Machine Learning: The hot technology keeping products cool
With retail undergoing a massive transformation, machine learning has become an innovative asset, changing the way organizations deliver customer experiences.
As companies adopt advanced technologies that are easily implemented and show worthwhile return on investment, there is a massive opportunity to help customers take and complete this digital journey – not just to innovate, but to scale as a digital business. With artificial intelligence (AI) and machine learning platforms, organizations’ front and back-office processes are evolving.
Many food and beverage companies are using AI, machine learning, and automation to revolutionize critical aspects of their businesses. Food and beverage retailers who stand out are leveraging a suite of machine learning platforms to guarantee products are maintained properly. With this technology, retailers can ensure their beverages, refrigerated food, and frozen food products are always stored at the right temperature and safe for consumption.
In addition, the technology allows retailers to accurately track inventory, monitor maintenance needs, and reduce losses due to spoilage or theft. Here’s why there’s never been a better time to adopt machine learning and achieve retail success:
Tracking every move
The increasingly complex supply networks and the need to coordinate logistics flows across multiple suppliers, present major challenges across the supply chain when tracking inventory. Slow reactions within the supply chain cause inefficient use of fleet, wasting both time and money, and failing customer expectations for on-time delivery.
Additionally, negligence during transportation can also result in damaged goods leading to more unsatisfied customers. These challenges prompt the need to monitor delivery as well as shipment status – and the involved connected logistics equipment (like trucks) – to have a real-time view of the current location of products. By compares the planned and current logistic flows, retailers can quickly react to unexpected conditions and deviation from plans.
Furthermore, to guarantee the on-time availability of components for the efficient processing of orders, retail companies need to implement technologies that control and monitor their complete supply and delivery chain. With an IoT-optimized tracking system, production, and delivery logistics are improved, inventory levels are increased, logistics costs are reduced, and on-time delivery rate is enhanced. This makes it possible for transportation management companies to increase customer satisfaction as products are received on-time, and in working condition.
If it’s broke, fix it
Cold chain monitoring, especially for companies with large global operations, represents both significant investment and maintenance challenges. Refrigerators, coolers, and freezers all see frequent use by restaurants and retailers, and while they are built to withstand wear and tear, asset failure not only comes with the cost to repair the appliances, but the cost of incurred losses from spoilage. Machine learning adapts the data provided through connected devices to practical applications. In this way, retailers can monitor and adjust average ambient temperatures and temperature variations from opening and closing of doors, ensuring consumers receive satisfactory products.
Additionally, today’s IoT connected appliances generate massive volumes of data from sensors and present a greater opportunity for continuous machine learning to turn this data into value-creating assets. With this data, retailers can establish a plan for predictive maintenance in advance of asset failure. By maximizing equipment uptime and ensuring consistent temperatures within pre-set tolerances, machine learning technology makes it possible for retailers to deliver the highest quality and full shelf-life products to their customers.
Stop shop loss
Retail companies selling beverages, refrigerated products, and frozen foods need to manage freezers, coolers, and other refrigeration units in their stores. These cooling units do present a significant ongoing investment in assets, maintenance, and inventory. These appliances need to be monitored to minimize or eliminate lost revenue due to spoilage or product expiration.
Machine learning, along with AI platforms, have also helped food and beverage retailers automate inventory management. By initiating machine-learning processes where employees take photos of store shelves, sensors within the platforms can identify which items are missing or incorrectly displayed. With this technology, store managers and warehouses can automatically be notified to organize or restock the shelves properly, ensuring that customer demand is met. Shelf management is an important part of reducing product loss, whether it’s from vandalism, damage, or theft.
In the food and beverage industry, retailers, producers, and restaurants are rapidly changing their business strategies to incorporate new, innovative technology to stay ahead of competition, meet consumer demands, and provide an enhanced experience.
Through the implementation of AI and machine learning technologies that provide a 360-degree view of both the consumer and their everyday operations, retailers can transform business processes and directly improve the customer journey. By investing in platforms that produce beneficial insights to facilitate this process, while also optimizing production and inventory, retailers within the food and beverage industry will see significant ROI and increase customer engagement.
Lori Mitchell Keller id global general manager, consumer industries, SAP.
Convenience store giant jumps into chatbot game
7-Eleven is trying its hand at conversational commerce.
The convenience store giant launched a chatbot on Facebook Messenger, called The 7-Eleven Bot. Attracted by the approximately 1.3 billion people who use Messenger each month, 7-Eleven saw a new opportunity to reach customers in their online ecosystem by leveraging the Messenger app, according to the company.
Here’s how it works: Consumers using Messenger can connect with 7-Eleven and engage in a conversation with the 7-Eleven Bot. Using the chatbot, customers can sign up for the 7Rewards customer loyalty platform, find a store location near them, and learn about the latest discount offers, among other capabilities.
The technology, which is driven by Conversable, a conversational intelligence software platform that leverages automation and machine learning technology, learns from customer responses. As a result, the chatbot will help the company research new — or better — solutions to consumer issues, 7-Eleven said.
The bot will also help 7-Eleven revamp its loyalty program. For example, customers immediately receive a digital card in messenger and “scan it scan to start earning points, check status as well as collect coupons when they choose,” said Gurmeet Singh, 7-Eleven chief digital officer.
The program augments the digital coupons that can be redeemed through the 7Rewards app, which enables customers can earn and redeem rewards through their smartphone. The app can be downloaded from the Apple Store or Google Play.
“Today’s digital-savvy consumers expect brands to be present when and where they choose, in an effortless manner,” said Singh. “This new form of customer experience proves that 7-Eleven is redefining convenience through digital, as well as pioneering a new era of loyalty programs.”
Study: Rising shopper expectations outpace in-store service
Overall shopper satisfaction is on the upswing, but many customers are still unsatisfied with customer service.
Forty-four percent of surveyed shoppers are still not satisfied with the in-store customer experience — an issue that spans returns and exchange processes, as well as in-store associate knowledge, according to the “2017 Global Shopper Study” from Zebra Technologies.
According to the data, 53% believe store associates armed with the latest technology improve the overall shopping experience. Yet, four in 10 shoppers reported they were better connected to consumer information than store associates. Drilling down further, 53% of millennial shoppers believe they are better connected than store associates, compared to 32% of Gen X shoppers and 15% of boomers.
The good news is an increased use of tablets in stores is improving the shopper experience. More than half of surveyed shoppers (57%) believe technology is improving the shopping experience, and 62% of shoppers appreciate associates’ use of handheld mobile devices in-store.
However, these technology adoptions are not improving returns processes. In fact, 44% of in-store and 53% of online shoppers are still not satisfied with the returns/exchange process.
Out-of-stocks also continue to plague retailers. When shopping in-store, 70% of shoppers have left without purchasing what they were seeking. However, when it comes to out-of-stock issues, retailers can recover six in 10 incidents with discounts or alternative fulfillment options, such as ship to home, according to the study.
Heightened customer expectations are transforming many areas within the retail landscape. While 66% of shoppers want next-day or same-day delivery, and 37% prefer same-day or sooner, 27% do not want to pay for shipping at any speed.
Retail customers also want a variety of fulfillment options. For example, 80% of those surveyed purchase items in-store and either take them home or ship from store to home. Shoppers are also taking advantage of other fulfillment options, such as buy online, ship to home (64%), buy online, pick up in-store (34%) and buy online- ship to alternative location (15%).
Regional findings include:
• Fifty-eight percent of North American shoppers said they have “showroomed,” or looked at items in a store and purchased them online.
• In Europe and the Middle East, 64% of shoppers would be willing to purchase more merchandise if they received better customer service, and 52% value retailers who use technology to make the shopping experience more efficient.
• Nearly one-half (48%) of Latin American shoppers trust sharing personal data with retailers. Moreover, retailers rank low on the list of institutions that shoppers trust with personal data.
• In Asia-Pacific, 32% of shoppers would prefer to go to a retail store to pick up items purchased online or through mobile channels.
• More than half of shoppers in both Asia-Pacific and Europe are interested in Wi-Fi and location-based in-store services, such as mobile coupons.
“The results indicate consumers around the world believe that retailers have come a long way over the past decade to enhance the in-store shopping experience, but shopper expectations continue to rise at an exponential rate,” said Jeff Schmitz, senior VP and chief marketing officer, Zebra Technologies.
“Retailers continue to invest in their physical stores; we see this with an increasing overall store count and growth in convenience and mass merchant retail,” he said. “Sales associates armed with the right technology tools are better equipped to serve customers and increase revenue by providing the visibility and actionable insight into product information, inventory and fulfillment options that bring the online experience into the physical store.”