Web analytics has lagged behind traditional business analysis methods for many years. IBM, a new/old player in the web analytics world, is now in the position to change that and move the two disciplines closer. Statistical modelling will significantly increase the value and prominence of web analytics.

Last week IBM announced the acquisition of web analytics and online marketing optimisation company Coremetrics. This acquisition is another milestone in a growing trend of large corporate organisations buying into digital analytics vendors. Adobe took over Omniture, Coremetrics’ biggest competitor, last September. Google acquired Urchin to create Google Analytics and similarly Yahoo purchased Index Tools rebranding it as Yahoo Web Analytics.

At the same time large data and marketing solution companies such as Unica and SAS are expanding their web analytics and optimisation capabilities through acquisition (Sane NetTracker) and partnership (Speed Trap) respectively.

Some argue that the IBM acquisition of Coremetrics will stifle web analytics innovation. Similar claims have been made regarding the Adobe Omniture tie up.

Whilst such arguments might hold in the Omniture case (Adobe’s focus on measuring its own applications), the Coremetrics acquisition is different.

IBM is investing heavily in the area of business analytics and optimisation. It has spent over $10bn since 2005 on acquiring companies in this and related fields. The company recently announced its new big data information management and insight service offer Infosphere BigInsights.

Two key shortcomings of web analytics technology are the large amounts of unstructured data and the lack of any significant statistical modelling and predictive analysis capabilities.

Tools such as Omniture Insight and Webtrends Segments offer significant analytical and visualisation capabilities but leave much to be desired in terms of modelling and future trending. Google Analytics is only starting to address these issues scraping the surface with its Intelligence feature.

In comes SPSS, IBM’s acquired predictive analytics software and solutions firm. IBM is now in a position to merge Coremetrics’ web and mobile analytics collection platform with its powerful statistical modelling software. Such analytical capability is common practice in the offline CRM and Direct Marketing worlds but so lacking in the online world.

Web analysts spend significant amounts of time guesstimating which visitor segments are most important to their business and how to break down users’ behaviour in order to optimise the online customer experience. With SPSS’ decision tree algorithms analysts will no longer need to go through this trial and error process. Instead the software will tell them which visitor segments they should focus their attention on. They would then be able to approach the data in a much more constructive way gaining deeper insight faster.

This is just the tip of the iceberg.

Statistical modelling will enable analysts to identify significant outliers skewing any analysis. They could validate which data streams are significant and which should be ignored. They would be able to structure the data and apply it onto predictive models. These models would then be used to inform A/B and multivariate testing, currently an art as much as a science, and transform them into a more robust empirical process.

More than anything else the IBM Coremetrics tie up symbolises the expected transformation of the web analyst role. Currently a siloed analytical entity residing in the e-commerce or online marketing departments, the web analyst will migrate into a more traditional business analyst role within the insights and MI departments.

This next
step in the web analytics revolution promises a significant improvement in the
management of online assets. This process won’t be devoid of many new (and some
old) challenges. However, I will leave the discussion of those challenges to
another less euphoric post.