While most shoppers are no longer required to quarantine, e-commerce is still growing\u2014and 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\u2019s because succeeding at e-commerce and delivering the shopping experiences consumers demand requires a LOT of information.<\/p>\n
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The power of data in retail<\/h3>\n
Data is every modern retail organization\u2019s (not-so)-secret weapon. It\u2019s 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:<\/p>\n
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- What channels customers prefer for browsing or making purchases<\/li>\n
- How customers prefer to communicate with the retailer<\/li>\n
- What their customers\u2019 values are\u2014do they want sustainable products? Local artisans? Best price?<\/li>\n
- Where the line between price and quality falls for their customers<\/li>\n
- When and why customers return products or buy from competitors<\/li>\n
- Which sales incentives best motivate customers\u2014discounts, loyalty points, gifts with purchase<\/li>\n
- When and why customers will write reviews on store and third-party websites<\/li>\n
- How customers see the retailer\u2019s brand and overall reputation<\/li>\n
- And much more<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
If retailers don\u2019t know their customers in the above ways and more, they can\u2019t deliver the experiences that keep customers coming back.<\/p>\n
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.<\/p>\n
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.<\/p>\n
Of course, it\u2019s not enough to simply have<\/em> 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.<\/p>\n
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Making use of retail data takes advanced technology<\/h3>\n
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\u2019s take a closer look at each of these technologies.<\/p>\n
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<\/a>Read: Data Storage and the Internet of Things<\/div><\/div><\/div><\/div><\/div>\n<\/p>\n
Internet of Things <\/strong><\/p>\n
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.<\/p>\n
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<\/a>View: Phison aiDAPTIV+ Solution<\/div><\/div><\/div><\/div><\/div>\n<\/p>\n
AI & machine learning<\/strong><\/p>\n
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<\/a> can process that information and give recommendations to retailers about where they should place certain products for more exposure and so on.<\/p>\n
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