Is your data telling the right story? We have done a tag audit for many clients who are concerned that they do not have accurate data from Adobe Analytics. Below are a few steps to help your organisation drive data-driven decisions, be confident in your marketing strategy and leverage all the best features of Adobe Analytics.

Key Best Practices:

Below are a few best practices that will help you make Adobe Analytics as your primary analytics tool and help you get most out of your Adobe Marketing Cloud investments.

1.  Spend time to gather requirements for your implementation:

Gathering the requirements exhaustively is very essential to complete the implementation on time and in avoid rework. Discuss what data needs to be collected, whether getting the required data is possible, what marketing channels are involved, how the data should be processed, how the data should be reported and then finally, list out any exclusions.

2.  Create a detailed plan:

Probably one of the most overlooked aspects of Adobe Analytics implementation is planning. Many marketers skip the planning and jump straight into the implementation phase which could result in rework, missed deadlines, additional resources and unexpected results. Create a project plan to outline all the various steps required to carry out the implementation, list key deliverables and list resources required from client’s end to carry out the implementation.

3.  Spend time to document all your work:

Creating a Solution Design Reference (SDR) is the cornerstone of Adobe Analytics implementation and it will be the focal point of all the activities related to tag implementation. Even if you have implemented Adobe Analytics many a times, it is important to maintain the SDR up-to-date with each change. As important as documentation is the need to get the sign-offs on the document at regular intervals as well.

4.  Create a benchmark – Adobe Analytics Vs Internal Reporting:

The Adobe Analytics data reported may not exactly match with the Client’s internal database, so it is important to set correct benchmark of accuracy so that the expectation can be set right from the outset. This should be setup as part of the testing process before a switch-over happens.

Technical Recommendations

Important technical recommendations that can be used as a checklist to ensure all aspects of Adobe Analytics implementation are discussed here. Although the Adobe Analytics implementation guide covers the complete implementation in detail, it is not possible to list out all the technical aspects as they may vary depending on the nature of business, underlying technology used and a host of other factors.

1.  Tealium Data Layer Validation

Test the Tealium Data Layer Variable to ensure that required data is available as per business requirements, so that it can be sent to analytics. The Tealium Data Layer forms the backbone of Analytics Implementation; hence it is important to periodically perform validation to ensure that the data is populated as expected. If the required data is already available in the data layer, it may not use the JavaScript Extensions to capture this information dynamically. Tealium offers predefined data layer variables that can speed up the code deployment process and provide various extensions which are helpful to get required information from the website.

2.  Choosing the JS library for Adobe Analytics

We recommend implementing the Adobe Analytics using the JavaScript AppMeasurement Library as it is faster, provides native support for several common plugins and provides native utilities such as query parameters, read and write cookies and advanced link tracking. Some of the plug-ins are no longer supported in the updated version, hence one must check the adobe AppMeasurement plug-in support for additional details.

3.  Configuring Report Suite

Setting up the report suite to ensure the required data is passed to the correct eVars, props and merchandising variables.

4.  Unique Page Name

Probably this is the first thing that will be captured in Adobe Analytics. This information will be a key factor for most of the analysis performed on the website, so keep it simple, unique, friendly and consistent across the website. Effective use of Set Data Extension will be helpful in achieving this.

5.  Avoid Duplication

Avoid sending the same information across different variables as Adobe Analytics offers many ways (processing rules, classifications) to manipulate the information passed. This would also result in restricted usage of variables.

6.  One JavaScript File

It is better to have one JavaScript Extension to populate the information required for passing to Adobe Analytics otherwise this will result in conflict and the order of execution of various information populated will decide the outcome of result. Hence one must do this diligently.

Using the above-mentioned key factors have significant importance in effectively implementing Adobe Analytics and the user-friendly interface provided by Tealium will only make the implementation journey memorable and easy to maintain.

About the Author

Chaitanya Kayasri heads Digital Analytics and BI at Convergytics. Chaitanya has over 13 years of consulting experience with the likes of Netapp, Verizon, DSW, Coca Cola, Excelity, Swiggy, Landmark, Aditya Birla, Henkel and many others. She has conducted webinars and workshops on Power BI and Digital Analytics and most recently presented her views at AI Round Tables in Bangalore and Chennai. She can be reached at [email protected]. You can also connect with her at https://www.linkedin.com/in/chaitanya-kayasri-91336825/