Artificial intelligence makes this possible for the hair color products retailer. The machine-learning algorithm factors in the answers to a 20-question hair coloring quiz more than 4 million shoppers have taken, along with more than 24,0000 product reviews of the retailer's 50 SKUs. It also factors in a shopper's repeat purchase rate, net promoter score and hundreds of thousands of shopper and customer service agent interactions, says Dave King, chief technology officer at Madison Reed. With all of this historical information, Madison Reed's algorithm is the ultimate master colorist that can recommend hair coloring products, King says. When Madison Reed first launched its product recommendation engine, it was coded by humans and did not factor in all of the data points that it does today.

When E-commerce took off the way it did, every retail pundit predicted the doom of in-store shopping as we knew it. The novelty and glamour associated with in-store shopping were replaced by convenience and never-ending aisles that an e-tailer brought. These'new guys' were born and brought up in the tech industry and knew how to use data to make products more accessible to customers. But, things always don't go as planned, do they? The hostile takeover of the retail kingdom is getting harder and as it stands today, the e-commerce players market share is still in single digits.

In their first guest exclusive with us, Acuvate Software shares the many different ways in which predictive analytics, combined with AI, is changing our industry. Acuvate provides AI and predictive analytics solutions for consumer goods and retail businesses. Their mission is to produce intelligence applications that simplify processes. A retailer can predict the number of footfalls for a given period, but cannot predict where these footfalls are likely to pause in the shop, stop for exploration and for purchase. But, for those retailers who have incorporated predictive analytics and Artificial Intelligence, knowing these gray areas is possible.

This article is part of CMO.com's March/April series about emerging technology. Rapid digital disruption has sparked a wave of innovation, forcing organizations to drastically rethink how they operate and interact with customers. Power, as we know, has officially shifted to the consumer, who expects seamless buying experiences across all platforms and devices. Pair that with the emergence of data-driven technologies, such as artificial intelligence (AI), and it's clear that improving your business' bottom line requires a data-centric approach--one that complements, augments, and ultimately drives consumer preference and decision-making. In fact, an estimated 95% of customer interactions will be supported by AI technology by 2025.

According to analyst Forrester, artificial intelligence (AI), big data and analytics will increase businesses' access to data, broaden the types of data that can be analysed, and raise the level of sophistication of the resulting insight. For 2017, Forrester expects investment in AI to triple. Check out the latest findings on how the hype around artificial intelligence could be sowing damaging confusion. Also, read a number of case studies on how enterprises are using AI to help reach business goals around the world. You forgot to provide an Email Address.

The retailer can know the status of our strawberry from the moment it's picked, thanks to connected sensors that collect information about soil content, exposure to sunlight, humidity, and temperature. These sensors are in place across the supply chain, giving the retailer a tool to make better decisions about how and when to get the strawberry to the store. The strawberry's batch is assigned a digital "token" immediately after it's picked. The retailer is now able to ensure freshness by tracking every action it takes from the orchard to the store--how long it sat in the distribution center, the truck it was loaded on, and when it arrived at the store. AR-equipped glasses enable distribution center workers to examine our strawberry and see the data about it.

Building trust in artficial intelligence (AI) is vital to promote the adoption of the technology. In the digital era, where there is an unstoppable increase in smartphone usage, consumers are empowered to buy anything at any given time. Consumer trends are forcing the retail sector to be better able to cope with the requirements of the market. Modern day technologies are transforming the way people are buying from a retailer. According to statista, global e-commerce will accumulate sales of approximately 4,479 billion US dollars by the year of 2021.

Ahold Delhaize will explore potential retail applications of artificial intelligence (AI) in a partnership with the Innovation Center for Artificial Intelligence (ICAI), a project of the University of Amsterdam and VU University Amsterdam. The Zaandam, Netherlands-based global food retailer said its partnership is the first lab within the ICAI, which was launched yesterday at Amsterdam Science Park. Dubbed the AIRlab, the joint ICAI-Ahold Delhaize industry lab will have seven PhDs researching socially responsible algorithms that can be used to make recommendations to consumers and transparent AI technology for managing supply chain flows, according to Ahold Delhaize. The retailer's Albert Heijn and bol.com brands will participate in the research. In addition, the AIRLab will focus on talent development.

Get cost optimization recommendations based on your spend with secure read-only unintrusive access. In minutes, identify opportunities - right-sizing, reserved instance planning, idle/orphaned resource insights, for continuous cost optimisation. Get cost optimization recommendations based on your spend with secure read-only unintrusive access. In minutes, identify opportunities - right-sizing, reserved instance planning, idle/orphaned resource insights, for continuous cost optimisation.

Shopkeepers in emerging markets seldom use technology only to have a better "picture" of their business, they usually have been running their shops for many years and think they know everything they need to in order to be successful. They are drawn to much more tangible value propositions if they are to use an electronic POS system. The value prop has to address a real, instant, and tangible pain point. At the same time, on-boarding barriers and learning curves have to be taken down or reduced. In Frogtek we try to achieve this by using data and algorithms to automatically build and update a massive product database and eliminate the need to create from scratch the shop inventory before the system is rolled out, by offering a pricing feature that automatically adapts to the shop's price-levels and provides accurate pricing suggestions when new products show up.