Tag management is a way to add, edit, and remove tags from your website. The most common forms of tags (small piece of code) are for web analytics, search engine marketing, ad serving, and testing; however, there are many other types. These tags are usually in the form of JavaScript. Tag management systems provide you with flexibility to combine these tags into a single tag and control the deployment of the tag from a console, not directly on the website.
In my opinion, it depends on the type of website (content management systems or “hard coded” websites), your marketing tactics, website performance, security policy, and business strategies. If you are not proactively looking to measure all marketing initiatives, then you’re not ready for tag management and you need to start measuring. If you have more than 1 million pageviews to your website and 3 different types of JavaScript or tags on the website, then you might want to consider tag management. In addition, if you have specific needs such as poor load-times, industry security issues, or to make a strategic decision to empower your marketing team, I would recommend looking into a tag management system.
Types of Tags supported by Tag Management Solutions
There is a variety of implementation methodologies, but most vendors use client-side tag implementation. A few use server-side tag management and a combination of client-side & server-side tag management. Both options use JavaScript tags; however, the main difference refers to where most tags are fired, either at the browser or server level.
Most tag management solutions have partners with prebuilt common tags to implement quickly and save you time. There are often workflow and user administration features to manage users and processes to manage quality assurance as well as approvals to launch tags. The uses of simplified user interfaces make it easy for everyone to use the tool. There are also reports to see if the tags are working effectively. Many vendors give you additional features for auditing, conversion analysis, and attribution modeling.