Trust, [Noun] 1. The firm belief in the reliability, truth or ability of someone or something.
Trust is a funny thing, it can be difficult to achieve, easy to lose and even harder to get back. We hear clients regularly complaining of a lack of trust in their web data. Unlike in personal relationships, trust in a system can be built in and intrinsically linked to the output of that system. Unfortunately, like a personal relationship, it takes time, effort and maybe a little heartache to attain.
“29% of companies using Google Analytics exclusively are unsure if their installation of Google Analytics is properly configured.” [Source: Econsultancy /Lynchpin Online Measurement and Strategy Report]
There are a growing number of tools and methods available to allow us to dig down into the data and eliminate the finger in the air guess work that is a scarily common method of optimisation and justification of online marketing activity even in 2011!
“Less than a fifth of organisations have an internal strategy that ties data collection and analysis to business objectives” [Source: Econsultancy Online Measurement and Strategy Report]
To regain the confidence in the quality of your data, it is necessary to return to the root of the problem, start at the foundations and rebuild a measurement structure and strategy from the implementation level up.
This means auditing, configuring, testing, tweaking and more testing, prior to embarking on the analysis. Rebuilding the foundations of your web analytics implementation is essential to building up the confidence lost.
What are the barriers to accurate online data?
Web data will never be 100% accurate; accepting that there is an inherent fragility in web data collection is key. Visitors may block cookies, browsers may bounce before code fires and so on and so forth. On the plus side, web analytics is infinitely more quantifiable than traditional marketing channels.
Taking a vested interest in how the tracking code on your site works and the factors that could affect it will allow you to make site decisions that fulfil the need for change and ensure that data retrieval is not negatively impacted.
Another vitally important element of gathering accurate online data is campaign tagging. Incorrect or improper use of tagging can be the cause of incomplete or incorrect data being retrieved. These tags contain the data key to understanding and optimising your marketing spend.
Finally, a strategy that engages with multiple web developers, a multitude of search agencies and internal stakeholders can spiral off course. It is important to understand who is responsible for what and ensure that there is suitable guidance for any activity which may affect your web data. It could be a case of “too many digital cooks spoil the broth”.
How should you go about fixing these issues?
- Audit and evaluate the tracking code implementation on site. It sounds basic, but you wouldn’t believe how many sites are using out of date, incorrectly customised, misplaced or just plain missing code.
- Evaluate processes on your site. With flash, iframes and like being used on many sites. Is the tracking code taking into account these on site elements and is it ensuring that visitor movement is being tracked in the manner you wish.
- Review your tagging strategy and understand its importance. A great number of the issues we deal with are tag based. Whether it is missing tags, incorrectly implemented tags or redirects stripping them off. They are fundamental to understanding online data.
- Configure your data into logical sets and sub sets. It is easy to get bogged down in the mire of web analytics data. Make it easy on yourself, by utilising smaller, more focused ranges of data.
Then get on the Analytics road map!
Assigning ownership and understanding the challenges, whether internally or externally, will allow for a suitable measurement structure to be put in place. Alongside this, a KPI framework or measurement strategy will focus your understanding of the success metrics in relation to your business project and tie together data collection, configuration, retrieval and analysis.
In the privileged position we find ourselves in as web analysts, with abundant technology, sophisticated software and plentiful data. We owe it to ourselves and to the companies we work for to deliver quality conclusions, based on quality data with pretty graphs as an extra little bonus!