I have heard someone say that life was much simpler
when Apple was only a fruit and we just had to worry about one web analytics
tool for our web site. Apple, the company, and proliferation of digital
technologies have turned everything upside down - in a good and exciting way.
Talking about digital data quality is not considered as hot as talking about analytics, big data or machine learning. Probably, that will never change! But I am sure companies will do more about the digital data quality in the future than they do with it today. In the end, data quality is one of the underlying foundations for better reporting, analytics and decision making.
Everybody agrees about the importance of data quality but collectively we probably need to figure out an overall strategy from a data quality perspective. Who can argue about the need for your digital data to be accurate, relevant, complete, timely etc.? Haven’t we worked on data quality, data lineage and data stewardship for more than a decade in an offline world of datawarehouse, MDM and CRM? We still have, however,a long way to go in a digital world as far as data quality is concerned.
We definitely have become smarter, more practical and more sensitive about data quality. We have also learned to live with imperfections and realize that 5-10% discrepancy is probably acceptable given the huge effort required to fix it in a real world. We are also learning to understand how to improve data quality iteratively by understanding the gaps, shortcomings in the process, developing feedback loops etc. But more methodical and structured approach is required to improve data quality instead of reacting to it after a glaring discrepancy in any critical report.
Before we talk about data quality, we need to talk about digital data collection process. You collect data with the help of tags. For those who are not aware, a tag is a simply a chunk of code —usually JavaScript — that performs the task of data collection for various purposes. It has always been painful historically as it was very hard to make it agile both from business and IT perspective given the constraints of release cycles in an enterprise environment. Unfortunately, the level of complexity in managing it manually without a tool and the effort behind it is sometimes not recognized. All of this has been changing in last few years with the new category of tools called Tag Management Systems.
For those who are new to this area, using a Tag Management system lets marketers easily insert snippets of code, called tags as mentioned above, which enable third-party tracking, analysis, reporting, remarketing, conversion tracking, optimization, and much more. A marketer can log in to the tool themselves and add, edit or delete tags as they see fit, without needing code-level access. To make it even simpler, these technologies have already integrated with other ad-tech companies, so the marketer can now just tick a box to activate the appropriate tags. Tag managers allow marketing to have control over their own little space on a web page. For example sake, if you have 5 to 20 tags on any given page then they are replaced by a single container in a Tag Management System. That container contains code that listens to rules dictated in the tag manager's backend as to when to fire what tags. The Tag Management systems can also do some cool things like reducing cost to POC a new tool in your ecosystem; correction of campaign issues in real time among many others. Innovative techniques like data layer is being implemented by companies which separates data collection, manipulation and delivery from web page structure. Data layer defines events and information uniformly across the site – basically a consistent place to store and retrieve data values so that different tags can easily and quickly find the same piece of data.
The world of tag management continues to gain more traction. The recent 47.2 million dollar funding of Tealium – one of the leading tag management vendor – validates the upside of this new space. There are dozen vendors like Tealium, Tagman, Ensighten, DC storm, Site tagger, Google Tag manager etc. with their own strengths and weaknesses and often rated based on number of tags they can support among other criteria.
But before you plan your tag management strategy, don’t you need to think about the existing tagging gaps and errors in your web pages? Even if you bought a brand new tag management tool today, you will still have existing tags throughout your website deployed probably in the last decade. The most common tagging problems are incompletely deployed; incorrectly configured; not configured; duplicated and non-removal of old tags. How do you know where to start to implement your new Tag Management tool? Basically, you need to audit your existing web pages landscape in order to develop any approach.
A tag auditing tool like Observepoint enhances your investment in the tag management solution - It doesn’t matter which tag management tool you own. An improperly deployed data collector can result in broken web pages, loss of site traffic and subsequently lost sales – you definitely want to prevent all of it from happening. If you worry about compliance then there is also a risk of data leakage also if tags without permission are deployed or not removed by mistake.
Even if you own Observepoint and generate reports with it, you still need to define your digital data quality governance process to make it work. There is no standard way of doing it as all of it is new and every organization is different. There are many questions to answer! You still need to define who owns to fix various issues identified in the audit report? How do you prioritize? How do you know it is working well? Do you know who owns digital data quality in your organization? Should the team who is collecting and normalizing data be responsible for data quality? Should it be your Analytics team, IT team, QA team or different business units should be accountable for every type of tag/data? What should be the frequency of your audits? Who makes a decision whether it is critical issue or not after an alert from your tag monitoring system?
We do need to recognize the learning curve in the world of tag management and auditing as it is still not mature. Enhancing digital data quality is a hard job and often tedious for the people who work hard for it. But it can be very rewarding in the long run! Also, improving digital data quality is a collective responsibility – not something which can be just owned by your analytics or your IT team though they can certainly lead the effort.
Talking about digital data quality is not considered as hot as talking about analytics, big data or machine learning. Probably, that will never change! But I am sure companies will do more about the digital data quality in the future than they do with it today. In the end, data quality is one of the underlying foundations for better reporting, analytics and decision making.
Everybody agrees about the importance of data quality but collectively we probably need to figure out an overall strategy from a data quality perspective. Who can argue about the need for your digital data to be accurate, relevant, complete, timely etc.? Haven’t we worked on data quality, data lineage and data stewardship for more than a decade in an offline world of datawarehouse, MDM and CRM? We still have, however,a long way to go in a digital world as far as data quality is concerned.
We definitely have become smarter, more practical and more sensitive about data quality. We have also learned to live with imperfections and realize that 5-10% discrepancy is probably acceptable given the huge effort required to fix it in a real world. We are also learning to understand how to improve data quality iteratively by understanding the gaps, shortcomings in the process, developing feedback loops etc. But more methodical and structured approach is required to improve data quality instead of reacting to it after a glaring discrepancy in any critical report.
Before we talk about data quality, we need to talk about digital data collection process. You collect data with the help of tags. For those who are not aware, a tag is a simply a chunk of code —usually JavaScript — that performs the task of data collection for various purposes. It has always been painful historically as it was very hard to make it agile both from business and IT perspective given the constraints of release cycles in an enterprise environment. Unfortunately, the level of complexity in managing it manually without a tool and the effort behind it is sometimes not recognized. All of this has been changing in last few years with the new category of tools called Tag Management Systems.
For those who are new to this area, using a Tag Management system lets marketers easily insert snippets of code, called tags as mentioned above, which enable third-party tracking, analysis, reporting, remarketing, conversion tracking, optimization, and much more. A marketer can log in to the tool themselves and add, edit or delete tags as they see fit, without needing code-level access. To make it even simpler, these technologies have already integrated with other ad-tech companies, so the marketer can now just tick a box to activate the appropriate tags. Tag managers allow marketing to have control over their own little space on a web page. For example sake, if you have 5 to 20 tags on any given page then they are replaced by a single container in a Tag Management System. That container contains code that listens to rules dictated in the tag manager's backend as to when to fire what tags. The Tag Management systems can also do some cool things like reducing cost to POC a new tool in your ecosystem; correction of campaign issues in real time among many others. Innovative techniques like data layer is being implemented by companies which separates data collection, manipulation and delivery from web page structure. Data layer defines events and information uniformly across the site – basically a consistent place to store and retrieve data values so that different tags can easily and quickly find the same piece of data.
The world of tag management continues to gain more traction. The recent 47.2 million dollar funding of Tealium – one of the leading tag management vendor – validates the upside of this new space. There are dozen vendors like Tealium, Tagman, Ensighten, DC storm, Site tagger, Google Tag manager etc. with their own strengths and weaknesses and often rated based on number of tags they can support among other criteria.
But before you plan your tag management strategy, don’t you need to think about the existing tagging gaps and errors in your web pages? Even if you bought a brand new tag management tool today, you will still have existing tags throughout your website deployed probably in the last decade. The most common tagging problems are incompletely deployed; incorrectly configured; not configured; duplicated and non-removal of old tags. How do you know where to start to implement your new Tag Management tool? Basically, you need to audit your existing web pages landscape in order to develop any approach.
I still think that
importance of tag auditing is not well understood because first it is new as
well as process around tag auditing needs a broader conversation across
different business units. Using a tool like Observepoint, founded by John
Pestana (cofounder of Omniture), to audit your website can be a good option. There are few other
tools also in the marketplace if you want to explore. Tag auditing is about validation and identifying
tag placement and configuration problems. It helps you find missing tags; tags
which are not firing and incorrect variables and parameters. And it presents its
finding in an easy-to-read reports.
There are two components of a tag audit – a site scan and
monitoring. During the scan, the system tests the web site and catalogs tag
data for every page. The monitoring component – also called as “simulations” –
is put into place to detect sudden disappearance of tags, or unexpected tag
variable changes.A tag auditing tool like Observepoint enhances your investment in the tag management solution - It doesn’t matter which tag management tool you own. An improperly deployed data collector can result in broken web pages, loss of site traffic and subsequently lost sales – you definitely want to prevent all of it from happening. If you worry about compliance then there is also a risk of data leakage also if tags without permission are deployed or not removed by mistake.
Even if you own Observepoint and generate reports with it, you still need to define your digital data quality governance process to make it work. There is no standard way of doing it as all of it is new and every organization is different. There are many questions to answer! You still need to define who owns to fix various issues identified in the audit report? How do you prioritize? How do you know it is working well? Do you know who owns digital data quality in your organization? Should the team who is collecting and normalizing data be responsible for data quality? Should it be your Analytics team, IT team, QA team or different business units should be accountable for every type of tag/data? What should be the frequency of your audits? Who makes a decision whether it is critical issue or not after an alert from your tag monitoring system?
We do need to recognize the learning curve in the world of tag management and auditing as it is still not mature. Enhancing digital data quality is a hard job and often tedious for the people who work hard for it. But it can be very rewarding in the long run! Also, improving digital data quality is a collective responsibility – not something which can be just owned by your analytics or your IT team though they can certainly lead the effort.
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