While working on both the tools and several more – I have had a rocky time explaining which on one is better or which might be the best one.

The answer is never too real or right on point, there are several reasons to choose one from the other like PRICING, EASY THIRD PARTY INTEGRATIONS, CUSTOMER SUPPORT, EXTRA DATA STORING VARIABLES, MORE IMPORTANTLY WHAT IS THE BEST SOLUTION ALLIGNED TO A COMPANY’S MEASUREMENT PLAN.

Quick points help through some general questions while choosing your tag management solution.

	Adobe Analytics	Google Analytics
Reporting Interface & Tools	Adobe Workspace and general reporting tool. Adobe generally needs an expertise to run through the reports	Google has recently introduced Google Data Studio and mostly the UI is easier to scroll and pick and drop elements of use
Variables/Dimension/Metrics	Traffic, conversion and success events. Very clearly defined information in terms of dimensions and metrics	Hit, product, sessions and user scoping. Google works on creating custom variables to make it more powerful
Data Connectors	Large collection of connects though some of them might be stuck due to multiple security locks from Adobe	Google gives a pretty interesting and robust collection of connectors and APIs and is easier in terms of sampler connections
Attribution Modelling	Adobe wants you to pay more for attribution model and funnel marketing	Google has one of the best attribution modelling system with 360 providing high level models to fit multiple business requirements.
Pathing and Funnels	Adobe has very in depth reporting as per pathing for previous flow reports, next flow reports and full flow reports.	Google has basic information in terms of pathing and flow data dividing it by dimensions and metrics, good point for Google to work on.

Work with what works for you and try the SIOT plan for adoption of an Analytics Tool

Tag management is a concept that was born out of the increasing need for more agile marketing measurement and tracking ability. Managing and making changes to tags can be tedious and involve unnecessary developer engagement.

A tag, in this case, is simply another name for a piece of data-collecting code that is inserted on every page of the website that is supposed to be tracked..

These tags often collect visitor behavior information, user navigation values and persons data for personalization. Simple values like trip category, country region, cost of a product, whether a pdf was downloaded or printed..

The real star of tag management, however, is something called “the data layer” — the behind-the-scenes data that drives customer interactions in web, mobile and other digital channels.The data layer resides between the application layer, comprised of various mission-critical digital solutions, and the experience layer that users interact with.

Why do we need a Tag Manager solution:

• You can track anything you want to
• Mistakes won’t impact your website
• Easy to use & centralised
• You can transfer your data to other platforms

Google Tag Manager Tracking plan:

• Create a measurement plan
• Determine tracking requirements
• Do Tag Audit of your live website
• Create Solution Design Documentation
• Do Tag Deployment Planning
• Setup Google Tag Manager Account
• Install GTM container tag on the staging website
• Create, test and publish tags on your staging website
• Install GTM container tag on the live website
• Create, publish and test tags on the live website
• Do tag audit of your live website

Checkout this article for much more

Adobe DTM implementation plan:

• Create a web property.
• Configure your hosting options.
• Add header and footer code to each managed page.
• Add the Adobe Analytics Tool.
• Create data elements, rules and conditions, and actions.
• Publish tools and rules to the production server.

BigQuery is a fully managed, massive scale, low cost enterprise data warehouse on top of Google’s compute storage and network infrastructure. It uses familiar SQL queries optimized for massive public and private datasets.

Traditional queries can take hours to run on traditional DW infrastructure. BigQuery allows any end user to be apart of the data science effort at their company. Users can self service datasets without a DBA. Run adhoc queries, aggregate queries across extremely large datasets. It takes very less time (after all its GOOGLE) and run queries for massive datasets or raw data pulls.

IT CAN TAKE LOT OF TIME SOMETIMES !

Reference

A Data Layer is a JavaScript object or variable that stores and sends information from your site to a Tag Manager (later that data is transferred to other tools, like SiteCatalyst, Google Analytics). In other words – it’s like a virtual layer of your website which contains various data points and measurement values.

Data Layer in GTM

1. To gather important pieces of information

2. To create much advanced triggers inside DTM

window.dataLayer.push({
    'formLocation': ‘footer’,
    'event': new_subscriber
});
                        

Data Layer in DTM

digitalData.page={
    pageInfo:{
        pageName:"Category:Technology",
    },
    category:{
        pageType:"category",
        primaryCategory:"technology",
        subCategory1:"n/a",
        subCategory2:"n/a"
    }
}
                        

Google Data Studio	Adobe Analytics Workspace
Google Data Studio is a highly usable, approachable dashboard program to ingest and analyze/visualize data and information. It offers a number of templates to organize and present material in a logical fashion.	Again, learning how to use the system is difficult. It is nearly unusable if you haven't received training, and training from Adobe is EXTREMELY expensive
Adobe Analytics has allowed us to quickly spot performance issues and correct them. This has allowed us to lessen the impact of these issues.	Once the reports are set up, this definitely saves time on the regular reporting deadlines (monthly, biweekly, etc.) Sometimes simple data translation in GDS in tough and time consuming.
The ability to segment and run breakdowns/correlations/subrelations provides access to a great deal with granularity in reporting	The limit of data points on a page can be challenging when trying to bring in a lot of different metrics - for example, processing of dome data can be an issue, addition of new metrics can cause blockers.
A free tool with many reporting options without technicalities is always a good side asset	It comes with Adobe Analytics Suite so good to try
Google Data Studio is still building on lot of connecting elements but for the time being it is a great help to create some great maps, charts and graphic insights.	Adobe has levels of connectors and integrating with third party tools.