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Can you trust your data? Our analytics audit will help you

Information about user behavior on your website is a central part of your success in the digital world. However, the prerequisite for this is that the data collected is correct and of integrity. An analytics audit checks the entire configuration of your analytics tool as well as the underlying data in order to identify concrete optimization potentials. This is the basis for action-relevant data from which you can derive target-oriented measures.

Many companies today use analytics tools such as Google or Adobe Analytics to collect data about the users of their websites. However, companies are often not even aware of the opportunities offered by this data. In order for the various stakeholders to be able to use this data as a basis for their decisions, they must be able to trust it. This presupposes that the data collected is correct.

An analytics audit is a crucial component in the validation of your analytics tool and the data it collects.

Why should a company conduct an analytics audit?

Often the possibilities of the analytics tool used are not fully exploited, since only the basic settings are made. This can lead to erroneous reports and reduce the informative value of the analytics tool as well as confidence in the results. To use the analytics tool as a decision-making tool, the data must be correct and the trust must exist.

With our analytics audit point out to a company in which areas of the used analytics tool the maturity is still low and which configurations must be made in order to collect and process meaningful data. Based on comparative data from similar companies, the analytics audit provides an overview of strengths and weaknesses.

An analytics audit – the best way to make sure you can trust your data.

What do we evaluate in an analytics audit?

The basis for meaningful data are the online strategy, the (online) goals and the derived Key Performance Indicators (KPI). The audit is aligned according to these anchor points. We analyse these five central areas:

  • Account Setup & Governance
  • Tracking
  • Data quality
  • Extended data acquisition
  • Reporting

In the first topic area we check the account setup and analyse to what extent governance and data protection guidelines (e.g. DSGVO) are observed. The second area analyses the tracking of the various websites. The detailed analysis of data quality also shows conspicuities in the reports. Specific functions such as e-commerce tracking, conversions, targets or campaign tracking are analysed under the title «Extended Data Acquisition». Finally, we examine the specific reporting behavior of the company. For example, the cycles and granularity in which the identified stakeholders receive reports are examined.

Analytics Audit for the Mobility Cooperative

We were allowed to conduct such an analytics audit for the Mobility Cooperative. Martin Seifert from Mobility summarizes the audit as follows:

«Together with Unic we were able to identify conspicuities and potentials in our digital analytics setup. This enables us to continuously develop our online strategy. The results of the audit are clearly formulated and summarized in such a way that they could be shared with the relevant departments and employees without costly explanations. The recommendations contained therein have largely been directly converted into requests for the responsible developers and analysts.»

In summary, the analytics audit is an opportunity for your company to validate your data quality and to increase confidence in the data. The aim is to use the analytics tool efficiently as a decision-making tool and to provide your stakeholders with the right information at the right time.

Our digital analytics specialists will be happy to discuss your specific audit requirements with you. Contact us now: analytics@unic.com

Data visualisation – the tool for easy and quick knowledge acquisition

Our first article concerning digital analysis revealed the challenges faced by companies in today’s world of data. Companies often have enormous quantities of data at their disposal but fail to take advantage of them. This is because many entities focus on gathering and storing data, while the aim of digital analysis – which is to enable deriving data-supported recommendations and optimisations of actions – is frequently not pursued consistently. Data should support the decision-making process, and to this end there must be a possibility to analyse and interpret them comprehensively.