10/09/2024 | Press release | Distributed by Public on 11/09/2024 01:55
Digital Transformation Is Increasing the Amount of Retail Data-but That Data Is the Key to Delivering Exactly What Consumers Want
By Sean Yang| Sep 10, 2024| All, Featured, Technology
Today's consumers expect a lot. They're accustomed to fast, convenient, personalized shopping experiences that span every available channel, from making purchases via a mobile application to in-person browsing at a brick-and-mortar store.
Since the global pandemic, those expectations have only been reinforced. Before 2020, e-commerce rates were growing by about 10% to 15% annually. When lockdowns, store closures and social distancing became the norm thanks to COVID, online shopping activity skyrocketed. In just a single year, e-commerce increased by 43%, expanding from over $571 billion in 2019 to more than $815 billion in 2020.
While most shoppers are no longer required to quarantine, e-commerce is still growing-and so are the other digital enhancements retailers implemented during the pandemic, such as curbside pickup, buy-online-pickup-in-store (BOPIS) and home delivery. That can make meeting consumer expectations a growing challenge for companies that are in the early stages of their digital transformation. That's because succeeding at e-commerce and delivering the shopping experiences consumers demand requires a LOT of information.
Data is every modern retail organization's (not-so)-secret weapon. It's the key to unlocking ultra-valuable insights that help companies cater to customers in brand-new and exciting ways. Data can reveal the unique behaviors and preferences of each targeted audience. It can help retailers know:
If retailers don't know their customers in the above ways and more, they can't deliver the experiences that keep customers coming back.
Every decision a retailer makes in how it operates has an effect on customers. Data can not only tell retailers about their shoppers, it can also help them optimize and streamline internal processes, improve inventory management and supply chain logistics, make employees more productive and efficient. Improving operations in any of these ways empowers the retailer to do a better job with customers and give them what they want faster, more conveniently, etc.
As retailers continue to adopt digital tools to enable and simplify e-commerce and traditional shopping alike, they are becoming deluged with data from all sides. They get high volumes of information from sources such as in-store point-of-sale systems, online reviews, supply chain systems, inventory tracking applications, social media, e-commerce stats, call center logs, sensor data in delivery vehicles and store surveillance cameras.
Of course, it's not enough to simply have all of that data. It needs to be aggregated, stored, analyzed and managed for it to make sense. That requires robust data storage solutions and a range of technologies and tools.
The main technologies that enable retailers to extract the value from their massive volumes of data include the Internet of Things (IoT), AI and machine learning, data analytics and wireless connectivity. Let's take a closer look at each of these technologies.
Internet of Things
The IoT enables the collection of raw data from sensors or other devices. For instance, in-store surveillance cameras can capture real-time footage of customer behaviors such as foot traffic, how they move through a store location, where they stop and what they pick up. Sensors are often placed in vehicles to monitor delivery conditions or measure environmental factors like vibration or temperatures to ensure that certain perishable or fragile products arrive intact. These cameras, sensors and other monitoring devices often transmit the collected data to a central repository for storage, analysis and more.
AI & machine learning
Retailers are increasingly using AI and machine learning applications to parse data and get the insights hidden within it. Once collected, the stored data from all sources can be put through these systems, which process the data and identify patterns and detect anomalies to inform retailers how their customers behave. For instance, an IoT camera in a grocery store records how customers move through the store and which areas they stop at most. An AI application can process that information and give recommendations to retailers about where they should place certain products for more exposure and so on.
Data analytics
Data analytics often go hand-in-hand with AI and machine learning systems; in fact, they're often used together in the same solution. Data analytics takes raw information, processes it and offers up usable statistics or facts that retailers can use to improve processes and customer experiences. For instance, through data analytics, a retailer can discover that one specific product is returned more often than the others. Together with AI capabilities, a data analytics solution can offer insights into why that product is returned so often-say it's a piece of clothing and the primary reason for the return is that it doesn't fit right. The system can detect whether the item is improperly sized or whether there is another flaw in the product that keeps it from fitting correctly. These types of insights can be extremely valuable to retailers because it allows them to pinpoint issues and resolve them. The system can also show retailers what is working really well, too, so retailers can perhaps roll out those processes or practices to other areas.
Wireless connectivity (5G)
All of the above technologies require a strong, reliable network. Wireless connectivity is a critical component because it allows remote sensors and systems to transmit data and insights to retailers. While the full promise of 5G speeds and performance hasn't quite been realized yet, it will eventually transform wireless networks with massive improvements in data transmission and processing speeds. 5G's low latency and high bandwidth will also better support edge computing, in which some of the processing and analysis of data takes place right in the sensor or camera, for instance, itself rather than simply sending the data to a central hub.
With so much data needed to deliver the insights that allow retailers to improve customer experiences, there is also a great need for robust data storage and high-performance data access and management. Yesterday's hard disk drives can no longer support the data-intensive needs of technologies such as IoT, AI and machine learning, data analytics and 5G networking.
To meet these modern data storage and management needs, more retailers are turning to NAND flash-based solid state drives (SSDs) to make the most of their digital technology. SSDs are becoming an increasingly smart choice due to their:
Phison supports the data-intensive workloads of retailers with a wide range of NAND-flash-based SSDs and controllers. Each SSD and controller offers the high-quality features listed above and delivers industry-leading high performance and more.
Phison also has an excellent track record in SSD customization for some of the world's biggest retailers and brands. The company is committed to continual investment in R&D to ensure that its products remain on the cutting edge of innovation. Since its inception in 2000, Phison has been a pioneer in defining-and refining-performance and testing standards in its NAND flash controller and storage solutions.