Marcelo Sturn, Retail Leader at Diebold Nixdorf Brazil, addresses data as the key success factor and talks about how companies can collect and store information at very low cost.
Executives, industry analysts and thought leaders agree that we live in the ‘data era’. Nowadays, companies can collect and store vast information at a minimal cost. As a result, the volume of data gathered from electronic devices and connected sensors is substantially growing.
In the retail sector, this flood of information goes to an even higher level with loyalty campaigns, increased online transactions, flash offers, price scanners, electronic shelf labeling and even security control challenges when employees can use their own devices (Bring your Own Device – BYOD).
When discussing large quantities of data in retail, many people might also think of Artificial Intelligence (AI). And why not? We already see the arrival of this technology in modern self-service ATMs, automatic age verification, facial recognition and confirmation of consumer preferences for product targeting and promotions.
There will be a reduction in payment queues with automatic item recognition and the presentation of fresh products on the checkout screen. Undoubtedly, these data-driven solutions will make grocery shopping increasingly convenient, reduce the need for support team interventions, cut costs and simultaneously enhance the consumer experience.
Furthermore, when managing and optimizing the daily operations of retailers, access to the database is crucial. Just think of operational information such as sales per square meter, customer retention rate, item turnover, average transaction value, employee performance, number of daily visitors or even average dwell time. There are many Key Performance Indicators (KPIs) that retailers need to monitor to keep their businesses profitable and competitive.
In this journey, data interpretation is a critical factor for success. The era of information collection is in the past, making way for a new one of analysis and understanding of how specific data can aid business performance.
It is advisable to extract meaning from the immense amount of information we have available. However, it is not easy to interpret it in a way that contributes to retail success without first having a clear strategy and smart tools that make the analysis assertive and more efficient.
In this context, I understand that we have three significant challenges. The first is related to silos, where data is typically stored. Historically, different stages of customer journeys collected other types of information stored in separate databases. This situation persists to this day.
Surprising as it may seem, customer data remains with sales, promotional actions stay with marketing in CRM systems, transactions stay in a Point of Sale (POS) repository for legal or fiscal use and inventory is in the back office.
Generally, the digital structure used in e-commerce is entirely separate from the physical operation of companies. Thus, the communication between departments and data integration into a single corporate framework does not happen in many Brazilian companies.
The second challenge relates to data quality. Separate structures with isolated data tend to be in different formats, which makes combining and comparing the information more difficult. Moreover, data is not always up-to-date, consistent and complete when saved in diverse sources. Practical examples include loyalty campaigns tracking customer details but not always having the latest registered address, despite updated customer data in e-commerce systems. Therefore, alongside silos, data quality represents a significant problem for retailers.
The third challenge is analysis. Time availability is essential to make information actionable. Sufficient resources are needed to analyze and interpret the data first.
Retailers struggle with complex and time-consuming processes based on outdated data, which seriously impacts decision-making, especially when it needs to happen immediately, in real-time. In pursuit of business success, it is necessary to use solutions that provide access to a robust data analysis and visualization platform so new strategies can be efficiently and effectively implemented based on facts.
By eliminating data silos and cross-referencing information, Brazilian brands will achieve better performance and accuracy in their business, transforming data into tangible commercial value.
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