“To succeed, know what your customers want, even before they do.” An adage that every retailer knows by heart and a truth that drives the hyper-competitive retail industry – where continued customer engagement and loyalty could result in a 15% to 25% uplift in annual revenue.
Customers today expect nothing short of an exceptional and personalised experience: more tailored recommendations and offers, less templated emails and generic notifications – whether they’re shopping online or in-store.
Modern retailers often do have the data points needed to build a unified customer experience or the means to acquire more if needed. The challenge most face, however, is the inability to access and process data the very moment it’s created and then shared to multiple points across the business – when the value of the data is at its highest.
Real-time data processing is crucial for retailers wanting to leverage data to generate up-to-the-minute insights to inform decisions around retail operations and customer engagement initiatives.
Does this mean retailers without costly data tools are destined to fall behind? Not necessarily, when modern alternatives like data streaming exist. In this first of a three-part series, we’ll dive into how data streaming can help retailers, big and small, tackle data challenges that may surface in their quest to win the hearts and minds of today’s customers.
Unpacking data streaming for retailers
As retailers continue to digitise, they will inevitably generate greater volumes of data than ever before. Imagine endless streams of data – flowing in various states (in-motion, at-rest) and formats (structured, unstructured) – from sources like point-of-sale systems, e-commerce websites, and inventory databases to destinations across the business at lightning speed. This data holds immense value and competitive insights, but only if retailers can bring order to the ‘data chaos’ and access the right datasets for analysis.
To further complicate matters, legacy data processing methods are no longer viable in this fast-paced, non-linear data environment. Retailers can’t afford to spend days or weeks collecting, storing, structuring, and processing data in batches, especially not when consumer trends and preferences can change at a dime. Data handled this way risks quickly becoming stale, leading to outdated insights and a diminished competitive edge over more agile competitors.
Data streaming enables retailers to harness the full potential of their data explosion by providing real-time ability to access, process, and analyse data as it’s created and shared across business networks. Unlike traditional batch processing, which handles data in predetermined timeframes, data streaming continuously captures data-in-motion and stream processing transforms it into usable formats instantly with real-time data processing.
This allows retailers to derive continuous value from their data as it evolves, action on that data immediately, and to utilise real-time analytics for decision-making. By aggregating real-time data from multiple sources into events, retailers gain rich snapshots of system changes over time, helping track inventory levels or spot supply chain disruptions – critical factors in delivering an exceptional customer experience.
How does data streaming benefit retail?
Now that you understand how data streaming works, consider how data across your organisation can be leveraged to enhance the customer experience. A well-designed data streaming solution can provide a 360-degree view of customer behaviour by unifying their data across all channels in real-time – from what they searched online, to what’s in their shopping cart, and to what they purchased last week, whether online or in-store.
By leveraging this data, retailers can make smarter decisions on pricing, product assortment, and stock placement—all key to creating a standout customer experience. Omnichannel personalization becomes seamless, enabling retailers to deliver targeted offers, recommendations, and tailored content based on a customer’s real-time interests. The same processed data can also be integrated into retail AI solutions to engage customers with personalised notifications and offers on the online store.
How about efforts to streamline the efficiency of operations? With real-time data drawn and processed from across the supply chain, retailers stand to gain instant insights into inventory levels at different locations, incoming stock shipments, and outgoing deliveries. This continuous flow of processed information supports demand forecasting initiatives and facilitates just-in-time inventory management. Done right, data streaming could prepare retailers to better navigate busy and unpredictable events like Black Friday or Cyber Monday with greater agility.
With data streaming, retailers could even tap into their data as rocket fuel for rapid growth. Retailers like Instacart “experienced 10 years of growth in 6 weeks” by delivering a quality of service that continues to build trust and loyalty with their growing customer base – on the back of the right data streaming architecture.
There is opportunity for other retailers to do the same or more – but it all starts with a re-examination of their data strategy. As it stands, data streaming is a powerful method to turn their most abundant commodity into a competitive edge.
Next, I’ll be expanding on ways data streaming can enable retailers to improve both the in-store and online experience to sell more and remain top-of-mind among today’s customers.
Simon Laskaj is regional director for Australia & New Zealand at Confluent.