November 19, 2019
4 Minute Read
Serving a niche audience, personalization, cultivating strategic partnerships, or even cutting costs in your supply chain to pass on the savings are well-known ways e-commerce enterprises remain competitive.
However, in an era where an agile operation is fast becoming the expectation, here are four reasons e-commerce needs artificial intelligence to stay ahead.
Demand planning already uses machine learning to incorporate data and insights like store traffic, weather forecasts and competitor pricing in supply chain operations, but AI can also help improve accuracy and efficiency in your supply chain in other ways.
Since working together, Samasource has improved Walmart’s item coverage from 91 percent to 98 percent.
Training Walmart’s systems meant manually cataloging and evaluating more than 2.5 million items, and while sharpening the supply chain with AI comes with its share of challenges, having a training data partner with a commitment to quality and security helped further Walmart’s machine learning initiatives.
AI can play an integral role in streamlining e-commerce operations. For example, Amazon uses artificial intelligence to make adjustments in delivery routes and arrival times.
Other retailers like Gap are also using a combination of human effort and automation to perform dynamic product picking in shipping warehouses.
Research continues on how to fully automate shipping warehouses, but it’s this level of human-in-the-loop AI that shows great promise for e-commerce enterprises.
Working together, humans and machines can find ways to deliver customer orders with efficiency, providing a stark competitive advantage to companies who adopt AI as part of their operational roadmap.
A product recommendation engine allows you to suggest products uniquely suited for your buyers. Think of this algorithm as the digital substitute for brick and mortar store clerks who guide shoppers to relevant and similar products.
Our work with Walmart contributes to the accuracy of their product recommendations, and we’ve also helped Getty’s Images catalog stock photos based on key attributes, to support the foundation of its recommendation engine.
Recommendation engines help you up-sell, cross-sell and otherwise inspire customers to bundle offers and create custom solutions best suited for their needs, and according to a McKinsey report, Amazon’s AI-powered recommendation engine was responsible for 35 percent of the company's revenue.
In addition to product recommendations, artificial intelligence can automate post-purchase activities like accurately timed repurchasing messages, so your buyers are their most ready to buy.
Today’s always-connected consumer shops from multiple devices, putting seamless customer experiences at the core of driving customer engagement.
A recent study showed that about two-thirds of shoppers check their phone in-store for product information e.g. looking up product reviews, comparing prices, etc. Whether it’s to send targeted and relevant messaging and ads, or to enable real-world product scanning, e-commerce needs AI, in order to create immersive customer experiences at scale.
When we work with companies that want to use AI in e-commerce, we notice a few common barriers in AI adoption, such as a lack of training data strategy, lack of talent and/or platform to get started with AI and a lack of high-quality data to properly train AI algorithms.
If any of these barriers are stopping you from implementing AI across your organization, we can help. Helping e-commerce enterprises keep up with the demand for personalization, while driving the best level of digital classification, i.e., enabling the maximum/optimal experience for users to describe and see what they are shopping for, is what we do.
Contact us to learn more about accelerating your ML pipeline with high-quality training data from Samasource.