Working cross-functionally
- Topics:
- Admin Tools
CREATED FOR:
- Experienced
- Admin
Transcript
Hi, I’m Abhinav Saxena. I’m an admin for Adobe Experience Cloud, a Certified Adobe Analytics Architect, and Adobe Analytics Champion for 2021. The journey of Adobe Analytics start with a good implementation. We all know the concept of garbage in and garbage in. So we have to make sure we do not put any garbage into the tool. This is why working cross-functionally with different teams throughout your organization is critical for a clean analytics instance. Adobe Analytics is an ocean with many inputs, and where various settings play different roles in massaging the data. As the owner of the tool, we have to work with business to understand their requirements and KPIs. We have to team up with IT and design partners to understand the flow, and last but not the least, we have to collaborate with reporting stakeholders to help them understand what was implemented in terms of variables and values, so that they can build their segments, calculated metrics, and reports. In this article, I share some useful tips for admins to maintain such cross-functional relationships with their stakeholders, while keeping the data integrity in check. Those steps are, first, building on a good technical foundation. Second, providing inspired leadership. Third, creating a customer driven mindset. And fourth, forming open lines of communication. I hope this helps you with working cross functionally with all the different stakeholders across your organization. Thanks and good luck. -
The journey to Adobe Analytics starts with a good implementation. We all know the saying of “garbage in, garbage out”. To eliminate a “garbage out” implementation, Admins must monitor every detail of the data put into the system. That said, the data collection strategy is influenced by many stakeholders in the organization whom an admin will have to work with day-in and day-out.
As an owner of the tool, you must work with business teams to understand their requirements and KPIs, work with IT and design partners to understand the data flow and work with reporting stakeholders to help them understand implemented variables and values for reporting. Furthermore, we also must work with EDW teams to ingest data into their systems to be widely used across the company. To add on, there are other teams who are dependent on Analytics data like Adobe Target, media campaigns, and other vendor partners.
As you can see (and already know), as an admin of Adobe Analytics, you are consistently working across organizations and teams. To maintain efficient cross-functional relationships, admins need to put on a “product manager” hat. Instead of only thinking about your own reporting/data collection needs, you must consider the product needs of the entire organization. Being an admin is not an easy role but can be made much easier with collaboration across teams.
These are some of the skills needed to work well cross-functionally:
- Technical foundation: An Admin should have a solid understanding of the technical implementation of Adobe Analytics. Admins are the middle-man between business owners and technical resources, bridging the gap of “what to measure” vs. “how to measure”. Admins need to be an active part in the solution design, based on their knowledge of the organization’s KPIs and KBOs. In order to be efficient in cross-functional collaboration, admins need to be able to converse on a deep level with engineers to establish expectations of the implementation. Based on the solution design, the admin can implement and manage the appropriate variable settings and taxonomy required. There are hundreds of details in every project and admins should be able to understand how their data set will fit into the grand scheme of things.
- Leadership: A skilled admin should have the ability to inspire confidence in the quality of their dataset. This is accomplished by implementing and maintaining Adobe best practices. Adobe best practices ensure accuracy of data collection, the usability of collected data, and ensuring actionable insights from the collected data. Additionally, passing implementation knowledge and training new users is an integral part of leading within Adobe Analytics. Admins should look to increase adoption of the tool by leading enablement and training sessions to showcase the usefulness of Adobe Analytics.
- Customer-driven mindset: An admin must have a sense of how to make the user experience better. As admins of Adobe Analytics, your customers are the stakeholders and users of Adobe Analytics. In order to create a better experience for them, ensuring cross-functional teams have appropriate access is critical. Understanding their roles and needs, you can preemptively overcome roadblocks by provisioning appropriate access from the beginning. Moreover, Admins should implement and maintain appropriate taxonomy and documentation of components and variables within Adobe Analytics. This will provide clear documentation for your cross-functional teams to review.
- Communication: Effective cross-functional collaboration requires expert communication skills. An admin must clearly articulate business questions and how they are trying to answer them. Admins should frequently request feedback from the cross-functional team and implement necessary changes to facilitate effective collaboration. Changes to the implementation can have rippling effects throughout the data flow and reporting processes. For example, a variable collection change can impact the results of a segment, which in turn can impact a report summary that is used by a business stakeholder to make a business decision. Documenting and communicating any changes made to components or variables ensures transparency of reporting impacts and helps facilitate implementation troubleshooting.
More help on this topic
Analytics
- Analytics tutorials
- Introduction to Analytics
- What is analytics
- What Can Adobe Analytics Do For Me?
- How Adobe Analysis Workspace Can Change Your Business
- It’s More Than Data. It’s Customer Intelligence
- Adobe Sensei and Adobe Analytics
- Customer Use Case - ServiceNow
- Customer Use Case - Accent Group
- Customer Use Case - The Home Depot
- Summit 2019 Super Session - Travel and Hospitality
- Summit 2019 Super Session - Retail
- Summit 2019 Super Session - High Tech
- Strategy & thought leadership
- Transitioning from other platforms
- Analytics Basics
- Customizing the UI
- Getting Help
- Analysis Workspace
- Analysis Workspace Basics
- Analysis Workspace quick intro
- Analysis Workspace overview
- Navigate the new landing page
- Start your analysis with a pre-built report
- Building a Workspace project from scratch
- Create and manage custom templates in Analysis Workspace
- Understanding how data gets into your Analysis Workspace project
- Foundational metrics in Adobe Analytics
- Component management in Analysis Workspace
- Selecting a report suite in Analysis Workspace
- View Analysis Workspace performance metrics
- Create bot reports
- Tips and Tricks
- Navigating Workspace Projects
- Data Dictionary in Analysis Workspace
- Starting your first project
- Training tutorial template
- Use folders in Analysis Workspace
- Copy and insert panels and visualizations
- Create a table of contents
- Right-click for Workspace efficiency
- Keyboard shortcuts
- Annotations
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- Use filters
- Use multi-select drop-down filters
- Real-time reports
- Using Panels
- Using Tables, Visualizations, and Panels in Analysis Workspace
- Quick Insights Panel in Analysis Workspace
- Using the Attribution IQ Panel
- Media Concurrent Viewers Panel in Analysis Workspace
- Media Playback Time Spent Panel
- Using Drop-down Filters
- Using Panels to Organize your Analysis Workspace Projects
- Choose segments for a panel
- Multiple Report Suites in Analysis Workspace
- Next/Previous and Page Summary Workspace Panels & Reports
- Understanding attribution panel and lookback windows
- Building Freeform Tables
- Understand your data–freeform tables
- Use the left rail to build freeform tables
- Easy drag and drop to blank projects
- Work with dimensions in a freeform table
- Work with metrics in a freeform table
- Row and column settings in freeform tables
- Freeform table totals
- Use the freeform table builder
- Right-click for workspace efficiency
- Reorder static rows
- Use Attribution IQ in freeform tables
- Cross-sell analysis
- Freeform table filters
- Time-parting dimensions
- Visualizations
- Visualization types and overview
- Visualization use cases
- Data visualization playbook
- Getting data into visualizations
- Using component drop-downs in Workspace
- Area and area stacked visualizations
- Bar and bar stacked visualizations
- Bullet graph visualization
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- Unlocking insights with histograms
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- Summary number and summary change visualizations
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- Text visualization
- More than words - Using text visualizations and descriptions
- Scatterplot visualization
- Treemap visualization
- Venn diagram visualization
- Use the cumulative average function to apply metric smoothing
- Flexible layouts
- Changing the scale/axis on visualizations
- Dimension-graph live linking
- Set the granularity for visualizations
- Link inside or outside of your project
- Customize visualization legends
- 100% stacked visualizations
- Table and visualization data source settings
- Build a time-parting heatmap
- Analyzing Customer Journeys
- Applying Segments
- Apply segments to your Analysis Workspace project
- Apply ad hoc segments
- Use different Attribution IQ models with segments
- Choose segments for a panel
- Use segments as Dimensions in Analysis Workspace
- Use segments to limit data in Analysis Workspace
- Quick segments in Analysis Workspace
- Building Customer Journey Segments
- Building Customer Journey Segments - Part 2
- Metrics
- Dimensions
- Calendar and Date Ranges
- Curate and Share Projects
- Attribution IQ
- Using Cross-tab Analysis to Explore Basic Marketing Attribution
- Adding side-by-side comparisons of Attribution IQ Models
- Attribution IQ in Calculated Metrics
- Using Attribution IQ in Freeform Tables
- Using the Attribution IQ Panel
- Using different Attribution IQ models with segments
- Algorithmic Model in Attribution IQ
- Custom Look-back Windows in Attribution IQ
- Cohort Analysis
- Cohort Analysis in Analysis Workspace
- Understand your data–Cohort Tables
- Overview of Cohort Tables
- Cohort Table Settings
- Churn Analysis with Cohort Tables
- Cohort Analysis Using Any Dimension
- Latency Analysis with Cohort Tables
- Calculate Rolling Retention in Cohort Tables
- Use Cohort Analysis to Understand Customer Behavior
- Voice Analytics
- How to Manage and Track Your Voice Assistant App Data
- Understand Differences Across Voice-Enabled Devices
- Finding Opportunities To Increase Engagement for Voice Apps
- Reducing Error Rates and Improving Success Rates in Your Voice App
- Understand User Behavior on Voice Assistants
- Understanding the User’s Voice Journey
- Analysis Workspace Basics
- Administration
- Key Admin Skills
- Creating an empowered community
- Simplify and spend less time training users
- Getting the Right People on Your Analytics Team
- Gaining a seat at the table
- Telling impactful stories with data
- Translating Adobe Analytics technical language in a non-technical way
- Working cross-functionally
- Are you asking the right questions?
- Admin Tips and Best Practices
- Download the implementation playbook
- Audit your data dictionary
- Create standardized naming conventions
- Create standardized code templates
- Create basic videos and training
- Create an internal Adobe Analytics site
- Use a global report suite
- Create a news & announcements project
- Drive success with executive summary dashboards
- Create operational dashboards
- Company Settings
- User Management
- Manage Report Suites
- Configure general account settings
- Customize calendar settings
- Configure paid search detection
- Set up marketing channels
- Create marketing channel processing rules
- Manipulate incoming data with processing rules
- Configure traffic variables (props)
- Configure traffic classifications
- Configure hierarchy variables
- Configure events and variables
- Configure conversion classifications
- Configure list variables
- Configure finding methods
- Set internal URL filters
- Configuring zip and postal code settings
- Enable the timestamp optional setting
- Configure bot rules in Analytics
- Data Governance and GDPR
- Traffic Management
- Logs
- Key Admin Skills
- Implementation
- Implementation Basics
- Experience Platform Tags
- Implement Experience Cloud solutions in websites using Tags
- Basic configuration of the Analytics extension
- Configure library management in the Analytics extension
- Configure general settings in the Analytics extension
- Configure global variable settings in the Analytics extension
- Use custom code in the Analytics extension
- Use a data layer to set variables
- Use doPlugins and implementation plug-ins
- Configure easy download link tracking
- Configure easy exit link tracking
- Prepare Tags for your Analytics implementation
- Create data elements for the Analytics implementation
- Create a global page load rule
- Validate the global page load rule
- Create rules for special pages
- Create rules for success events
- Publish Tags libraries to stage and production
- Using JavaScript
- Components
- Segmentation
- Segment builder overview
- Finding and creating segments
- Rolling date ranges in segments
- Segment comparison in Analysis Workspace
- Segment containers
- Segment management and sharing
- Applying segments in Analysis Workspace
- Using segments as dimensions
- Using segments to limit data
- Differences between the segment builder and quick segments
- Sequential segmentation
- Before/After sequences in sequential segmentation
- Segmentation on distinct dimension counts
- Dimension models in segmentation
- Use ‘equals any of’ in segmentation
- Analytics Insider Webinar - Customer Segmentation Strategies
- Now just wait a segment… Using segmentation to discover new insights
- Calculated Metrics
- Calculated metric builder overview
- Calculated metrics - implementation-less metrics
- Calculated metrics - segmented metrics
- Calculated metrics - functions
- Approximate count distinct function in calculated metrics
- Quick calculated metrics in Analysis Workspace
- Manage your calculated metrics
- Attribution IQ in calculated metrics
- Use dimensions in calculated metrics
- Take your data analysis to the next level with calculated metrics
- Classifications
- Virtual Report Suites
- Activity Map
- Segmentation
- Additional Tools
- Exporting
- From the UI
- Data Warehouse
- Data Feeds
- Report Builder
- Upgrade and reschedule workbooks
- Add Segments to Multiple Requests at Once in Report Builder
- Anomaly Detection in Report Builder
- Edit Metrics across Requests
- Using Report Builder to learn the Adobe Analytics API
- Get started with Report Builder
- Schedule a Report Builder request
- Use Report Builder advanced delivery options for Power BI
- Integrations
- Experience Cloud
- Audience Manager
- Target
- Adobe Advertising DSP
- Configuring Advertising Analytics
- Implementing tracking templates into search engines
- Introduction to the Adobe Advertising DSP integration
- Create a Pre-launch campaign analysis
- Report on Advertising DSP marketing channels
- Create Analytics site journey profiles
- Create Analytics segments for activation and reporting
- Create Advertising DSP alerts with Adobe Analytics
- Create Analytics custom metrics with Advertising DSP data
- Create Advertising DSP site entry reports
- Create Advertising DSP dashboards
- Ad Hoc Analytics
- Power BI
- Magento
- Data Science
- Vertical-Specific
- Media Analytics
- Mobile App Analytics
- APIs
- Analysis Use Cases