Driving Retail Sector Through AI For Future
How AI Drives Innovation in eCommerce and Retail
Large amounts of AI Training Dataset are required by retailers to enable machine learning and AI algorithms to be trained to respond to high volumes. Blogged recently about a McKinsey report for 2018. This report examined hundreds of AI applications. Customer service teams are able to provide better customer experiences through chatbots and smarter analytics, which can help them deliver faster wins when using AI. Marketing and sales departments often get the most out of AI. McKinsey suggests that physical retail stores invest in AI to improve supply chain management and optimize inventory. AI can help retailers personalize their customer experience and improve product recommendations by using technology that considers all of a person's preferences and behaviors when creating a search result, pricing quotation, or next best step.
Boosting eCommerce sales using AI tools
Online retailers are the pioneers of AI-driven personalization due to their vast data collection about customers' preferences and behavior. These winning strategies include personalizing product recommendations and website content based upon previous customer behavior, personalized communications based both on behavior and learned preferences, and using chatbots for customers to navigate the shopping experience.
Using AI for personalizing customer experiences
Online retailers are investing heavily in AI-powered personalization engine to blend the human interaction of an in store experience with the convenience and ease of an online purchase. These AI tools enable shoppers to search for products online using voice commands or Image Dataset taken from their phone. It is a similar experience to interacting with someone in person. This strategy helps retailers stand out, increase word-of-mouth sales and customer loyalty.
Skechers uses AI in site search relevance to their lifestyle and sportswear brand. AI powered tools analyze Skechers' catalogue to present similar or related products as online shoppers click on the product they are interested in. This makes shopping easier and more intuitive for customers. Customers also get the best possible product recommendations, which increases sales and customer satisfaction.
Artificial Intelligence and Machine Learning Industry News. AI in Retail, Interactive Vending Machines and Vocal Recognition
Artificial Intelligence opens up new opportunities for the traditional retail experience. Brands can learn from customers and identify patterns in their purchasing behavior to make better business decisions. AI models can also be trained to provide personalized customer services, product recommendations, customer service assistance, and other tasks.
Amazon is currently testing AI to suggest personalized purchases, while Sephora uses a Kik chatbot for one-on-1 chats with customers that include curated beauty tips.
Interactive Vending Machines
Coca-Cola Company has recently launched an AI-backed vending system for China. Customers can use this machine to purchase beverages as well as return and recycle empty cans and bottles. The machine helps the company achieve its sustainability goals by combining beverage sales and recycling capabilities.
A vending machine incorporates AI technology like facial recognition and sound interaction, which provides customers with an interactive experience. The vending machine has two eyes, one to access purchased beverages and one to return bottles to be recycled. Additional to the "eyes", the machine's mouth and eyebrows are LED pixels controlled via AI. They can change expressions using facial recognition and sound interaction. Mobile reminders may be sent to consumers who have purchased a beverage. These reminders will remind them to return the bottle when it's empty and allow them to earn credits by recycling.
Voice Recognition
A frustrated by the current state of voice-recognition technology today, musician and entrepreneur will.i.am created the machine learning branch of his consumer electronics business i.am+ in 2016. The startup makes wearable products that mix fashion and technology. It also addresses concerns regarding AI-based Speech Dataset.
i.am+’s AI voice-recognition technology Omega looks similar to digital assistants such a Siri or Alexa. After receiving $117 million in venture capital funding in 2017 for Omega, i.am+ began to shift its focus from consumer technology products to become a Salesforce Ventures partner to improve voice recognition interfaces.
Salesforce's annual Dreamforce conference 2018 was all about voice technology. Salesforce has launched Einstein, which allows users voice communication with Salesforce. Einstein Voice will allow employees to connect better with customers and streamline work processes.
Where Retailers Should Make Investments in AI
The research highlights use cases where AI can be used to benefit both eCommerce sites as well as brick-and mortar retailers. eCommerce sites can collect large amounts of customer information that can be used to make product recommendations, tailor promotions, and create a highly personal shopping experience. AI can significantly optimize supply chain management and inventory management for brick-and mortar establishments.
The McKinsey report's chart below illustrates how AI could impact retail. It shows that sales and marketing can reap the greatest benefits from AI In Retail, particularly when it comes pricing, promotion, and customer service management. According to the authors, using customer data to personalize promotional offers, such as tailoring individual offers for each day, can lead directly to an increase of 1 to 2 percent in incremental sales for brick and mortar retailers.
Retailers that invest in AI are seeing significant results, especially with machine learning-based solutions. This technology can be used to give retailers a competitive advantage, from recommendation engines to chatbots, to manufacturing and inventory control, the leading retailers use it.
GTS helps retailers improve their machinelearning using high-quality data that is human-annotated.
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