In today’s exceptional situation, the use of digital channels by users has grown exponentially. Besides being a test of resilience to the organizations that hold them, it is also a business opportunity and a technological evolution for all stakeholders.
The period of confinement has resulted in an unexpected flow of users in several digital channels, among which we can highlight e-commerce websites, media, entertainment sites and channels of general content. This situation that at first glance could be perceived as a positive impact for organizations, is in many cases a challenge that can generate misinterpretations of interaction dynamics (user-item and user-Channel), culminating in processes inefficiencies such as customer service, inaccuracies in content segmentation and constraints in the functioning of the business.
Whenever a user accesses and interacts with one of these channels, it generates a digital footprint that is sometimes not analyzed in an integrated way due to lack of visibility or lack of capture processes, but which are crucial for the knowledge and growth of the business
In the market, there are some Black Box solutions that allow you to create a set of predefined metrics for customer actions and behavior, such as Google Analytics. However, these solutions are limited in terms of types of events that can be generated, and the vast majority run on statistical samples of actual traffic.
From this perspective, the solution can and should go through the creation of customized models of event capture and analysis (Data Stream Pipelines), which in this way makes it possible to effectively track the behavior of users and their interactions with digital channels. By creating customized events, that is, metrics specific to the business context, these interactions can be customized and the data can be transformed into great opportunities for organizations in terms of both offering and providing value-added services
How are Data Stream Pipelines created?
The creation and automation of these data flows is a process that involves an end-to-end solution. As a first step, a survey of requirements and business objectives, including a definition of the events and Kpis to be consumed and analyzed, is essential to later culminate in the creation of analysis processes and/or algorithms, that using artificial intelligence/ automation mechanisms, will ensure the continuous reading and transformation of data into important outputs for decision making.
The creation of a custom Data Stream Pipeline makes organizations 100% owners of the data generated on their websites and applications in the first instance, assuming that on other platforms the data is shared with third parties. Additionally, businesses gain flexibility to customize and define the information that is displayed and relevant to their business, based on real traffic results.
How can the data support the business?
Depending on the maturity of the business, various metrics can be analyzed and sets of events can be created to understand the different stages of interaction, such as product impressions, page views, clicks and conversions. Through the convergence of data it is possible to define user profiles and segments for the different offers, also taking into account geographical and demographic metrics that allow the subsequent personalization of the content.
Finally, the possibility of integrating more than one source of information, i.e., centralizing the analysis of data from various digital channels, such as websites, apps, blogs, social networks, on a single platform, should be highlighted.
One of the great advantages of digital is the technology and analytical capacity it provides. With data we make better decisions and interact with the public in a personalized way at a lower cost. Are you really getting a 360 view of the users of your digital channels?
*Published in IDC