Anshika Agarwal
Digital Analytics Evangelist | Digital Strategy Consultant | Data-Driven Decision Maker

FAQ - Analytics


Google Analytics 360 vs Adobe Analytics

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
Strategy, Implementation, Optimization and Training

Tag Management

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:
This guide leads you through the following steps to implement Analytics using DTM:

BigQuery sounds big and query full !

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 !

Quick facts:

  • SIMPLER TO USE
  • COMES FREE WITH GOOGLE SUITE – (you will pay per query that you run and much more)
  • Easy Integration with GTM, data studio and other third party tools
  • Visualize data with Web UI, command line tool or BigQuery Restful API
  • A simple way to generate valuable datasets using BigQuery for re-marketing purpose and content optimization
Reference

Adobe Analytics FAQs and fun

1. eVars — These are conversion variables, used to store success events in to SiteCatalyst. Example: Conversions. Campaign conversions are measured with eVars
Props — S.Prop: Are used to count number of times certain metrics are sent to SiteCatalyst data tables. Metrics like Visits, Unique Visitors, Page views etc.
Events — Events or success events are the desired actions or goals that occur on your site, like filling up a form, or a web application

2. The number of sessions within a given time period. A visit is defined as a sequence of consecutive page views without a 30-minute break, or continuous activity for 12 hours. They most commonly consist of multiple image requests, however visitors that bounce can consist of a single page view.


3. Adobe started with Adobe Tag manager, went on acquiring omniture to get hands on DTM (Dynamic Tag management ) and now to compete with many other analytics tools – we have the new Adobe LAUNCH

4. Segmentation is a very cool property to be used in Adobe to filter and convieneielty get hands on the required data, there is a segment mamager to control access for the users

5. Adobe had number of reporting UIs, adobe ad-hoc reporting, the regular reporting and analytics tool and now mostly Adobe Workspace

What is a Data Layer?

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

Example code:
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 vs Adobe Analytics Workspace

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.