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# System prepended metadata

title: Crawl

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# Crawl

We propose incremental imporvements to today's Fusion platforms, to enhance offer prioritization, serving, and reporting.


- Current state Inventory activities: 
	- Understanding of what's being tracked today (internal need)
	- Understanding taxonomy for ad units and native styles
	- Identifying reporting redundancies or gaps
	- Establish access to Adobe Analytics data (challenging dependency)
	- Broaden distribution of GAM reporting, and create more shared insights
	- Identify highest performing offer slots and creatives.  
- Applying GAM Implementation Updates
	- Reprioritization of offer serving & reporting strategy
		- how we can tweak our naming conventions to support more meaningful data/insights
		- The "what" and the "where".  Today, the Where is not being accurately identified
			- Solution:  change the Ad Unit to correctly inform the Where
			- This will provide enhanced reporting for the ads we serve, telling us precisely where each offer is served
	- Migration and re-tagging activities may be required, adding targeting to any existing campaigns **[LIAM: tie to business value]**
		- we may want to consider making this change exclusively for Fusion 2.0
- Connecting our offer measurement systems:
	- Establish privacy compliant process to associate offer interactions across GAM and Adobe 
- Author a Fusion Tag Manager integration evolution plan, to optimize our systems down the line
   


**Consideration**:  Leverage Fusion 2.0 build as a prototype for Marketing Placements implementation.  




# Walk 

- Integration of GAM and Adobe Analytics data 
    - value: support for building segments 
	- [Google documentation on pulling Adobe Analytics data into GAM](https://support.google.com/searchads/answer/7674588?hl=en&ref_topic=7670432)
	- [Adobe documentation on pulling Google and Bing data into Analytics. ](https://docs.adobe.com/content/help/en/analytics/integration/advertising-analytics/advertising-analytics-workflow/aa-report-ad-data-an.html)
	
	- activity: understanding Citi's current state DMP capabilities and segmentation support
	- goals: 
        - data flow from google to adobe
        - data flow from adobe to google
        - leveraging Citi's DMP


- Addition of Floodlight tags to track end to end user journeys and conversions 
	- [DFA Data Connector for Adobe Analytics](https://docs.adobe.com/content/help/en/analytics/import/dataconnectors/dfa/dfa-data-connector-analytics.html)
	- Manual strategic placement process (eg: addition of PageView tag for a modal presentation)
	- Tags need to be deployed for each new campaign
	- Ensighten is in use today in CRS (Shiva?)
	- Use of Citi's own tag manager is recommended, to expedite approval and optimize client side load
	- It's essential to design with simplicity in mind, to support this scaled, repeated process
- Leverage behavioral analytics
	- Enable heat-mapping tool (Crazy Egg, Content Squared, Adobe Activity Maps)
	- Dependency:  Update App Measurement version (need 1.6 or higher to support Adobe Activity Map)


- We should aspire to enhance Fusion's Tag Manager integration **[foundational activity]**
    - Walk: Establishing a TM evolution plan
    - Value: On a high level, a Tag Manager organizes all of the marketing and site-side tags and data being tracked by any systems (floodlight, adobe analytics) into a single solution
    - Note: P1T Taag team does not currently manage CRS's tag management solution.  CRS utilizes its own separate Ensighten license.  One downside is that this limits our visibility **[LIAM: please validate this statement]**  
    - Site-side adobe analytics is handled separately from Ensighten in Fusion today
    - Goal: consolidate all tracking and measurement into Fusion's Tag Manager.  Establish alignment of our systems and consolidated administration
    - Notable benefit: enhanced site speed, which can improve site speed, quality score, and organic search
    - speed to market would be vastly improved with updated Ensighten utilization


# Run

- Adobe Target integration, to support split testing for page optimization
    - This enables testing of alternative layouts for pages which can have a corresponding effect on marketing performance
    - Allows limited testing of new ideas, e.g. the "pencil" ad design or other new creative items
- Addition of Floodlight tags on Partner properties (eg Best Buy Thank You page) to support whole-jounrney tracking
    - This final step of the purchase journey would give us full visibility into the customer journey from ad display to eventual purchase (or other) decision
- Programatically pass data from the funnel back into GAM for audience generation and into DBM to enhance Citi's customer profiles
    - This would create additional data points for targeting offers (bar and promo codes) and defining user segments
	
