Adobe Analytics

Adobe Analytics allow us to blend, combine, and dissect data from every digital touchpoint throughout the customer journey. Through comprehensive analysis, adaptable reporting, and predictive insights, you gain the foundational understanding necessary for crafting superior customer experiences.

Adobe analytics speeds up the organization and preparation of data with the assistance of Adobe Sensei. You receive robust segmentation and user-friendly visualizations of your website data. Moreover, It has the capability to effortlessly curate all of this, enabling anyone within the company to uncover their own insights, thus freeing us to focus on the in-depth data science tasks for which we were hired.

Adobe Analytics is a specific web analytics solution offered by Adobe. It is important to understand things around web analytics.

Web Analytics Features

Web analytics is a method used to analyze visitor behavior on our website or mobile application, providing the following insights:

• It furnishes us with data regarding the number of unique and returning visitors, traffic sources, sessions, etc., visiting our websites on a daily basis.
• We can gather data on conversions, which represent the achievement of an end goal, such as placing an order, adding to cart, or completing a blog.
• Insights also encompass the most viewed pages or products, enabling us to generate a report that reflects current market trends while providing real-time analysis.
• Additionally, we can capture visitor behavior, the duration of their visit, and the exit point where they lose interest on our site.
• Web analytics platforms offer features to track e-commerce transactions, including revenue, average order value, product performance, and shopping cart abandonment rates.
• Web analytics tools allow segmentation of website visitors based on various criteria such as demographics, geographic location, device type, referral source, or behavior. This segmentation enables targeted marketing and content personalization.
• Some web analytics tools, like Google Analytics or Adobe Analytics, offer real-time reporting capabilities, allowing us to monitor live website activity and quickly identify trends or assess the impact of marketing campaigns.
• Web analytics tools also offer specialized features for tracking and analyzing mobile visitors’ behavior, including mobile app usage and in-app events.
• Furthermore, they enable the creation of customized reports based on gathered data.

Common Terminology in Web Analytics

Before delving into Adobe Analytics, it is essential to grasp below common terminologies used in web analytics:

New visitor: First-time user accessing the website.
Page views: Total number of pages visited by users.
Click: Interaction with an element on the website.
Audience: Group of individuals visiting the website.
Traffic: Flow of visitors to the website.
Impressions: Number of times an ad or page is viewed.
Content: Information displayed on the website.
Conversion rate: Percentage of visitors completing a desired action.
Entry Point: Starting location of a visitor’s journey on the website.
Exit: Last page or action before leaving the website.
Engagement: Level of interaction and involvement of users.
Metric: Measurement used to track website performance.
Bounce rate: Percentage of single-page visits.
Conversion: Desired action completed by a user.
Session: Period of time a user is actively engaged on the website.
Acquisition: Process of gaining new visitors or customers.
Analytics: Analysis of data to gain insights into website performance.
Campaign: Planned series of activities to achieve specific goals.
Funnel: Stages through which visitors pass before conversion.
Landing page: Initial webpage visited by users.
Paid traffic: Visitors acquired through paid advertising.
Account: User profile or account for accessing the website.
Attribution: Assigning credit to various marketing channels.
Channel: Platform or source driving traffic to the website.

Types of Analytics

Adobe Analytics provides a comprehensive suite of tools and features for web analytics, marketing analytics, attribution, and predictive analytics, helping businesses gain valuable insights into their digital activities and optimize their strategies for success.

Web Analytics: Web analytics involves analyzing website data to understand visitor behavior, traffic patterns, and website performance, helping businesses optimize user experience and achieve their goals online.

Marketing Analytics: Marketing analytics focuses on analyzing marketing data to evaluate the effectiveness of marketing campaigns, understand customer behavior, and optimize marketing strategies to drive better results and ROI.

Attribution: Attribution is the process of assigning credit to various marketing channels and touchpoints that contribute to a conversion or desired outcome, helping marketers understand the impact of their marketing efforts and allocate resources effectively.

Predictive Analytics: Predictive analytics uses historical data and statistical algorithms to forecast future trends, behaviors, or outcomes, enabling businesses to make data-driven decisions, anticipate customer needs, and optimize strategies for better performance.

Adobe Analytics Pre-requisites

Before commencing analytics development, it is imperative to thoroughly comprehend the client’s business objectives.

The end goals of analytics projects may vary significantly depending on the nature of the business, its industry, target audience, and overall strategic direction. By gaining a deep understanding of the client’s business, including its products or services, target market, competitive landscape, and unique challenges, analytics developers can tailor their approach and solutions to effectively address the specific needs and objectives of the client. This comprehensive understanding ensures that the analytics development process is aligned with the client’s overarching business goals, maximizing the value and impact of the analytics solution implemented.

Below are the pre-requisites documents developer need to have before starting Adobe analytics development:

KBR (Key Business Requirements)

KBRs are the essential needs and objectives that a business wants to achieve through its digital presence. These requirements are often defined at the outset of a project or initiative and serve as the foundation for setting up analytics tracking and reporting in Adobe Analytics. Examples of KBRs might include increasing website traffic, improving conversion rates, or enhancing user engagement.

KPI (Key Performance Indicator)

KPIs are specific metrics or measurements used to evaluate the performance and effectiveness of a business or marketing strategy. KPIs could include metrics such as website traffic, conversion rates, average order value, bounce rates, or customer retention rates. By tracking KPIs, businesses can monitor their progress towards achieving their KBRs and assess the success of their digital initiatives.

Below are the examples of some of the KPI’s

Sales Key Performance Indicators (KPIs) encompass critical metrics such as overall sales performance, win ratio, and the number of subscriptions acquired. These indicators serve as benchmarks for evaluating the effectiveness of sales strategies and the attainment of revenue goals.

Marketing KPIs include metrics like qualified leads generated, conversion rates achieved, and the growth of social media followers. These metrics provide insights into the success of marketing efforts in attracting potential customers, converting them into paying customers, and expanding brand reach through social media channels.

Product management KPIs gauge various aspects of product performance and customer satisfaction. These metrics include the product engagement rate, the Net Promoter Score (NPS) derived from customer feedback, customer retention rates, and the frequency and nature of customer complaints. Monitoring these indicators enables product managers to identify areas for product improvement, assess customer loyalty and satisfaction, and address any issues or concerns promptly to maintain a positive brand image.

BRD (Business Requirements Document)

A BRD is a formal document that outlines the objectives, scope, and specifications of a project or initiative. BRD include details such as the business goals and objectives, key performance indicators (KPIs) to be tracked, data collection requirements, reporting needs, and any other relevant information. The BRD serves as a roadmap for implementing Adobe Analytics tracking and reporting to meet the business’s needs and objectives accurately.

SDR (Solution Design Reference)

Now, it is the right time to create SDR (Solution Design Reference) document once we have KPI, KBR and BRD documents. SDR serves as the blueprint for business requirements and data collection design for analytics on your digital properties. This document acts as the source of truth for your analysis solution. In simple language, it is a document having config, requirements, variables map as mapping of requirements with evars and variables, report suites.

Please find link for sample SDR document for reference. We will discuss and try to understand everything about SDR in upcoming blog.

Note: It is important to review KPI’s, KBR, BRD and SDR documents on the regular basis.