Deploy Overview

After your implementation has been designed and documented, it is time to begin the deployment phase of the analytics implementation. Within the typical deployment phase of analytics projects, there are three distinct required activities:

Deployment of the data layer and tagging specifications to developers who will populate the data layer
Configuration of the tag management system that will be used to deploy the code
Configuration of the variables within the analytics tool itself

These three tasks must be done in concert in order to correctly get the data needed to answer business questions. Apollo simplified this process by ensuring that the data layer, tagging specifications and analytics tool variables are properly aligned by leveraging a relational database versus text documents and spreadsheets. Apollo also expedites your analytics deployment by leveraging API’s to automatically deploy the items outlined above. This means that activities that have traditionally been done manually, over weeks or months, can now be generated and deployed within seconds!

Another important aspect of the deployment stage of the analytics implementation is the creation of analytics calculated metrics and dashboards. Reporting is like the “tip of the iceberg” in that it is often the only thing that business stakeholders see related to the implementation. Therefore, it is important that your implementation have metrics and reports that answer the specific business questions that were selected when the implementation began. Unfortunately, if you have many business questions, that could mean manually creating hundreds of different reports for your stakeholders. Apollo solves this problem by providing a mechanism for automatically generating a baseline set of metrics and reports for selected business requirements. These reports are created using API connections to the analytics tool’s reporting interface and are a great starting point to ensure that business users can start seeing data as quickly as possible.