Why will data usage redefine the consumer journey?

Digital transformation has emerged as one of the main drivers of retail today, requiring companies and brands to invest in solutions for effective operations in the virtual environment. Digitization, in addition to strengthening and expanding the visibility of products and services, creates opportunities for innovation in the shopping experience, contributing to a projected value of over US$100 trillion for the global economy by 2025, according to data from the World Economic Forum.

The advancement of Big Data is a clear example of this transformation, enabling the identification of consumer behavior patterns and preferences. Through the massive cross-referencing and analysis of data, it has become possible to personalize offers and target campaigns individually, providing a more relevant and engaging shopping experience. It's worth noting that a key difference between the use of business intelligence and big data, in addition to the volume of data, is the ability to make decisions based on current, not just past, data, given the high processing power of Big Data technologies. 

One of the most notable examples of this resource is Amazon, which uses algorithms to suggest products based on previous purchases and each user's profile—sometimes even creating recommendations based on products already in the cart. It's no surprise that, according to analyst Mordor Intelligence, the Big Data market in the retail sector was estimated at US$1,400,000 (T$6.38 billion) last year and is projected to reach US$1,400,000 (T$16.68 billion) by 2029. If this scenario is confirmed, this amount would represent an average annual growth of US$21,210,000 (T$3,38 billion).

Operational efficiency also benefits significantly from intelligent data management. Tools that optimize inventory control, demand forecasting, and logistics are essential for anticipating consumption trends and maintaining optimal operational levels, avoiding excess or shortages of supplies. Furthermore, it's important to highlight the integration of multiple sales channels—or, in other words, the much-discussed omnichannel approach—which allows consumers to seamlessly transition from an online store to a physical or mobile store. This allows for a seamless purchasing journey and facilitates the completion or even re-sale of the transaction. 

Some of the world's largest retailers have a predictive logistics algorithm that combines user location data, page traffic for specific products, shopping cart data, and estimated conversion rates to speed up the fulfillment process (the set of logistics operations that go from a customer's order to product delivery). This allows products to be sorted in the logistics warehouse before the items are even purchased.

But beyond the impacts on operations, how can we also increase customer loyalty through data? First, by capturing customers who tend to be more loyal. It's possible to analyze a company's historical order base and understand which items brought in customers with the highest repeat purchases. Implement a price elasticity strategy for these items, understanding the ideal pricing. versus existing competition to increase the conversion of these loyal consumers. 

A second point is to understand what motivates customers through data, which can be done by conducting customer surveys and using gamified solutions with offers based on the results of this study. The most recommended method for using this survey is Octalysis, with questions like: What are my customer's goals? What fulfills my customer? What empowers my customer? What generates a sense of ownership? What influences my customer? What sparks curiosity? What benefits and advantages would my customer never want to miss? By collecting this data and building a retention strategy, loyalty results will certainly increase.  

However, Big Data doesn't drive this revolution alone or in isolation. Other resources—and here, of course, we need to emphasize the leading role of artificial intelligence (AI)—are taking on the role of a fundamental competitive differentiator for brands. AI-driven optimization can lead to cost reductions, improved operational efficiency, and a host of other benefits, but it's digital optimization driven by more sophisticated assistants that truly has the potential to revolutionize business models. 

At this point, it's important to differentiate between what we call AI optimization and digital transformation. The former focuses on increasing operational efficiency, reducing costs, and maximizing revenue through scale, but without impacting the core operations. Now, digital transformation implies a complete change in the company's business model, impacting products and the core business of the company. In other words, when we talk about retail, it's important to understand that technology, especially AI, has revolutionary power. Therefore, to make the most of it, we need to go further and seek more interactive and personalized tools.

However, technological advancement must go hand in hand with investments in data security and privacy. Protecting sensitive information through biometric authentication, encryption, and automated fraud detection systems will be essential to maintaining consumer trust and data, as well as safeguarding brand reputations.

The fact is that companies that effectively integrate continuous research, Big Data, and the most up-to-date technological resources will be better positioned to meet consumers' high expectations. In a constantly evolving market, digitalization is the best way to transform challenges into business opportunities.