Retailers are constantly pushing to deliver omnichannel shopping experiences. In today’s post-COVID-19 world, it’s imperative to provide consumers with the same personalized experience no matter where they shop.
Real-time data distribution is the answer to this challenge. Read on to learn how retailers leverage event-driven architecture (EDA) to gain business efficiencies and deliver enhanced customer shopping experiences.
Personalized Experiences
When it comes to livestream shopping, today’s tech-savvy consumers expect personalization. Retailers must offer a seamless experience across every channel – online, in-store, and anywhere.
With e-commerce giants offering same and next-day delivery, brick-and-mortar stores must improve customer service to compete. To do so, they must have access to real-time data that can quickly identify and respond to changing contexts in seconds, not hours.
AI-powered personalization is one way that retailers can meet consumers’ expectations. Retailers can build personalized recommendations by analyzing users’ browsing or search histories, social interactions (likes, shares), physical store visits, and past purchases. This lets shoppers find what they need quickly and easily while helping brands increase conversion rates.
Retailers can also track shopper traffic patterns and deliver targeted ads in response to fluctuations in trends or events. For example, an air conditioning company can optimize search terms before a forecast heatwave and a fashion retailer can send shoppers coupons for similar items when visiting their competitors’ sites.
Finally, virtual shopping and clienteling technologies are transforming store associates into white-glove service providers capable of engaging with online and in-store customers. This is a win-win for retailers and employees as it helps keep people employed in stores while providing a flexible work schedule.
Real-time Inventory Management
One of the biggest challenges e-commerce brands face is needing more stock to fulfill orders. That’s why real-time inventory management is essential to stay competitive. Real-time inventory solutions automatically update stock levels as they move through the supply chain, allowing retail brands to optimize their inventory levels and avoid under or overstocking. This process is made even easier with the right software solutions that can recognize and predict trends like seasonality or a sudden spike in demand.
Aside from the obvious benefit of avoiding inventory discrepancies, real-time inventory management also offers more visibility into your supply chain. It lets you see your inventory’s full picture across all sales channels and locations. It also identifies any areas of concern, such as long production lead times or warehouse receiving timelines.
Another advantage of real-time inventory management is that it gives you a clear picture of your aging inventory, so you can prioritize the sale of slow-moving or seasonal products to avoid having them go bad before they can be moved to customers. As a result, you can save on holding costs and increase customer satisfaction. This is particularly important in today’s environment, where word of mouth and social media are the main drivers of brand reputation.
Streaming Analytics
Streaming analytics uses real-time data processing to create insights for many use cases. The ability to capture, process, and analyze data in real-time provides a new world of possibilities, including everything from Netflix recommendations to predictive maintenance for industrial machinery. Every industry that relies on data can benefit from the power of streaming analytics:
For example, imagine shopping at a physical store and being interested in a particular product. Your shopping experience could be enhanced if the location of the stock was automatically updated based on your proximity to it. This would save you time and effort and prevent you from revisiting the store if the item is out of stock.
Augmented Reality can also improve customer shopping experiences by enabling customers to try products on themselves before buying them. As a result, fewer products will be returned because they are the incorrect size or are unsatisfactory.
Streaming analytics also helps businesses cut preventable losses by allowing them to detect unusual activity sooner. Credit card companies, for example, use real-time data to detect suspicious transactions and immediately alert the customer to take action. Other examples of real-time analytics include tracking stock market movements and adjusting portfolio settings to capitalize on opportunities. Then, sensor data streams monitor factory machines to ensure quality, monitor field assets like trucks and oil rigs, track traffic patterns, and more.
Contextual Recommendations
Recommender systems drive personalized experiences, deeper user engagement, and powerful decision support tools in retail, entertainment, healthcare, finance, and more. Recommendations can account for up to 30% of revenue on some of the largest commercial platforms. A 1% improvement in recommendation quality can boost sales conversions and improve retention by providing customers with the information they most likely want and need.
Augmented Reality is expeditiously revolutionizing shopping experiences by enabling customers to interact and customize products more effectively, engagingly, and conveniently. With AR, customers can visualize how furniture, clothing, or appliances will look in their homes or bodies, helping them make confident purchasing decisions and reducing the likelihood of returns.
More and more retailers are leveraging the Metaverse to create innovative virtual shopping experiences that are on par with or better than physical store experiences. By enabling customers to shop using their avatars, they can save time, energy, and money. And they can also increase brand trust by providing a more authentic and trustworthy experience.
