Google Cloud

Revamping experience-based retail with IoT

Online retailers increasingly opt for clicks-to-bricks strategies. Also, research shows that over half of consumers are first visiting stores to feel, see, and try products before buying them online. Opening brick-and-mortar stores provide online retailers with new opportunities to reach out to their customers. This article describes how the Internet of Things (IoT) can help with a seamless shopping experience for click-and-brick stores using experience-based retailing.

First of all

IoT is the all-encompassing term used for machine-to-machine (M2M) connectivity. In other words, sensors exchanging data with different devices. Think about an app closing the curtains automatically for you at sunset. Convenient, isn’t it? But IoT's true potential is much bigger. When IoT systems are used along with AI and data analytics at full power, this highly valuable data will turn into concrete insights of, for example, consumer service. 

Since this may sound quite complicated, Google Cloud Platform has created IoT Core. IoT Core helps with IoT device connectivity and management. Use sensor data streams for advanced analytics, visualizations, machine learning, and more to help improve operational efficiency, anticipate problems, and build rich models that better describe and optimize your business. All without thinking about complicated infrastructure.

Excellent customer experience

Thanks to the powerful combination of IoT, AI, and data analytics, the in-store shopping experience can gain extreme boosts. We have three innovating examples of how IoT, AI, and data analytics can leverage your customer experience.

First, IoT sensors can monitor the movement of consumers, and the frequency of viewing, touching, and buying a product. Through this knowledge, retailers can gain insights into local demand and decide which new items to add to their inventory, or how their store layout can be optimized.

Second, displays could also be used in collaboration with a camera sensor to recognize a product and provide a description to the customer. This could vary from a food description, nutritional information, alternatives, or related goods that would complement the product. 

Finally, location-based marketing could be used to attract customers with an advertisement in their phone’s notification bar when they pass the store. This could be with a one-time offer or by showing a product that they have been looking for.

With these three examples, customers will walk into a store with an inventory and layout optimized for their local community. Additionally, product awareness and transparency are promoted by providing more information on products. At last, customers are increasingly selective on which branded messaging they interact with. With personalized deals at appropriate times, their overall experience is enhanced as a result.

Case study: Trax

Trax is a world leader in computer vision solutions for retail. Capturing shelf data in real-time through wireless IoT cameras, Trax puts the power of out of the shelf and low stock alerts in the hands of store staff. Powered by cutting-edge Computer Vision technology, their solution helps retailers optimize replenishment, accelerate order picking, and uplift customer satisfaction.

 

Interested? IoT Core supports businesses with hassle-free IoT connectivity. Start measuring operations in real-time, and gain groundbreaking insights.

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