Here comes Google again. In 2006, Google disrupted the Web analytics industry with its free product, Google Analytics. On October 1’st, 2012, Google announced availability of Google Tag Manager, also free. A Tag Manager is a proxy-like service that converts a single tag on every web page into any number of additional tags for tag-driven products and functions.
Free and good enough, Google Tag Manager will disrupt the current market dynamics for tag management products. Within 18 months, we can expect more users of Google Tag Manager than all others combined, similar to the adoption ratios that Google Analytics enjoys.
Tag managers are a great for marketing analysts and advertisers, but that is not the point of this post. Gartner clients can learn more about tag managers and those that provide them in this document: Tag Management Systems Boost Website Efficiency, Quality and Results G00238074.
More importantly, Google’s disruptive entry is a golden opportunity moment for the digital marketing industry to standardize a data exchange model across all tag management systems.
Of the many benefits that come with using tag managers, having a common definition for variables and events is key requirement for advanced users. Here, variables about the visitor, page or transaction, and events like filling in form fields are picked up by a tag and passed on to the tag-driven product. Tag carried data is how tag-driven products work, such as web analytics, A/B testing and advertising attribution.
Normally, each tag-driven product has its own variables in a page and its own tag to retrieve the data. Tag managers consolidate the data passing phase, then maps common variables to whatever is needed for each tag driven product. Imagine how much more simple it is to configure tags in a management system versus maintaining tags within a web page. Now it is easier for web site and content developers to define variables without having to know which tag-driven products will be used.
Now, here is the problem and opportunity. While common data models in today’s tag management systems are a great step forward, each provider represents a different common data model. We are swapping many proprietary data models for a single one, but that one still locks you into a single tag management provider.
If the tag management providers could agree on an standard data exchange model, developers, content management systems and even off the shelf commercial application developers wouldn’t have to care who’s tag management system would be used.
Why is the time ripe for a standard? Let’s face reality. Google will quickly be the new 500 pound gorilla in the tag management market. No other provider has enough market share or market clout to dictate a data model standard, not even Adobe and IBM. Yet, Google’s data model is not finalized yet. There is more work to do. This is the perfect time to try for standardization.
Standards are hard to create, especially among competitors, but it can be done. The networking industry is not without precedent. Ethernet, TCP/IP, SNMP and HTML are prime examples of evolutionary standards that each sparked rapid growth in the overall industry and got us to where we are today. Standardizing a tagging data model would reduce market inhibitors by shifting competition from data model lock-in to more sophisticated management of tags and more use of applications that tags enable.
The standardization effort could be driven by Google, but involvement by a neutral party would help ensure success. The Digital Analytics Association is one obvious candidate for driving a standard, but advertising associations, such as the Internet Advertising Bureau must be represented too.
Read Complimentary Relevant Research
Predicts 2017: Artificial Intelligence
Artificial intelligence is changing the way in which organizations innovate and communicate their processes, products and services. Practical...
View Relevant Webinars
The BI & Analytics Challenge for T&SPs: Major Disruptions on the Way
From artificial intelligence (AI) to machine learning to smart data discovery, the BI market is once again going through a major transformation...
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.