The customer experience is shaped by all the consistent interactions across multiple touchpoints. "Untangling" these interactions and bringing them together requires the implementation of an efficient technical framework that enables data to be easily manipulated, empowering business teams and ultimately improving the customer experience. This approach is known as "data as a product."
Website, mobile application, social media, stores, advertising, chatbots, call centers… Your customers can engage with your brand in many ways. While this may seem like a cliché, it's important to emphasize because their opinions are molded and influenced by the sum and coherence of these elements; this is what we now call the customer experience, or CX.
The key to unifying these different engagement channels lies in data exploitation. Modern customer experiences require seamless communication between all data sources and user-facing touchpoints. However, this is where the challenge lies. Data sources have inevitably followed the organization's structure: marketing data is only fed and utilized by the marketing department, logistics data is solely handled by logistics, and so on.
This siloing also stems from the software itself, often built as "monoliths" that inherently tightly couple raw data and business data. Re-architecting your applications into decoupled microservices offers modularity, portability, and autonomy in exposing these data. The new and trendy concept of "datamesh" replicates this idea but applied to data.
However, it is crucial not to limit this approach to purely technical aspects. Data governance must be correlated with the overall business strategy. This is where common repositories such as "data lakes" or "data warehouses" coupled with data manipulation tools come into play to facilitate access. It involves establishing mechanisms for referencing and collaboration, aggregating customer insights, communicating and visualizing data, and creating operational dashboards – all usable by business teams without prior technical knowledge.
The key to success lies in creating the right framework to empower data owners and effectively manage their traceability, quality, and availability. This is what "data as a product" means.
This strategy offers multiple advantages for your CX: understanding prospects' context and enabling highly targeted personalization of offers, even opening the door to predictive analytics or AI!
