Our Process

Why Process is Important

In short; arbitrary approaches bring arbitrary results.

Web analytics is a very new discipline. As such the skills required to gain full advantage from this are rare and extremely varied. A skilled web analytics professional has skills that include marketing and business acumen, technical expertise, domain knowledge and significant experience in applying data to real world problems.

The big problem for most companies is that finding and retaining these people is very difficult or impossible. Many people who claim to have analytics experience are really not any more advanced than the average digital marketing professional. The result is that the value of analytics is significantly limited.

Tools like Google Analytics provide a wealth of options to record and measure data from your website and online marketing. The downside is that interpreting this information is nuanced and complex. Ensuring that you have documented processes on how to gather, report and interpret this data is a critical step to realising the benefit of this resource.

Having documented processes helps reduce the reliance on highly skilled consultants and team members, reduces the total cost of ownership of web analytics, ensures that results can be repeated in the future.

Even simple things like how campaigns are “tagged” can be fraught with difficulties in larger companies. For instance if someone sets up the campaign with the medium as Email and another uses email then Google Analytics treats these two as completely separate. The result is that campaigns are more difficult to analyse as a whole due to one simple difference in capitalisation. Having a formal process and tools to create and manage campaign tracking codes is just one small example of how process is very important to the success of any web analytics project.

The Panalysis Process

Our key difference is that we apply a highly disciplined approach to web analytics. This approach has been developed over the past decade based on many client cases and the common problems that we see time and time again.

Whilst in essence the process is identical to the standard discover, plan, implement and react cycles the difference is how we do this.

Discovery

Our first step is to identify the key drivers that will make a difference to your organisation and how these apply to the digital marketing initiatives (e.g. websites, apps, social media campaigns, etc).

These drivers are then examined to identify which signals will provide reliable measures that can be used to identify the current and potential future performance of the initiative.

Measurement Framework

Panalysis will develop a documented framework that outlines each of the important measurements your business needs to understand how it is performing. This framework will include information on each measurement, how it’s mapped to the broader business goals, where the data is sourced from, how it is accessed and how it should be interpreted.

Data Audit

We then determine what data is currently available to measure these and to plan what changes can be implemented to gather data where it doesn’t exist. This may require that some additional JavaScript code or other method is employed to record and store this data.

Implementation and Quality Assurance Testing

Often getting the right data requires adjustments to your website, social media and mobile applications and other systems. Panalysis will work closely with your development team to implement all of the necessary tracking required to capture the appropriate data. We will also check and test the work as required during the implementation phase.

Operating the System

Web analytics implementations fail if they are not used regularly. A key reason that people stop using web analytics is that it is often too difficult to operate the system. Panalysis will work with your team for the months following to ensure that they can both understand and master the system that we build for them.

Our services include training, coaching, consulting and support services to ensure that your team gets the greatest benefit from its investment in analytics.