BPM Analytics
Tag Management Systems: Enhancing the User Experience Through Intelligent Data Capture
Brands seek to understand the customer’s journey on digital interfaces to personalise their offerings, and an effective tag management system (TMS) is vital to this undertaking. Web or marketing tags are pieces of code that are inserted into a brand’s website or app to collect data such as page views, IP address, time on page, or links viewed. Tags allow marketing executives to measure performance, track KPIs, compare channels, and analyse website design efficacy. Tag management systems are interfaces that facilitate the setting up, organisation, rule definition, and deployment of tags.
Applications of TMS in Marketing
Omnichannel businesses execute a wide variety of marketing campaigns through social media, affiliates, search, and email, and deploy different tracking systems. Tag management systems help monitor these marketing exercises, which can get complicated. The most significant advantage of using a TMS is enabling non-technical marketers to manage tags without the involvement of an IT professional, significantly reducing associated costs. It allows them to add, edit, remove, or test tags without modifying the website code script. Other features of TMSs are faster websites due to the asynchronous loading of tags, built-in tag libraries, identification of tags that slow down websites or are non-compliant, and flexible rule engines.
An evolving technology
Tags are the backbone of digital marketing strategies, but there are cons too. Primary among these is the latency added to the website due to the overhead of loading third-party tag code and the consequent degradation of user experience. By putting third-party code on the site, control of data collection is handed over to the vendor, which can cause privacy issues. Complying with privacy regulations across geographies is more fraught with complexities as the vendor controls the data collection. Piggybacking, or tag redirects, is when a container tag on a website refers to other tag pieces of code that are not directly put on the website. Piggybacking can cause unauthorised data collection, non-compliance with privacy regulations, long website load times, and data loss.
How can AI and machine learning enhance tag management systems?
AI-based systems are trained on data models, and there is a vast volume of marketing tags training data across sectors. They can provide intelligent recommendations regarding the pertinent tags for a digital customer interface based on function, industry, historical patterns, and usage. The recommended tags generate customer data that will lead to valuable insights for improved campaigns and, thereby, more conversions. Deployment of tags can be taken over by smart solutions that analyse structure, content, and layout and use insights derived from training data models to configure and place tags appropriately. These systems can go a step further and dynamically manage tags. They can adapt and adjust in real-time depending on conditions and user behaviour.
For example, certain tags may not fire if the website loading time exceeds a certain threshold. Tags might be inserted or removed subject to customer actions like completion of the purchase, navigation changes, or shopping abandonment after adding to the cart. This real-time and dynamic insertion and removal helps collect relevant data which is more likely to reveal actionable insights that help deliver personalised user experiences while ensuring minimum negative impact. Automated audits of tags will prevent non-compliance, unauthorised data transfers, data loss, and long loading times. Predictive analytics systems can detect anomalies, inaccuracies, and inconsistencies in the data from the tags and, by doing so, help maintain data integrity and reliability. TMSs are now integrated with consent management platforms, and this allows users to deny or grant permission to gather information, the consent choices are passed on to the TMS, and tags are placed in compliance with the user consent.
TMSs will have to deal with the third-party cookie phase-out announced by Google for its Chrome browser. The alternatives are a universal identifier, a unique identifier for a customer that can be used across websites, or a browser fingerprint, identification using technical features like IP address, browser version, and language settings. Server-side tagging is another relatively newer feature for TSMs. There is a cloud-based server tag container. The server container is an intermediate between the website tags and the third-party endpoints. The server tag container accepts all the data-sending requests from the website tag container, which allows for setting up processing rules before the data is forwarded to any third party. This redirection reduces the website client processing, improves the response time, enables privacy protection, and allows for data validation.
Tag management systems will continue to play a foundational role in a brand’s effort to personalise the customer experience by understanding customer behaviour. TMSs will use AI and predictive analytics to hone their offerings, improve data privacy, and comply with regulatory laws like GDPR and CCPA.
This article was first published on The Evolving Enterprises
