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Unified Data is the Key to Consistent Omnichannel Customer Experiences

In this contributed article, Bruno Farinelli, Fraud Analytics Manager for the ClearSale US branch, discusses how unified data can help you connect customers to the products you have in stock, get them through checkout quickly and without mistaking them for criminals, keep up with the changes in their lives for better, more empathetic messaging and make it easier for your front-line employees to deliver great service.

4 Digital Experience Strategies You Need to Consider

In this special guest feature, Garrett Schwegler, Program Manager for Digital Commerce at Lucidworks, offers four strategies you should consider to help you focus and improve the digital experience for your users. More is better—more data, more insights, more happy customers and employees. More can also feel like ‘too much’ if you don’t know where to start.

The Need for Brands to Invest in Data Analytics

In this special guest feature, Thalya Hamilton, VP of Analytics & Data Science, Quotient, discusses how brands will need to strike the right balance by bringing data and analytics in-house—staffing the right talent and empowering them to lead the way forward—while also finding third-party experts to partner with to strengthen their understanding of that data. This dual approach is key if brands want to succeed in a digital-first world.

How Can AI Enhance Human-to-Human Communication and Improve Customer Service?

In this special guest feature, Krishna Raj Raja, founder and CEO of SupportLogic, discusses how AI can help service agents detect customer signals – picking up on how a customer is feeling and also understanding context, then dynamically flagging or escalating a case before an annoyance turns into a major problem.

Applying GANs to Image Generation Tasks

This contributed article by Maksym Tatariants, PhD, AI Engineer at MobiDev, overviews StyleGAN2 application to image generation task and is based on MobiDev’s logotype synthesis research. When it comes to powerful generative models for image synthesis, the most commonly mentioned are StyleGAN and its updated version StyleGAN2.

Walmart Innovates at the Retail Edge with AI

Through the combination of world-class software from Malong Technologies and a powerful processing platform Dell Technologies and NVIDIA, Walmart is able to deliver groundbreaking AI acceleration at the store edge.

How Yum! Brands Uses Location Data from Foursquare to Make Smarter Decisions

Join this virtual event with a compelling panel of technology leaders to discuss to discover how Yum! Brands and other organizations are leveraging location-based data to boost in-app location accuracy, increase in-store foot traffic, and expand e-commerce business.

High Value, Low Contact: Emerging Retail Technology for a COVID-Influenced World

In this special guest feature, Melanie Nuce, Senior Vice President of Corporate Development at GS1 US, discusses extracting maximum consumer information from store traffic while also making the experience safe and contactless. Digitizing store experiences is becoming paramount–consumers want to make the most of fewer shopping trips while technologies like AI, IoT, and sensors are coming to the forefront to support innovative consumer engagement strategies.

How AI is Being Applied to Retail: Deep Learning Brings Superpowers to eCommerce with Companies like Wish and RTB House Leading the Charge

In this contributed article, Garth Holsinger, founder of Enterprise Alpha, and Partner at Prota Ventures, discusses how Deep Learning technologies are bringing superpowers to e-commerce and digital advertising platforms, and how Wish, RTB House, and Macy’s are leading the charge.

87 Percent of US Retailers Race to Achieve Faster Data-Driven Insights to Support Online Sales

Exasol, the high-performance analytics database, published new research that reveals since the pandemic started, 87% of retail organizations in the U.S. have been under pressure to make data-driven decisions faster. The finding comes from an in-depth research report, “Retail: Decision making during times of uncertainty,” that quantifies how retail organizations in the U.S. are heightening data-driven decision-making cycles to meet real-time demand and prepare for surging online sales brought on by the COVID-19 pandemic.