[Catch part one of this three-part series on how data streaming empowers retailers to turn data in motion into powerful insights that drive customer loyalty and engagement here.]

Modern retail stores have evolved far beyond being mere combinations of brick, mortar, and product. Today’s physical storefronts are data-rich environments where point-of-sale systems, inventory management tools, and other in-store devices continuously generate and process streams of data in real-time. But the retail data explosion isn’t just limited to these sources. Another source walks through its doors and peruses its shelves every day: its customers.

These customers tend to be digital natives who expect seamless and personalised omnichannel experiences from phone to store. Over 74% of shoppers expect high levels of personalisation in return for the data they share, and over 80% value a personalised retail experience as much as a retailer’s range of offerings, according to Salesforce. This demand for ‘anytime, anywhere’ omnichannel experiences that are personalised is what drives customer loyalty considerations today – and the data strategies of modern retailers.

Taming and tapping into retail’s never-ending data flow to enable meaningful personalisation has never been easy. Retailers must find effective ways to access and process data in real-time, so they have the customer information needed to provide tailored in-store offers or value-adding services like product reservations for in-store pick-ups. To achieve this, a data streaming solution is necessary.

Unlocking data’s potential beyond the storefront

Traditional batch processing via point-of-sale and inventory systems, typically run at the end of the day, cannot meet the real-time demands of omnichannel personalisation. Customer insights generated this way are often stale and outdated by the time they are ingested, stored, and processed.

To respond to in-store personalisation opportunities as they arise, retailers will benefit from data streaming solutions that simultaneously process, store, and analyse data in motion – allowing retailers to strike when customer interest is at its highest.

Free from the constraints of legacy data solutions, retailers can unlock greater on-time value from their data with data streaming. Data streaming technology enables on-the-fly integration and processing of in-store data alongside other data events, such as online purchases or web searches, to create a unified view of a customer.

With real-time analysis, retailers can obtain the customer insights they need to instantly respond to in-store customer visits, by delivering personalised recommendations based on their previous interactions across all channels.

Retailers can enhance engagement further by processing customer location data – using geofencing or mobile-based location services – to automatically send alerts about product availability or location-based promotions whenever a customer is near a branch.

Integrating e-commerce data with customer data allows retailers to provide tailored recommendations and more fulfilment options – further improving convenience and creating a seamless omnichannel shopping experience relevant to individual customers.

Supercharging customer interaction and engagement

How can near-instantaneous data processing and analysis transform customer engagement and loyalty for retailers? For starters, having real-time insights at their fingertips empowers in-store employees to respond quickly and proactively to customer needs. Here are a few ways this can enhance the in-store experience:

  • Targeted white glove service: Retailers can use data streaming to analyse customer purchase frequency and preferences across digital and in-store channels, for a clear understanding of each customer’s value to the business. This enables retailers to tailor varying levels of “white glove” service based on loyalty. Premium experiences can be offered to top-tier customers, while loyalty-building experiences can be designed for repeat customers to nurture them into becoming long-term brand loyalists.
  • Seamless in-store purchases: Whenever a store lacks the product size or colour desired by a customer, employees can quickly pull up supply chain data on their device to check for stock at other branches, place the order, and arrange for purchases to be delivered to the store – or directly to the customer’s home. The convenience and service quality provided is sure to delight customers and build loyalty.
  • Flexible fulfilment: When a customer places an order on a retailer’s e-commerce platform, data streaming allows transaction data to be instantly cross-checked with stock at nearby stores. This capability enables retailers to offer seamless options like buy online, pick up in-store (BOPIS) and curbside pickup. Over 38% of Australian customers are more likely to make additional purchases when picking up in-store, making this approach a cohesive shopping experience and a revenue booster for retailers.
  • AI-enhanced recommendations: Data streaming enables the continuous processing and preparation of data across a retailer’s omnichannel network, ensuring AI solutions have the high-quality and relevant data they need to create the most relevant offers and recommendations for customers. By integrating data from CRM systems and streaming it in real time, retailers can deliver the same consistent, personalised recommendations through chatbots on e-commerce platforms or apps – building customer engagement and loyalty while increasing sales at the same time.

These are just a few ways data streaming can empower retailers to capture and nurture customer loyalty. As new technologies emerge and customer expectations evolve, more possibilities will arise.

In the face of these changes, data streaming will remain essential for unlocking the full value of data – enabling retailers to keep in-store experiences fresh, relevant, and engaging for future shoppers.

Simon Laskaj is regional director of Australia & New Zealand.