Mind the Digital Analytics Perception Gap

Monday Nov 2, 2009

Articles, blog posts, and press releases abound about how much data the internet is now making available for marketers, about what a sea change this data deluge is bringing to business processes and decision-making. New data companies are entering the space every day, each with case studies that verify the utility of their offerings. A new world of data-driven marketing is upon us!

The success stories and the promise of digital data are very real.

As head of Ogilvy’s digital analytics practice, I obviously believe that. But marketers can be lured in by all of the industry blitz and buzz about data and analytics. Despite what you may have read, successful analytics doesn’t just happen by virtue of having the latest tools. Without proper planning and dedication, the result can be a failure of digital analytics to live up to some very lofty expectations.

There is currently a digital analytics perception gap.

The siren song that “the internet is the most measurable medium” can lead us to crash up against several truths that this oft-repeated mantra, masks:

1) Not everything is measurable on the internet

2) Not all things are worth measuring on the internet

3) Measurement is not an inherent byproduct of the internet

Fortunately, overcoming the above issues — which can derail an analytics program — is as straightforward as having a comprehensive KPI planning process. All three of these potential landmines can be tripped when expectations are not established at the very beginning of the process. KPI planning is a key part of laying that groundwork.

I found a recent Unica survey of marketers’ challenges with web analytics to be illustrative of the current perception gap.

Source:  “The Web Analytics War Reader Survey”, September 2009, http://www.unica.com/eMediaeSurvey

Source: “The Web Analytics War Reader Survey”, September 2009, http://www.unica.com/eMediaeSurvey

1) Not everything is measureable on the internet

In the eMedia/Unica survey, 32% of marketers noted that one of their biggest challenges with web analytics was that the data was not comprehensive enough. Now, it is possible that implementation issues are to blame (more on that below), but from my experience I would posit that it is also likely that there is a desire for web analytics or the website to do more than it should.

Solution: The key is to match very clear KPIs to both business problems and realistic expectations of web performance. Be very clear about the role the website is intended to play within the business, and be sure to capture measures that provide information about its performance of that role. If it is an ecommerce site, track sales; if it is a brand website for a packaged good, then sales are probably not in the cards. Having upfront agreement on KPIs means that the role of the website has been considered, and there are no surprises later on when web analytics is tasked with answering questions the website was not intended to resolve.

2) Not all things are worth measuring on the internet

In the same survey, 23% of marketers stated that one of their biggest challenges with web analytics was that the data was too complicated to analyze. Again, from my experience, I would suggest that it is likely that a clear KPI process was not undertaken by many of these marketers. If KPIs are set upfront, then the measures to analyze are known entities, thereby limiting their complexity.

Solution: Mitigating data overload requires planning and foresight. Else a kitchen-sink approach could develop, in which too many measures compete for attention. In that scenario, the result is either “paralysis by analysis” (where data is crunched myriad ways but without direction) or “data indifference” (where the metric of success is reset anew with each project). Having a proper plan in place, in which KPIs are thoroughly thought through, will focus down the number of measures to analyze to just those that matter. Formalized measurement planning is so important to us that Ogilvy has developed a framework for establishing KPIs, called Evaluate. As we work clients through the Evaluate process, we move step-by-step from business goal alignment, to metric identification, to benchmarking, and finally to implementation. Which leads us to the mother of all hidden truths:

3) Measurement is not an inherent byproduct of the internet

Implementation is absolutely critical to the digital measurement process. This is where the respondents to the eMedia/Unica survey revealed the biggest gulf between web analytics perception and reality. 41% stated that data accuracy was an issue, while 19% felt that site tagging was too hard. Just because the internet is the most measurable medium does not mean that measurement appears out of thin air or is just a built-in-feature of having a website. Accurate and comprehensive measurement on the web demands technical planning and implementation. The hype around digital measurement often neglects this fact; it’s the small print in the advertisement.

No matter what you may have heard, it is not as easy as flicking a switch. I want to be very clear that I am not suggesting that the physical work to do the tagging is difficult or laborious. But, without proper planning it can certainly seem that way. That can be the perception.

A majority of current web analytics solutions have moved beyond earlier log-file techniques and onto tag-based collection techniques. Logfile solutions were easy to implement because the logs were already being populated by the website. But logfiles were not originally designed for marketing purposes. They lack the specificity and flexibility that marketers need. So, tag-based systems evolved. However, if it isn’t tagged it isn’t measured. And if it isn’t tagged properly, it isn’t accurate.

Solution: In baseball vernacular, “tagging it” means hitting a homerun. If marketers want to hit homeruns with site measurement, this means really thinking about and planning for measurement and site tagging. Out-of-the box tagging solutions won’t cut it for most marketers. And, implementations customized to goal-specific KPIs require consideration in early stages of site design, not at the completion of site build. Vanilla implementations will miss the measures that marketers really want to look at, and attempting to mash measurement implementation into the back-end of site build can lead to hasty tagging, missed opportunities, site delays, and sour feelings about web analytics. To avoid these issues, marketers should aim to have a KPI plan that is finalized early in the site design stage. The web analyst should be involved in creating measurement specifications before site build has gotten too far under way. This way measurement is part of the development cycle. Time at the end of build can be spent on QA instead of on how to retrofit a tagging strategy to an already-built site.

As you can see from my discussion of the hidden truths of web measurement, I suggest rigorous KPI planning at the early stages of site development as a solution to the perception gap in web analytics. It helps us to come to grips with what can be measured, keeps us focused on what should be measured, and ensures that we actually follow through on appropriately measuring it.

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