, and more. When you add non-digital data sources to that, understanding omnichannel customer engagement and campaign attribution can start to seem overwhelming. However, if you don’t have insight into things like real-life phone conversations customers had with call center-support teams or point-of-sale interactions they had with your store managers, you don’t really have complete pictures; which could impact the customer experience in unintended, possibly even negative ways — and ultimately, the bottom line.

For instance, let’s say a first-time customer purchases a pair of adult ballet shoes from your store. You may try to entice her to make additional purchases by sending her an offer for tights. But, that offer may miss the mark if you don’t know more about what she’s doing offline. Perhaps those shoes were a gift for someone else. Perhaps those shoes were for a new hobby she had hoped to start — until it stimulated an old injury. If you know she’s recently been searching your site for ankle braces, you can send her personalized offers about ankle support and rehabilitation, so your offers are as well-received as possible. If you know what is happening offline as well as online, it’s much easier to make sure your marketing efforts actually hit the mark.

Creating an Integrated Customer Profile
So, how do you bridge the gap between digital and non-digital marketing data? To do this, you need to capture and integrate several types of event and attribute data. First, though, you must make sure your digital house is in order — is your email integrated with your web analytics so that you can combine pre-click email-campaign data with post-click site-engagement data? Do you have your survey data connected to add qualitative dimensions to your customer profile analysis? As you become adept at new types of analysis, you can then add offline datasets to enrich the customer profile. Make sure to start small — integrate one new dataset and see what new insights are revealed. Common next steps can include:

1. Customer Attributes
The base of most customer profiles can’t be ignored. This data typically comes from your customer-relationship management (CRM) system (or some type of enterprise record-management system). This can also include demographic data (e.g., gender, age) as well as psychographic data (e.g., interests, hobbies) and is a key component in building an integrated customer profile. Start with this basic information and build from there.

2. Customer Engagement Data
Once you have customer-attribute data in hand, you should integrate customer-engagement data such as event-level campaign and activity data. If you are a B2B company, you’ll want to look at this data from an account view as well as individual views. To build a truly integrated customer profile, you need to include both online and offline customer interactions with your brand.

3. Non-Marketing Data
Customers can communicate with your organization in a number of ways — with more than just marketing touches. A common next set of data revolves around the customer-service part of your business, typically post-sale. Phone calls, texts, or chat conversations with customer service are important engagement points that must be part of the customer profile. A customer who is unhappy with his current purchase won’t want to be contacted by email with an offer for a complementary service. This data can provide you with a rich understanding of what your customer’s disposition really is.

Making the Connections You Need
Bridging the gap between digital and non-digital marketing data and marketing efforts is no longer an option. In today’s marketplace, customers expect personalized messaging and seamless brand experiences. It’s critical that you start creating an integrated customer profile to marry the information you receive from all marketing platforms and customer-engagement points. Learn more now about how to integrate digital and non-digital marketing data.

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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/bridging-divide-digital-non-digital-marketing-eng...

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TanmayMathur
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07-11-2016

Below blog post is from Emily Chu, Senior Manager for the customer reference program at Adobe

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Reliable Marketing Data Helps WestJet Boost Online Bookings and Achieve Greater Savings

In an industry where higher fares coupled with fewer services is becoming the norm, WestJet quickly became Canada’s second-largest airline, building the company’s reputation upon their ability to consistently deliver outstanding services and offer amazing savings. The company aims to delight passengers by providing them with relaxing, fun experiences that exceed their expectations — in the air, on the ground, and online. Those experiences include WestJet’s digital marketing campaigns.

In recent years, WestJet’s holiday video campaigns have achieved viral success, showing WestJet that creative and meaningful campaigns — based on targeted, reliable data — can guide marketing strategies to reach more travelers, drive more website traffic, and more positively impact the bottom line. To effectively deliver and measure better digital customer experiences, WestJet relies on Adobe Marketing Cloud solutions. For instance, Adobe Analytics allows WestJet’s marketers to gauge how customer experiences across multiple channels — including email, web, app, and social media — increase online bookings.

“Because we can see how successful our campaigns are, we know which ones are best at encouraging customers to book on our website instead of other channels,” says Ahmed Elemam, senior digital analyst at WestJet. “Increasing online bookings can help us achieve greater savings that we can also pass on to customers.”

Personalized customer experiences can increase those sales and savings. Adobe Audience Manager and Analytics work in tandem to power messages — such as fare upgrades or rewards-program benefits — sent to consumers after they’ve booked flights, and Adobe Target identifies a customer’s location to deliver relevant ads.

Using Adobe Media Optimizer alongside Analytics allows WestJet to review search-campaign performances daily to maximize search-engine marketing (SEM) investments. Besides reducing SEM support time by 40 percent, overall costs of weekend campaigns dropped 14 percent.

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Read the original blog post at - https://blogs.adobe.com/digitalmarketing/analytics/reliable-marketing-data-helps-westjet-boost-onlin...