With the advent of Google Analytics the rapidly dominant standard in web analytics, hundreds of thousands of small to mid-sized online marketers jumped in and began reporting on consumer behaviors on their sites. This made for great discussion and was thought provoking. It spurred marketers to “copy and paste” GA tags into their sites at a blistering pace, in short order, GA had an 80% market share.
Big players like Omniture had a long head start, and though their relative share of the market fell, they also held tight to the larger and enterprise client base. Their product was mature –and considered complex.
Google rolled out Google Analytics 2.0 which ushered in a generation of enterprise-class online marketing features. This created a dramatic change for marketers in how they viewed their data. Accomplished primarily through a tool called “Advanced Segments” marketers would be able to view data by literally hundreds of dimensions and include and exclude populations that met any number of criteria –and the web interface to do so was relatively straightforward.
If the online marketer, or their online agency had the experience with web analytics, they would see behaviors that were masked in the volume of activity on their websites. The tool was powerful, but on larger sites, the complexity and time commitment to extract value from GA’s enterprise feature set led marketers to seek the professional help of a Google Analytics Authorized Consultant (like us : )
Across dozens of Clients of every kind we’ve been able to usher in visibility into consumer behavior not previously available, and markedly improve the value of our Client’s websites, online marketing activities and ad budget.
What is truly the next step? It is likely it has to do with measurement of the behavior of an individual. This is a step Google avoids, and its much smaller competitors (who don’t also own the largest search engine) embrace. Awash in privacy concerns Google won’t touch the issue… today.
What are the solutions? A user level opt-in (possible) continuing to refine the analytics on an aggregate basis?
One answer is what will may already be regarded as Analytics 3.0 –Predictive Analytics. predictive analytics (“PA”) is implemented when you have access to a critical mass of consumer behavior and can begin to draw inferences that answers “next most likely product” questions –that is, what is the next most likely product that a consumer with a specific set of behaviors will buy? This requires the creation of an algorithm, the testing of it, and the optmiziation of the algorithm.
At Endai Labs, the R&D Group at Internet marketing company, Endai Worldwide, we’ve been experimenting and improving predictive analytics approaches and technologies on behalf of clients for some time now. Most recently we began integrating an algorithm to increase the number of purchases and increase average order size for etailers with email marketing.
Going beyond web site behaviors, marketers can now predict the products that a customer is most likely to respond to, we can also select the promotion they are most likely to respond to. This tool, MarketTraq Email for Google Analytics(MT/GA) is integrated on the back end with Google’s Data API. With MT/GA marketers can use your native Google Analytics data to measure and optimize the results of consumer behavior on your website and through your email –and the relationship between the two.
This is one of the first steps to increasing sales and share through predictive analytics. There is much more to come.