E-commerce as a concept is straightforward enough. Aisles and aisles of physical products, now easily accessible digitally at a click of a button. But the digitization of shopping has opened the flood gates to turbulent competition. New concepts give raise to new entrants who can expand much faster as they don’t need to build a large physical footprint. Sure, us within E-commerce can battle, perhaps engage in discount wars, dropping product prices to lure the ever-fickle customer back and forth. But, the past has shown that ‘trust’, if gained, creates a far better and everlasting draw with a customer.
Within the paradigm of E-commerce, ‘trust’ aka ‘brand value’ is created through consistent customer and seller experience. Both are multi-dimensional, and are comprised of how the platform is perceived in terms of ease of use, relevance, and consistent delivery of products and services. Data sits at the coreenabling the platform to scale, providing the base for the millions of algorithmic decisions taken by the platform every second.
The use cases of such data can vary from understanding and communicating the expected delivery time of a package, to showing customers products they are likely to buy. To start, raw data, the lowest denomination in the data world, must be captured, synthesized, and then fed to algorithms and/or human decision makers. These processed data points provide a foundation on which we build and continuously improve customer and seller experience and processes.
Scaling with Data
With scale, E-commerce’s need and capability around data must involve. Disparate structured and unstructured data sources, and large volumes of it, must over time be unified, reaching towards a single source of truth.
Big data is the new oil, powering the e-commerce ecosystem
A second important consideration is the velocity at which data is processed and utilized. E-commerce firms often must evolve to become less reliant on manual checks and balances, moving towards near real-time systems to verify orders and their respective buyers and sellers. Such a feat requires both strategic thinking and infrastructure investment.
In the ‘thinking’ phase, it is important to understand both the nature of raw data gathered and the input needs of the systems that run daily operations. If you take a step back, often a data solution appears from defining and then analyzing the problem statement that the business is trying to solve. “We incorrectly charge for shipping costs because the product dimensions provided by the seller are incorrect”, is a problem statement heard in the industry. In testing various hypotheses, in creating a scale-able and preferably automated solution, one must understand the data that is readily available and the data that must be derived or further acquired. Therefore, the real complexity for a Data team is in planning and adapting how it collects, cleanses, verifies, analyses, and deploys that data into a constant and structured ‘data pipeline’.
Enabling through Data
Once you have data processes and systems in place, the next important piece is data enablement and data security. Data enablement is about empowering the business side in its’ day to day management of operations. Visualizations tools output structured and derived data that often help E-commerce professionals navigate deviations or trends in the business, e.g. why do electronics sell better on weekday nights?
Data security and the governance of data comprises a few components as well. Is everyone using the same data and do they have a consistent definition with regards to it? This topic also covers the firm’s understanding of individuals and systems that access the data and can modify it. Striking a balance between Data enablement and its security, managing speed versus validity, is an interesting and complicated task faced by CIO’s and their teams.
With the basics up and running and the recent acquisition and technical integration of Lazada into Alibaba Group, my role as CIO has evolved. Firstly, I must ensure our business and operational systems have the data needed to operate efficiently. Secondly, ensuring we leverage and learn from Alibaba’s capabilities and tools is paramount, and setting up teams to explore and educate our staff has become critical. Standing on the shoulders of giants is a fantastic position to be in and there is an enormous upside that we get through adoption and integration. But we must never forget to keep the business value of the technology at the forefront and not adopt technology for technology sake. In addition, we need to ensure we don’t become complacent on the back of new shiny machinery and continue to innovate at all levels of the organization.