2018 Adobe Analytics Tips & Tricks Tips for upping your game in Adobe Analytics

I'm new to Adobe Analytics reporting - where do I start?

Bring on the tips!

  1. Attribution IQ
  2. Server Call Usage Reporting
  3. Time Part Map
  4. Filtering out bad bots
  5. Transaction ID Data Sources
  6. Reusable Variables with Virtual Report Suite (VRS) Curation
  7. Table of Contents project
  8. Advanced Calculated Metrics
  9. Virtual Report Suite Context-Aware Sessions
  10. Engagement Scoring
  11. Custom templates
  12. Integrations: Advertising Analytics (integrating search engine data)
  13. Integrations: Audience Analytics (integrating AAM data)
  14. Integrations: Analytics for Target (A4T)
  15. A list of all our Spark resources

Attribution IQ (released July '18) brings 10 rules-based attribution models to Analysis Workspace to help you quantify the value of your marketing efforts & beyond. The new models include U-shape, J-shape, inverse-J, same touch, custom starter/player/closer and time decay, in addition to existing models of first, last, linear, and participation. Attribution IQ can not only be applied to marketing channels & campaigns, but nearly any dimension (eVar or prop) collected in Analytics and requires no new implementation.

  • A new Attribution panel has been added to Analysis Workspace, that allows you to compare attribution models across a dimension & metric of your choosing.
  • You can also adjust attribution directly in freeform table metric columns. This allows you to change attribution on-the-fly, and compare models side-by-side within a table. (see video below)
  • Attribution models will also be available in the calculated metric builder. Calculated metrics allow you to create a metric that use 1 or many attribution models; for example, you can create an assist ratio that divides last touch by first touch.

It can be difficult to stay on top of your organization’s server call consumption, leading to frustration around overages. Server Call usage reporting (released Jul '18) makes it possible for you to track exactly how much of your server call commitment you’ve used at any time point in time, and will also proactively alert you when you are approaching your total commitment. The accompanying dashboard allows you to analyze where your server calls are being used, so you can fix runaway implementations or work with colleagues to scale back in places where large volumes of less-valuable data might be getting collected.

We added Time Part dimensions to Analysis Workspace out of the box. While the dimensions by themselves are informative, it's not always easy making sense of the different data points, e.g. time of day, day of week, etc. In Analysis Workspace, you can bring in these dimensions as a cross-tab table, and then visualize the data with just conditional formatting.

A time-parting "map". Hour of Day in the rows, Day of Week in the columns, with visits being plotted. All column settings have been turned of, except conditional formatting.

In the world of bots, there are good bots and bad bots. Good bots are things like feed fetchers, search engines, data crawlers and monitoring bots. Bad bots include impersonators, scrapers, hacker tools, and spammers. With our out-of-the-box IAB bot filtering & custom bot rules, you can take care of the good bots. But what about the bad bots? We conducted an analysis across a set of anonymized retail datasets and determined that bad bots account for <5% of total hits, but have a more significant impact as you move down funnel to product detail pages.

We also found that 75% of bad bots could be filtered from your data through a very simple bot segment definition:

We also recommend applying this segment + any other junk data segments to a virtual report suite, and sharing that to your end users. That way, if you ever have new bots that are identified or issues with your tagging, your segments can be updated and end users are none-the-wiser.

If you want to take bot filtering even further, the Hit Governor plugin is another option. It tracks the total number of Analytics image requests sent during a predefined rolling timeframe, and can perform additional logic as required if the that total exceeds a certain threshold. This can help you reduce server calls from inactionable data & drive improved trust in the data. Learn more.

A processing rule triggered from the plugin contextData sets 1 event & other helpful dimensions

Transaction ID Data Sources help you to connect an online experience that finished offline. With this solution, you can integrate offline data in Adobe Analytics, and fully tie that data to the online visitor profile you've collected. This level of integration allows uploaded events to be treated just like they were collected on the page. For example, you can use uploaded events in visitor segmentation, such as show me visitors that did offline event X. Use this to integrate offline CRM data from Salesforce or any other backend database that contains additional data points about an online lead.

Offline event 'Auto Sales' is used throughout the dashboard to drive deeper funnel analysis

As analysts, many questions that we get are adhoc in nature, and data does not need to be tracked long in order to be useful. This can cause you to run out of variables quickly. Some examples include: tracking various flash campaigns, capturing Marketing Cloud IDs for a brief debugging exercise, or measuring microsite engagement for a site that will be running for 2 weeks. With "Fluid (Reusable) Variables" set aside & Virtual Report Suite Curation, you can service these adhoc questions & create unique data views for each request, all while preserving variables.

In VRS, you can include your fluid variable, give it a unique name, and segment the suite down to one particular use case. For example, a temporary microsite that needs to be tracked for 2 weeks.

The Workspace landing page can sometimes be unwieldy, especially if you are creating projects daily & sharing them to/from your colleagues. To help organize it at for yourself, or your end business users, create a Table of Contents project. The project can be a mix of links to other projects, or even specific panels & visualizations within other projects. Once complete, set the project as your Analytics landing page under Workspace > Project > Set as Landing Page. Or, share the project to other users & set it as their landing page (an option when sharing).

Table of Contents project example. 6 analysis categories, each with their own set of relevant projects, panels, or viz links, along with a preview visualization.

Learn how to link to a specific panel or visualization in any project, to help when building out your table of contents. Links to full projects can be created under Share > Get Link to Project.

Internal Search is one of the few ways customers tell brands exactly what they want & need. Using advanced calculated metrics, you can measure the content requests from your customers (count of internal search terms) & hold your content optimization program accountable (expect a downward trend of this count). Also, you can use the count + search term instances to better understand which content to change & what changes to make.

Use the Approximate Count Distinct function to count number of unique items within a dimension, such as # of search terms.
The count of terms can be helpful in determining where to optimize first (which content pages). Breaking down by term & looking at "search term instances" can be helpful in determining what changes to make.

Virtual Report Suite Context-Aware Sessions allow you to define what constitutes a visit, so that it is meaningful to not only your analysis, but your business. By turning on report time processing, you allow Adobe to define the context of a visit at run-time, rather than pre-defining it to be 30 minutes. One use case of this functionality to is align Adobe Analytics with your CRM system, which may have a different definition of a visit, e.g. 20 minutes.

VRS Visit Definition setup
Additional use cases for VRS context-aware sessions

Engagement scoring is the process of assigning numerical “scores” to key digital activities. Scoring helps you understand how varying engagement levels affect conversion and customer loyalty. Scores can be setup via calculated metrics (non-permanent approach) and used throughout your analysis as a secondary success measure, and indicator of valuable revenue opportunities.

Calculated metric example for total engagement score
Engagement score event used in Marketing Channel analysis

Bonus Tip: You can take engagement scoring even further by setting up processing rules to assess scores at a visitor level. Scores can then be rolled up to create High/Med/Low engagement segments for deeper analysis.

Example Engagement Scoring processing rule for 1 activity

Custom templates are a great way to get users analyzing more quickly & helps to ensure they are following best practices defined by your organization. You can build in tables with the appropriate success metrics & calculations, as well as layer in visualizations to make the data come to life. End business users can then choose to start their analysis from one of the custom templates.

You can create templates that serve the sole purpose of being copied from as well. We like to call these 'Building Blocks' templates. Users can pull this template up side-by-side with a blank project, and copy visualizations & panels from it.

Advertising Analytics (released May '18) brings together search engine data from Google, Yahoo! and Bing with Analytics data, allowing you to do side-by-side analysis.

Combined search engine & Analytics data

Audience Analytics (released Oct '17) enables real-time segment sharing from Audience Manager to Analytics. The integration completes the handoff between solutions, and enriches customer profiles in Analytics. Audiences can then be used throughout Analysis Workspace, in Flow, Segment Comparison, or just basic freeform analysis.

Audience overlap visualized with a Venn diagram
Visitor journeys between audiences visualized with Flow

Analytics for Target (A4T) is a cross-solution integration that lets you create Target activities based on Analytics conversion metrics and audience segments. This integration lets you use Analytics reports to examine your results. If you use Analytics as the reporting source for an activity, all reporting and segmentation for that activity is based on Analytics data collection.

Ready for more content?

Visit adobe.ly/aaresources for a full list of Adobe Analytics Spark pages & other helpful resources.

Created By
Jen Lasser