Tag Archives for " Big data "

Handheld phone with image of products

DataPorts and Why they Matter

Improve the Quality of Product Content

​Retailers today struggle with managing ​the product content necessary to publish and maintain their online product catalog. Assembling content from manufactures is difficult when information ​comes in different forms. Likewise, manufacturers struggle to publish new product content and syndicate content throughout their channel.

Standardization is one approach and it is important for critical attributes such as the global trade identification number (GTIN). However, information such as schemas remain difficult to implement throughout the value chain and across the various different markets and regions.

Recently, IceCream Labs become involved with the Consumer Goods Forum (CGF). One core goal of the CGF is to improve data exchange throughout the value chain. The momentum within the CGF comes from the attention of executive leadership from many of the largest worldwide retailers and manufacturers. As a result, the CGF is starting to see momentum build from its initiatives.

Make it Simple

The executives within the CGF want to achieve the goal of reducing the pain of sharing information and improving interactivity (while reducing the costs of managing this data). From this need has emerged the idea of DataPorts. Conceptually, DataPorts deliver a method for peer-to-peer data exchange between any two points in the value chain. This removes the need for data aggregation or hub and spoke interactions. Any point in the supply chain can talk to any other point.

At the heart of the DataPort implementation is the use of Graph Query Language (GraphQL) and GraphQL schemas. The significance is that the GraphQL is emerging as a performant solution to the need for quickly finding related information in a network of related data. GraphQL has evolved to meet the needs of social media giants Facebook and LinkedIn.

What is a DataPort?

At its simplest implementation, a DataPort is a method for publishing information and then discovering and using the information using data virtualization rather than data federation. There is a common programming model for DataPorts, and this allows for peer-to-peer integration.

For example, a manufacturer can release a new product line, publish the content to a DataPort and then make that DataPort available for any retailer to query (with their product catalog DataPort). A retailer can request the new product content, and specify the schema that they desire and normalize any values in the process.

The services delivered by a DataPort ​are broken down (currently) into three broad areas:

1. Abstraction is the process of virtualizing the source data.
2. Transformation operates on the data to do things such as unit conversion.
3. Composition takes a set of results and creates a response from the DataPort.

At IceCream Labs, we are actively working on applying our existing expertise and experience in  data extraction to use machine learning models in the abstraction and transformation processes. We are already normalizing ​and extracting data from source images and unstructured information to generate high-quality product content.

Stay tuned, as we continue to explore more ways that ​DataPorts are changing the way that data moves through the supply chain, and improve the entire end-to-end process.

Dataport Whitepaper Cover

​Download your copy of the latest DataPorts whitepaper: Solving End-to-End Value Chain Content Integration from the Consumer Goods Forum

supermarket with fresh produce

AI and Automation are transforming the E-Grocery experience

AI and Automation are transforming the E-Grocery experience

The concept of e-grocery is not new, with existing e-commerce businesses like Walmart To Go, Amazon Fresh and Instacart, but with Amazon acquiring Whole Foods, all the players in the grocery retail industry have realized that grocery shopping is at the brink of transformation and are changing their strategies to accommodate and incorporate online shopping into their business goals. 

The focus is on providing solutions to enhance customer engagement, optimize inventory management and upgrade logistics for accurate and speedy delivery. To address these concerns, businesses are investing in technologies like artificial intelligence (AI), machine learning (ML), big data, internet of things (IoT), cloud computing, autonomous robots, virtual and augmented reality (VR/AR).

Challenges of e-grocery inventory management

The success of an e-grocery business essentially depends on inventory management. The fundamental problem that needs to be addressed is stocking: with grocers finding the right balance between understocking and overstocking. 

Overstocking uses up costly warehouse space and locks up capital which could be otherwise made available for resources. Products decay over time and with perishables, the decay is often quicker, in some cases, by the end of the day. Every wastage affects the business, increasing the costs and making it unproductive.

While on the other hand, understocking hinders the growth of the business. No grocer wants customers abandoning their shopping carts because of the inability to supply an item. While there are options to pre-order products that are not in stock, groceries are fast moving products that customers need on a regular basis. Grocers cannot list fruits, vegetables, cereals, soaps, detergents, and personal care items as out of stock. The demand for them is instant.

Optimizing inventory is crucial for the survival of the grocery industry. It’s no surprise that e-grocers are leaning towards innovative technologies to enhance and optimize their inventory management processes.

aisle with fresh fruits

Emerging trends in e-grocery

Big Data, AI and Machine Learning

E-grocery businesses generate a significant amount of data about purchasing patterns which can be useful to predict future trends. However, this data needs to be examined and categorized to make it efficient and useful. Here’s where data analytics and machine learning come in to help grocers extract relevant insights which help them make strategic business decisions.

Businesses are leveraging AI to predict operational failures and improve warehouse management. As machine learning models get smarter, the systems get more efficient over time.

Automation and use of robots

Besides inventory maintenance, the physical movement of the inventory is another challenge for the grocers as it requires a considerable amount of human labor. Technologies like automation and robotic systems are helping businesses by taking over these manual tasks.

The robotic systems are automating operations for customer orders and are also helping businesses to build space-saving warehouses and utilize the complete area efficiently without wastage. There are rails between aisles for robots to move around, stock and fetch products. Robotics and automation go hand in hand towards reducing the size of real estate investments.

Self-Drive logistics

Another challenge that e-grocers face is delivery of the products to the customers.

Groceries differ from regular e-commerce products such as shoes, or furniture items in two ways: the quick turn around time expected by the customer and the perishable nature of grocery items. As the order volume of the e-grocery business grows, the logistics system needs to scale along with it. This, in turn, increases the delivery cost that further affects the business.

Businesses are turning towards self-drive vehicles to deliver groceries to customers and with startups like AutoX with self-drive car deliveries and Marble with a sidewalk delivery robot coming in the market. As transport technology advances, self-driving automatons can become the next big thing to look out for.

The future of e-grocery

As online grocery businesses are adopting the latest technology to solve the supply chain, inventory management, and logistics problems, even small grocers are able to leverage these technologies to scale their businesses through automation and predictive analytics.

Moving grocery online has been a major problem with the high demand for operational excellence and the low margin of the products. This is a hard sell for many businesses, but with the advancements in AI, Machine Learning, Automation, Robotics, this is changing. This can be seen from the growth of e-grocery ventures that are emerging around the world.

Other e-commerce articles:

Enhancing the customer experience beyond shopping
Enhancing the customer experience beyond shopping With consumers changing how they purchase and engage with a brand, retailers have leveraged[...]
Importance of AI in customer loyalty
The expectations of consumers today from their favourite brands has increased ten-fold, and with big companies such as Amazon providing[...]
What is GS1 Verified? – Everything you need to know
​Live from the GS1 Connect 2019 EventWith the GS1 Connect 2019 event happening this week in Denver, Colorado, we think[...]
DataPorts and Why they Matter
​Retailers today struggle with managing all of the product content necessary to publish and maintain their online product catalog. Assembling[...]
3 ways Grocery retailers can survive in the age of Amazon
3 ways retailers can survive in the age of AmazonRetail giants like Amazon’s ability to effectively address the ever-changing customer[...]
The Impact of AI on Grocery Retail
The Impact of AI on Grocery RetailIn today’s age, grocery retailers no longer have to make guesses about what customers[...]