How to plan and implement an analytics product

When it comes to planning and implementing an Analytics product in the most effective way, there are several key steps that any business should take.  

The first key planning stage is producing a high-level view of what the implementation should deliver. This shouldn’t be too detailed, but it should give you a sense of who needs to be involved from a KPI/requirements perspective. Just saying “I want to measure website performance” is not enough!  

Once that’s done, a list of all stakeholders/interested parties can be drawn up. These will feed into the requirements/use cases that the implementation should be based and delivered on. This is a key step, and essentially informs the success of the implementation.  

Once the stakeholders are identified, a list of their reporting requirements needs to be captured. This usually works best via individual meetings with each business unit. For example, capturing the requirements for the digital team, the content team, marketing team etc. Separately.

Finding a solution

Once all of the relevant requirements have been identified, a solution design document/reference should be created. This document outlines the variables that need to be populated in order to meet the requirements set out in the discovery session. This will enable a data layer specification to be created that will then be utilised by the development team for implementation.  

Once the solution design document (SDD) has been created, a data layer specification needs to be built. This is a document that outlines all the data points required to be populated on each page of the website to enable the required data capture. The developers responsible for its implementation will need this to estimate the effort required in order to implement it. 

The plan of action

Next is resource management and planning. Whoever is doing the actual implementation, the likelihood is that IT/developers will need to update the site code to enable the data capture to deliver on the new requirements. This essentially means, either updating an existing data layer, or implementing a brand new one. It might also be the case that a new tag management system needs to be added to the site. Even though this is fairly straightforward, it is a consideration that needs to be made. The testing and bug fixing of all of this work should be included in the resource estimates.  

Similar to the above, the actual implementation can happen once the data layer work has been completed. Whilst some things can happen in parallel, development and testing of the implementation based on the new custom values in the data layer can only happen once the data layer is in place and working.  

Testing & checks

Post-implementation, there needs to be data validation/testing of the implementation in development environments. This is a key element and must always be factored into any original planning/timelines. 

Once all of the above has happened, it can then go live into production. This should be followed by post-live data validation to ensure that data looks correct. You can do a lot of testing in development environments, but there’s no substitute for checking the live data across thousands of visits. 

Please get in touch if you want to talk about anything related to planning and implementing an Analytics Product that is tailored to the requirements of your business.