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AI in commerce: Essential use cases for B2B and B2C

IBM Big Data Hub

Key takeaways By implementing effective solutions for AI in commerce, brands can create seamless, personalized buying experiences that increase customer loyalty, customer engagement, retention and share of wallet across B2B and B2C channels.  The applications of AI in commerce are vast and varied. . 

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PODCAST: COVID19 | Redefining Digital Enterprises – Episode 5: COVID-19 and Changing Business Landscape in Australia

bridgei2i

But because of COVID-19, digital transformation is helping B2B models trying to replicate successful B2C models. And since they involve making better decisions using data-driven insights, AI & Analytics led applications are leading the way forward. Let’s see it from B2C and B2B perspective.

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Diligent enhances customer governance with automated data-driven insights using Amazon QuickSight

AWS Big Data

QuickSight helps empower our customers by putting the reporting tools and capability in their hands, allowing them to get a comprehensive, personalized (via row-level security) view of data, unique to their workflow. Currently, she is focused on Diligent Highbond’s Data Automation Solutions. To learn more, visit Amazon QuickSight.

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Data Analytics for Crypto Casinos: Significance and Challenges

BizAcuity

A majority of online casinos have also started accepting various cryptocurrencies as payments and many B2B gaming providers have been heavily investing in crypto gaming to meet with the rising demand. Hence, a lot of time and effort should be invested into research and development, hedging and risk management.