Adobe Marketing Cloud, Google Analytics, IBM Core Metrics and Web Trends – all of these tools provide end to end digital data collection, data processing and provide you standard template based reports. All of these come as one package as ASP based model where you just load the software application in the browser to implement or use.
In late 90’s or early 2000’s- there were no options available for businesses but to rely on this software as storage and computing were quite costly to invest in-house.
Digital Analytics Tools Landscape – All the above digital analytics tools revolve around the four key steps.
Lacking Flexibility: Proprietary software lacks flexibility to meet unique business needs.
Cost: High License Fee, often over paying for the solutions offered.
Not standalone: Often require an additional technology or resource for meeting the business needs.
Scalability: Scaling is not immediate.
Takes a large amount of time to process the data and this makes system unavailable
With the proprietary measurement frameworks, enterprises have no control in how the data is collected, stored, processed and visualized. They often paying for multiple tools to meet one business requirement.
The Next Big Opportunity is in your Data and this data is across the globe in different formats.
Data is everywhere, it is imperative for businesses to collect this Data from across channels and combine the insights to optimize the multi-channel customer interaction processes and marketing.
But, the challenge is most enterprises have already locked or invested heavily to deploy the existing tools which operate in silo and never speak to each other fully.
However, with the current generation of cloud computing and Hadoop frameworks – it is working out very cheap to store and process the data the way your business needs and no more need to compromise the business with one size fit all software solutions.
Augment the current technology platforms in Digital Analytics in preference to : Big Data Technology Stack “cloud computing and hadoop frameworks”
Tag Management is the second generation digital analytics process, this was introduced to universally tag the pages for collecting data for multiple data collection/measurement tools – One Tag to address all your data collection & re-marketing needs.
Some of the widely used “Tag Management Tools” in the market are – Google Tag Manager, Adobe Dynamic Tag Manager, Ensighten Tag Manager, Tealium. All tools listed here serves the core purpose of digitally collect and distribute data to multiple systems with minimum tags in the page.
Lets explore if we really need a tag management tool for measuring clickstream behavior of our digital visitors.
If we segregate complete click-stream measurement into three different categories:
2. Meta Data is the data about data such as page names, classifications, product skus, targeted language & country and so on. This data is defined by us and available with us. We have absolutely no reason to recollect this data using the tag management. I have always seen 80% of the data collected currently about the data we already have with us. There are different ways to send the meta data back to the tools to avoid page tagging.
3. Dynamic Clistreamstream Data, this type of data is non-standard for each visitor and each click. This data is not known to us nor can be collected in a default like Meta Data. This data generally includes number of units, sum of revenue. If you really have a shopping-cart and visitors can add multiple items into the cart or you want to know what keywords are used on your site search. This becomes significant for you. though the data you collect is less than 1% most times, the value is above 80%.