Adobe Analytics Moving from data ► to insights ► to powerful customer experiences Author: Sue Murray, GM Celerity IS, Inc.
INTRODUCTION
Adobe Analytics gives you the ability to mix, match and analyze data from any of your digital points in the customer journey. With in-depth analysis, versatile reporting, and predictive intelligence, you get the insightful foundation needed to build better customer experiences. It serves to stitch together cross-channel data to capture a richer customer story that you can quickly act on.
An application such as Adobe Analytics is essential due to the high mobility of today's consumers. We use wearables, are immersed in the internet of things, cruise in connected cars and watch TV through gaming consoles or multi-task with our phones, iPad, and media streaming services. This requires organizations to create a seamless experience and to deliver consistent messaging no matter what device the customer is on. Delivering the best, most successful communications however, means an organization must have easy access and visibility to the data created by those actions.
Adobe Analytics is one of a handful of robust applications that can support the business needs to access and understand all the available information you now have. A lot of very large organizations use the platform such as Apple, United Healthcare Group, Phillips, and CVS. But while 37% of Adobe Analytics customers are organizations with over 10,000 employees, approximately 47% of Adobe Analytics customers have between 1-1000 employees, making it also a fit for small to midsize companies. The industry verticals where Adobe Analytics has been installed in the most include Retail, Manufacturing, Fi-Serv, Professional Services - encompassing 60% of all implementations. From a country-use perspective, over 56% of Adobe Analytics implementations are within the USA.
The primary benefits of Adobe Analytics can be summarized in the following seven areas:
COMPARISON OF ADOBE ANALYTICS TO GOOGLE ANALYTICS
Adobe Analytics and Google Analytics (GA)are two of the leading analytics platforms available on the market. They each have their own strengths and weaknesses, but below are some of the primary differences between the two:
Comparison of Adobe Analytics to GA in Relation to: Price, Setup, Data and
Reporting
Pricing:
GA4 is free until your website requires more custom event parameters or user properties. When you exceed the quota for GA4, you need to move to GA 360 with a hefty price tag.
On the other hand, Adobe Analytics has a handsome price tag from the start, and enterprises are the platform's typical target audience.
Setup:
GA has already-made home page and pre-made reports to start. You can jump right into your data and start investigating. Setup doesn't require that much knowledge of the platform itself.
Adobe Analytics is a bit more complex. There aren't ready-made views, requiring you to build reports themselves. This means your users need to be more data-oriented & data-mature.
Reporting:
Home pages are customizable in both GA & Adobe Analytics, but the Report Builder in GA is limited in comparison to Adobe Analytics.
Adobe Analytics' custom report writing is much more flexible and customizable to add data, columns, and colors.
Data:
GA is good for less established, smaller companies that won't need a lot of data customization or sophistication and require only direct views of quantitative data.
Adobe Analytics is better for more established companies that know the data they have and what they want to do with it - and they likely have data analysts that understand what and where it is to help support marketing.
STEPS TO SUCCESSFULLY IMPLEMENT ADOBE ANALYTICS
Celerity has defined 9 basic steps to implementing Adobe Analytics successfully. You may have partially or fully completed some of the individual steps, or you may be starting with a new implementation or re-start with Adobe Analytics. If you are going to be the owner or Project Manager of the implementation, below are some recommended steps to begin the process:
1. Identify the core team: As we all know, the team that you want involved in the project is critical to the success of the implementation. At a minimum, you would want to include representative(s) from your marketing group, SEO subject matter experts, IT team representatives and one or more executive sponsors. Be sure to include one or more people that really understand the data you have and are skilled in data analytics, segmentation and have a "what-if" type of data mindset.
2. Familiarize yourself with Adobe Analytics components: Get your arms around the foundational pieces of Adobe Analytics and Adobe Launch before building out your Business Requirements Document (BRD). This doesn't mean you need to be an expert in Adobe Analytics, but understanding the following areas is key to building a solid project approach:
• The Segment Builder
• The Analysis Workspace
• Activity Mapping
• Data mapping & tag management
• Traffic Variables & Management
• Attribution concepts
• Report Creation & Analysis Dashboards of various types
• Data and report importing & exporting options (e.g., using SFTP & FTP)
• Setting up user access
3. Build the Business Requirements Document (BRD). The BRD or Solution Design Document is the next step in the process. This document is the primary vehicle for outlining what is in scope (and out-of-scope) and the specific success criteria for the project and serves as a living document following the implementation. It includes identification of the business reasons and goals expected from the implementation of Adobe Analytics. Additionally, it defines the criteria identified by the stakeholders as to the data to be collected and the reports to be designed.
Essentially, it requires you to ask the business owners, 'What are the questions you want answers to?" This is all then documented in the BRD, with a Project Workplan, along with an audit and assessment of what is currently in place, the data that can be utilized, which users will be viewing reports/dashboards, and other resources that will need to be invested and trained.
4. Define your KPls. This is a crucial step in the process prior to beginning the physical implementation of Adobe Analytics. With so much data available, it will be tempting to measure everything. Be sure and avoid KPI overload by focusing on the most impactful measures.
A best practice to developing KPls is to conduct a couple of work sessions with your stakeholders to clearly define which KPls will be measured, their degree of action-ability, their link to documented business goals, and their formula or calculation. This will ensure you gain consensus from the project stakeholders from the start. The information to gather from the KPI Definition Workshops would include:
Defining how the KP/swill be utilized, (e.g., who is the audience, what do they need to achieve, and how they will be acted upon)
Tying them back to strategic goals (e.g., revenue growth of x%)
Using the SMART acronym when defining the KP/s, (e.g., Specific, Measurable, Attainable, Realistic, Time-Bound)
Having a mix of reactive & proactive KP/s, (e.g., reactive ones help you understand activity over a period such as the prior 30 days, but then also have KPls that help you predict what might happen based on data)
Preparing to refine your data if needed (e.g., accurate KPls require accurate data, so ensuring the data is correct, timely, and coming from the correct source is critical)
Defining the actions and alerts you will want (e.g., alerts help you respond to changes in the business, and trigger-based events will automatically take the next best action for the messaging)
Below are some traditional Marketing KPls that most organizations want to track:
Marketing Qualified Leads
Sales Qualified leads
Social Program ROI (by Platform)
Cost Per Lead
Net Promoter Score
Brand Awareness (visitor counts). New Customers Gained
Upsell & Cross-sell Rates
Return On Ad Spend
Total Revenue
Revenue Per Visit
Site Conversion (CTA Clicks)
Cost Per Acquisition
Organic Traffic & Leads
Average Order Value
Customer Lifetime Value
Rev by Prod/Service
Average Visitor Time
If the goal is to focus on Financial KPls (e.g., margin, expense, revenue, cash management), then below are some of the more common Finance KPls:
Gross Profit Margin/%
Working Capital Ratio
Net Profit Margin/%
Operating Expense Ratio
Payroll Headcount Ratio
Return on Assets
Quick Ration (Acid Test)
Debt-to-equity Ratio
Gross Profit to Op Expense
Operating Profit Margin
Cash Conversion Cycle
AP Turnover Ratio
AR Turnover Ratio
Budget Variance/%
It is important to note that the KPls should be re-visited every 6 months to ensure they are still the most important metrics to helping achieve your business goals. If one or more aren't providing you with actionable insight, then they should be replaced with new ones that are more specific to your business functions. Meet regularly to review them, take a close look at their performance, and publish any changes you make so teams are always up to date.
5. Implement Adobe Analytics. Now that you have learned the basic components of Adobe Analytics, created the BRD, have defined the KPls and assembled the team, the implementation can begin. There is a documented technical Pre Implementation Checklist' that you can follow to walk you through the steps, that Celerity can provide to you. Then you, or the designated Project Manager along with a representative from IT can begin the process. In general, and at a high level, the implementation steps include the following:
Receive the email from Adobe, click on it, and the installation steps begin - typically with the first step of adding one or more 'Report Suites." A Report Suite is simply a core where data is directed and calculated that you would set up for a channel (e.g., website, or mobile), or by brands
Next you would configure the DTM configuration, Following the technical instructions for setting up data collection rules and setup
Following your defined Naming Conventions, you would begin setup for data elements, rules-events, conditions/exceptions, and actions
Next you would set up your Single Page App (SPA, Multi-page applications and/or mobile apps) and any related configuration along with a well-structured Data Layer (event-driven is recommended)
Define how your data layer behaves with the data being used on the chosen application and add 'Send Beacon' in every rule where applicable
Carefully set up rules and any custom coding to define how data is forwarded to be used in Adobe Analytics
Create clear development, staging, production, and post-production processes of how code and libraries are rolled out
Create a development/staging build in Adobe Launch and a UAT environment based on your specific technical processes
Validate the UAT environment & begin creation of reports & dashboards
6. Create Your Dashboards. At this point, you are ready to develop your dashboards which are going to be collections of your data displayed to help you review your different KPls or metrics at once. Adobe Analytics provides some example templates, but below is a list of dashboards you may want to consider establishing so that the data is easily grouped and able to be analyzed by your team:
• Traffic Insights Dashboard (DB)
• Demographic & Audience Info DB
• SEO & Organic Insights DB
• Social Media DB
• Visitor Behavior DB
• Page Insights & Content Marketing DB
• Video Marketing Insights DB
• Conversion Tracking DB
• eCommerce DB
• Site Performance DB
• Mobile Performance DB
• Channel Performance
7. Build Additional Reports. Adobe Analytics offers 00TB reports that provide a starting point for your analytics team. But you will want to sit with the key marketing, executive &
finance users to define additional ones that will really speak to their business needs and provide them with new insights that were unavailable to them before Adobe Analytics.
8. Train, Test & Launch. There are several sub-steps in this activity specific to Adobe Analytics, such as training, testing, launch prep, ongoing support, post-launch updates, etc. Be sure to allocate sufficient time to the training and launch, and identify designated resources who will provide support during the first 6 months of the implementation. It's a powerful application, so thinking through how to introduce the concepts to users, along with some simple first exercises will help with adoption.
9. Bi-Annual Review. The most successful Adobe Analytics implementations are undertaken every 6 months to review the reports, channels accessed, marketing tags, and of course the KPls within Adobe Analytics. Don't let this review go past 6 months, as it gets off-track quickly as new promotions are added, new website updates are put in place and users come and go. You will want the Adobe Analytics reports to be bulletproof with their data and insights as once someone finds problems with a dashboard or report, people tend to not trust anything afterward. A quick 6-month review of the key components will allow you to stay on top of changes, and give your team the chance to evolve Adobe Analytics and add new reports, channels, and KPls in an organized fashion.
BEST PRACTICES, THINGS TO CONSIDER
Once you have finalized the BRO, KPls, dashboard and reports, and gone through the physical implementation steps, you are essentially up and running on Adobe Analytics and are now collecting your data for analysis. There are, however, a few best practices to consider to ensure the overall implementation goes as smoothly as possible. These would be considerations such as:
Think about ways to enable users to become familiar with your data for them to be self sufficient. It can be difficult to only have 1 or 2 people who are Adobe Analytics analysts. Those 1-2 folks end up having to support requests from Executives, Marketing staff, Site Optimization Team members, Mobile App Developers, etc. Getting more of those people comfortable with Adobe Analytics and being technically curious about the data will greatly reduce the load of questions on a small number of people.
Define Report Suites and dashboards specific to Executives (such as a Mobile Scorecard), Finance and Marketing, so that they become comfortable using the application
Define custom histograms for marketing end-users to help simplify the data and view the information in multiple types of formats
Take advantage of the various 'Extensions' that can advance the power and usage of Adobe Analytics for various end-user types
Develop Naming Conventions ahead of time and ensure the names you assign are as clear as possible for everyone to understand
Create standardized code templates to make it easier to ensure consistency
Set up your data layers to make them simple and easy to understand for future maintenance
Don't duplicate rules that have the same event or condition triggers -- instead think about global rules and conditions that apply to the same data collection process.
SUMMARY
An Adobe Analytics initiative can and will be 'exciting' to roll out. And, with the right degree of definition, planning and support, along with an appreciation for what can be a legitimate resistance to change, that excitement will be for the right reasons. Adobe Analytics' platform with its power to analyze large quantities of data, combined with Celerity's expertise in simplifying the interface and rolling out similar initiatives will give you a strong
and deep foundation to grow with it's ability to help you monitor web traffic, track marketing attribution, and predict business opportunities is unparalleled in the market. You can start simply with an easy-to-use Adobe Analytics setup, and then add to it with more data, KPls and reports as your team gains experience. But most importantly, the more attention your marketing executives and implementation team can spend on planning the setup up front, the greater the chances that you will knock it right out of the park.
If you would like to speak to one of our Adobe Analytics consultants in regard to any questions you might have, please don't hesitate to reach out to Sean Burrell at sean.burrell@celerity-is.com, or via his cell at (617} 816-9492.