In 2018, machine learning and its game-changing capacity for automated predictions of visitor behavior and purchasing trends currently dominate digital personalization. Machine learning’s flame is burning bright, but whether it can deliver the competitive edge depends on overcoming a key challenge: the need for structured, accurate, and consistent data. This is the gold dust of machine learning because the quality of every model depends on the data that feeds it. You can train and retrain a model ad infinitum, but it is doomed to failure if your data is poorly structured, inaccurate, and inconsistent.
Enter the data layer — an object of infrequent discussion, understood by few, but so fundamental to machine learning and the data-driven decisions that power high-impact and scalable personalization.
If personalization is a journey that takes us down the road to understanding customers, their purchasing habits, wider browsing behavior, and likely future trends, then the starting point on this journey is the data layer. If you set out on the wrong foot without a correctly implemented data layer that’s aligned with business requirements and goals, it will be painful and costly. You will achieve nothing more than inconsistent data, overly intensive manual data processes, and undelivered promises.
This is why it is important to begin the journey with a well-implemented data layer — not one plucked from thin air without a sound strategic basis, but one based on a well-thought-out plan, communicated across your business, with clearly defined goals. This is the key to personalization, not machine learning or AI. Those are merely tools. They can offer nothing without the business-critical information that drives them.
Stated simply, a data layer is a dynamic and flexible container for all the useful information you want to collect from each of your website’s pages. When we talk about “useful information,” we are referring to data points.
On a more technical level, a data layer is a collection of key data points exposed via a suitable data structure on the frontend of the website with JavaScript. Consisting of key/value pairs, the data layer is typically updated on key events, such as a page rendering, a login, a signup, a product view, or a transaction. The complexity can be a single variable, such as a user id, or multiple nested variables, often seen with product or transaction data.
How do you know what data points are important on a page? The answer to that is straightforward: It’s whatever is important to your business. Answering the following questions is a great place to start.
The starting point for implementing a data layer is, therefore, a wider business discussion that incorporates a clearly defined strategy, encompassing business requirements and goals. Defining the “why” informs the “what,” not the other way around.
