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Adobe Analytics Tutorial

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by Madhuri Yerukala
Last modified: August 23rd 2021

Digital experiences define today's world. Now we have more technology options than ever before, and competition between them is at its highest. The success of a business merely depends on data and insights.

Companies from all sectors have realized this fact and started investing in digital analytics for their data services. Adobe Analytics is a best-in-class tool in the digital analytics market, which rose in a staggering space in recent years. It lets you analyze the data and provide insights that drive business.

This Adobe Analytics Tutorial is designed for beginners and professionals looking to master Adobe Analytics basics.

Adobe Analytics Tutorial - Table of Content 

What is Adobe Analytics?

Adobe Analytics is an industry-leading analytics solution that enables you and your team to become data-driven. It allows you to capture data from almost every device connected to the web to extract insights. You can also onboard any offline data to originate data capture online.

Analysts around the world use this tool to discover insights from their data for business. APIs of Adobe Analytics offers limitless ways to integrate customer data into the business process. You can gather, analyze, and report on everything customers do through web analytics using Adobe Analytics. It's a part of the Adobe Experience Cloud.

Do you want to get certified and build your career in  Adobe Analytics? Then enroll in "Adobe Analytics Online Training" this course will help you to achieve excellence in this domain.

Why Use Adobe Analytics?

Becoming familiar with Adobe Analytics will expand your analytical skills. Adobe Analytics' new features and tools will enrich your analytics knowledge base. With Adobe Analytics for Target integration, you can reduce IT redundancies and marketing silos and drive efficiencies and ROI.

Adobe Analytics Features 

Adobe Analytics is named as a Leader in Gartner Magic Quadrant and Forrester Waves for analytics. Let's take a look at what features make it stand against its competitors.

  • Multichannel data collection: Adobe Analytics allows you to capture data virtually from any source (web, email, client-server apps, mobile devices, etc.)
  • Offline data integration: You can integrate offline data as well.
  • Tag management: It's easy to manage tags with Adobe Analytics and provides various tools to collect and distribute data across digital channels.
  • Advanced Calculated Metrics: These metrics can be created and segmented to any report for which you add metrics.
  • Cross-device analytics: It helps to understand the customer journey better by unifying both web data and apps as a single source.
  • Advanced segmentation: It allows you to uncover critical segments that drive the company's KPIs.
  • Anomaly detection: Machine learning and statistical modeling allow you to identify unexpected anomalies in your data.
  • Intelligent alerts: You can create and manage alerts.
  • Shared Audiences: Based on user behavior, you can create and manage audience segments and seamlessly share them to the Adobe Experience Cloud to activate other Experience Cloud products.
  • Third-party integrations: Using drag and drop UI and prebuilt APIs, you can integrate Adobe Analytics data connectors with third-party apps.

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Now that you understood the importance of Adobe Analytics and its features. Next in this Adobe Analytics tutorial blog, Let's look at some evaluation criteria when selecting a marketing analytics solution.

Explore - Adobe CQ5 (AEM) Interview Questions

What makes Adobe Analytics a leading analytics tool?

The below table shows the differences between Adobe Analytics and other analytics tools.

Basis of comparison Adobe Analytics Other Analytics Tools
Collect and Measure Adobe Analytics allows you to collect data from a wide range of sources and access this data every time Data collection is possible only through limited sources.
Predict and Model Uses predictive algorithms, machine learning models, and built-in statistics to make data accessible. Their data science is limited and challenging for everyone to use and act on data
Share and act Offers integration with best in class products Integration with other digital services is limited.
 

Next in this Adobe Analytics tutorial blog, let's understand how to implement Adobe Analytics.

Adobe Analytics Implementation

Adobe Analytics needs code within your website, application, or other application for sending data to the data collection servers. Based on your organization's needs and platform, there are numerous ways to implement this code. 

The below listed are the most popular methods utilized for implementing Adobe-Analytics:

  1. Adobe Experience Platform Launch
  2. Dynamic Tag Management
  3. Legacy JavaScript
  4. Mobile SDK

Benefits of Adobe Analytics

The significant benefits of using Adobe Analytics are:

  1. You can dig deeper into web analytics. Using advanced technology, Adobe Analytics allows you to go beyond visits, bounce rates, and page views to find customer insights that drive the bottom line. 
  2. Adobe Analytics allows you to integrate data virtually from any channel. Therefore, you can analyze data in real-time to understand your customers on a whole new level.
  3. With Adobe Analytics, you can create predictive insights.
  4. Adobe Analytics enables you to see your full conversion funnel. You can optimize your goals using Analytics conversion metrics.
  5. Adobe Analytics is perfect in cross-channel attribution. It helps you to understand the impact of every customer through paid, owned, and earned channels.

Till now, we have discussed the ways to implement Adobe Analytics and its benefits. Next in this Adobe Analytics tutorial blog, Let's move forward and discuss the top tools of Adobe Analytics. 

Adobe Analytics Tools 

This section discusses the recommended tools in Adobe Analytics -

#1. Analysis Workspace

It's a dynamic tool that serves both analysis and data visualization by allowing you to pull all the data you need. By utilizing the drag and drop interface, you can craft your analysis, build projects, create visualizations to bring data to life, and develop complex segments and metrics. Adobe recommends an analysis workspace for most reporting needs.

#2. Ad Hoc Analysis

This tool enables you to perform instantaneous, advanced analysis on web activity. Allows you to identify high-value customer segments with complete real-time visitor information.

#3. Reports & Analytics

A tool with dozens of prebuilt reports. Mostly, preferred by beginners to navigate pre-built reporting. You can set up targets, view bot reporting, access real-time data in UI, and more through this tool.

Till now, we have seen how Adobe Analytics plays a crucial role in the analytics world. Continuous learning and developing skills will give you a better position in your field. Next in this Adobe Analytics tutorial blog, Let's look into the types of certifications available for Adobe Analytics.

Adobe Analytics Certifications

You might be wondering what the different types of Adobe Analytics Certifications available are and what one should opt for. To put an end to all your doubts, let's discuss the adobe analytics certifications available for different roles based on industry standards.

1. Adobe Certified Master - Adobe Analytics Architect

The audience who can go for this certification are Solution Architects Technical Manager, Data Architect, Analytics Engineer, and Multi Solutions Engineer

2. Adobe Certified Expert - Adobe Analytics Business Practitioner

The audience who can go for this certification is Digital marketers, Data analysts, Business analysts, Business consultants, Web analysts, Media/marketing analysts, UI analysts, and Conversion/optimization specialists.

3. Adobe Certified Expert - Adobe Analytics Developer

The audience who can go for this certification is Implementation Specialists/Engineers, Developers, and Architects.

Job roles available for Adobe Analytics

Some of the in-demand job roles in Adobe Analytics are listed below:

1. Adobe Analytics Architect 

An analytics Architect's role involves translating business requirements into technical specifications, designing data architecture to map needs, and understands the interdependency between eCommerce systems, platforms, and digital marketing life cycle.

2. Adobe Analytics Business Practitioner

The role of a Business Practitioner is to help clients understand how to extract or pull the information they want, and which are contextually relevant.

3. Adobe Analytics Developer

Adobe Analytics developers should be familiar with various adobe analytics tools and Front-end web development environments.

Future of Adobe Analytics

As we know, many top companies, like Amazon, Microsoft, etc., are using Adobe Analytics to lead their business. Adobe Analytics is a popular analytics solution used by organizations because it possesses the features that every organization envisions.

Let's discuss some essential points to know why Adobe Analytics is a futuristic one.

  • According to Forrester, Adobe Analytics offers you the chance to get triple-digit ROI.
  • Gartner named Adobe Analytics as a leader for marketing analytics.  

We can expect the integration of adobe analytics even further to satisfy an organization's needs in the long run. Now it's holding a significant market share in the analytics space. We all know that Adobe Analytics often comes with industry demanded features that made it an active player in the Analytics domain. Its flexibility and easy adoption feature always keep it on the top of the market.

Conclusion:

We can clearly see that Adobe Analytics is multiplying with a broad range of possibilities to dive deep into data. We hope this blog has given you a clear idea of what Adobe Analytics is and its popularity. I hope this Adobe Analytics tutorial has helped you in educating on about Adobe Analytics! Happy learning! 

About Author

author
NameMadhuri Yerukala
Author Bio

Madhuri is a Senior Content Creator at MindMajix. She has written about a range of different topics on various technologies, which include, Splunk, Tensorflow, Selenium, and CEH. She spends most of her time researching on technology, and startups. Connect with her via LinkedIn and Twitter .