How to use Adobe Analytics features for data analysis & personalization

Coupled with in-depth analysis, versatile reporting, and predictive intelligence, businesses can build better customer experiences and improve sales and marketing performances with Adobe Analytics implementation best practices.

Why implement Adobe Analytics for data-driven decision making?

In today’s digital ecosystem, an enterprise cannot just rely on assumptions and predictions while creating competitive customer experiences. Enterprises need concrete data and insights before allocating campaign spends and investing in strategies. Unlike finding a needle in a haystack, marketers need to smartly play the field by measuring the ROI of their performances and assisting enterprise leaders with data-driven decision-making. 

Adobe Analytics increases the effectiveness of your marketing campaigns with its powerful capabilities. As a business owner, if you face any of the challenges mentioned below, the myriad of Adobe Analytics features can help to overcome them. 

#1. Irrelevant data impacting business decision-making

Challenge: Without relevant and quality insights from the amassed data, business decisions will impact. To make informed decisions, the data collected must be relevant and reliable so as to derive actionable details about user behavior, marketing campaigns, and overall ROI. 

How Adobe Analytics help: 

1. 1. Multichannel data collection: Adobe Analytics offers multiple ways to collect data from various channels like mobile, web, emails, and campaigns. All this data can be compiled on a single Adobe Analytics dashboard to gain a unified view of customers and marketing effectiveness. 
   2. Custom variables: It captures the data that matters the most for business. For example, if you want to know your product bestsellers and which search terms they use when browsing products, Adobe Analytics provides you with those insights.
   3. Offline data integration: You can integrate any third-party data source to Adobe Analytics to and to gain a complete view of your marketing efforts. Using attributes from all the sources allows you to get insights about customer traits, demographic data or sales stage, etc.

#2. Compromised analysis due to lack of proper tools

Challenge: Often, organizations struggle to perform data analysis due to the lack of proper tools, processes, and people. The absence of in-depth data analysis hampers user experiences and results in higher operational costs. 

How Adobe Analytics help: 

Leveraging the several Adobe Analytics features, companies can now analyze data, study it to understand user behavior, and implement the founding to overall strategies. This includes:

1. 1. Advanced segmentation: Adobe Analytics segmentation automates data collection, storing, segmenting, and management to help you focus on deriving profits from it. This advanced Adobe Analytics feature helps you evaluate customer behavior for remarketing and leverage the insights to improve visualizations like site design, navigation, content layout, etc. It also enables you to get a comprehensive way by analyzing customers’ online and in-store experiences.
   2. Ad-hoc analysis: With the Analysis Workspace feature from Adobe Analytics tool, you can dynamically analyze data tables, visualizations, and components to create breakdowns and segments in real-time. You can also apply customizable default settings for greater conversion and create multiple reports in a dashboard without switching tabs. 
   3. Cohort analysis: You can analyze a group of people with common attributes, track them, and understand their behavior to build new audiences and improve customer experience with Cohort analysis. This helps in creating effective and budget-friendly marketing campaigns focussed around profits and improve business decision-making. 
   4. Cross-device analytics: With this out-of-the-box capability of Adobe Analytics that unifies mobile and web interactions of the customer journey to make better decisions with complete data.
   5. Customer journey analytics: It provides actionable insights for higher customer conversions through business intelligence and data science to stitch and analyze cross-channel data.
   6. Flow analysis: With the flow analysis feature, you can witness customer paths and their current journey stage on your website or app. This ensures the creation of meaningful and personalized customer journeys with different segmentations in the same report.

#3. Getting real-time insights

Challenge: Since AI and machine learning are yet to be implemented frequently to collect, measure, and analyze data, businesses encounter challenges deriving real-time insights about their processes and how to improve their customer experiences. 

How Adobe Analytics help: 

1. 1. Marketing attribution: Adobe Analytics offers a variety of attribution models to predict user behavior, leading to smarter spending decisions and delivering the right message across user-preferred channels. 
   2. Anomaly detection: It filters vast data through statistical modeling and machine learning to identify factors that impact processes. Adobe Analytics features automatically detects anomalies with clear visualizations to drive better insights faster. It can notify changes for seasonal events like black friday, the holiday season, and spring break to identify metrics and segments accordingly when used in the analysis workspace.  
   3. Contribution analysis: Coupled with Adobe Analytics feature of anomaly detection, contribution analysis allows marketers to better understand data and replace complex data with better visualizations to simplify and accelerate decision-making. Contribution analysis removes junk data to get relevant insights using AI.
   4. Intelligent alerts: Adobe Analytics lets you monitor data smartly with smart alerts when you are away and notifies you when in case of an uncertainty, for example, unusual traffic on a website.

#4. Siloed analytics

Challenge: Limited information, duplicate data, and departmental inefficiencies are the main causes of siloed analytics, which often leads to miscommunication and inefficiencies. Data silos resulted in partial behavioral views, paralyzing departments from executing effective campaigns.

How Adobe Analytics help:

1. 1. Advertising analytics: When running ad campaigns, Adobe Analytics features allow you to break down data silos and get a clear view of advertising to create data-driven ads for audiences. You can import data from search engine impressions, clicks, cost, etc., to spend effectively on ads.  
   2. Remarketing triggers: Adobe Analytics lets you take advantage of data in real-time and set up remarketing triggers to send personalized messages at the right time. Adobe Campaign and Adobe Analytics integration help reduce cart abandonment and provide action triggers for newsletter signups, email subscriptions, and more. 

#5. Lack of required skills for data analysis

Challenge: Despite having analytics teams, businesses need to interpret data effectively, while taking business-critical decisions. Companies must look for platforms that can add value to their insights and present reports through automation, artificial intelligence, and machine learning. 

How Adobe Analytics help: 

1. 1. Unique processing rules: Adobe Analytics processes business data on the server side so they do not have to rely on IT teams or manually take up the task. This also allows you to dig data in real-time without going back and creating new reports. With processing rules, your business can segment customers efficiently and meet all their needs.
   2. Advanced calculated metrics: It lets you build metrics to shape your data through your analytical creativity. For example, if you want to create a metric for ‘new visitors’ for those who visit a website for the first time. Additionally, you can use functions like mean, multiply, currency, percent, time, etc. 

How can a business effectively employ the Adobe Analytics tool?

Adobe Analytics enhances your marketing efforts and helps deliver personalized email campaigns. The several Adobe Analytics features are divided into four main categories that help a company to make data-driven decisions effectively. Some of them are: 

#1. Web Analytics

Adobe Analytics enables you to measure traffic sources, customer pathing, content efficacy, and engagement to better understand your website visitors. Hence website analytics plays an important role in business success. Adobe Analytics allows us to gain better insights of data, powerful segmentation, and visually appealing reports through Adobe Sensei integrations. It improves customer experience and engagement by avoiding poor mobile and web experiences. This shapes real-time insights that drive decisions to fulfill your business goals. 

#2. Marketing Analytics

Adobe Analytics combines collecting, organizing, and analyzing valuable data quickly, giving marketers a complete understanding of customer behavior that lets them deliver meaningful and tailored experiences. The Adobe Analytics tools like anomaly detection, customer attribution, and cohort analysis prepare businesses for ROI-driven marketing spending. And with automation, AI, and machine learning capabilities, you will have insights to analyze, visualize, share, and act on. Overall, Adobe Analytics improves visibility into the performance of marketing and advertising campaigns to engage better and convert faster.

#3. Attribution

Attribution is an excellent way of evaluating the performance of marketing campaigns, and Adobe Analytics understands it well. Hence Adobe has come up with various attribution models to help marketers make decisions on campaigns, keywords, and advertisements that meet the organization’s goals.  Adobe Analytics features analyze the marketing funnel to improve site traffic, conversion rates, and brand engagement. This also helps make intelligent decisions while investing in productive marketing activities.

#4. Predictive Analytics

Predictive Analytics helps businesses to analyze future events using data models, statistics, and machine learning. This eliminates manual marketing tasks and provides companies with important insights mined from massive datasets through machine learning and advanced statistical models. 

Leverage the power of Adobe Analytics with our certified experts

Adobe Analytics has several out-of-the box features for your business despite having an easy-to-use interface that empowers marketers to analyze data and implement recommendations. In case you need assistance with Adobe Analytics’ custom reporting capabilities, interactive dashboards, real time insights and more to make data-driven decisions, you can connect with our certified experts to explore more of its business-driven features.