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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. Successful integration of AI in commerce depends on earning and keeping consumer trust.

B2B 49
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How we’re driving sustainable impact for business and society

CIO Business Intelligence

For decades, we’ve been investing in innovation, partnerships, and programs that apply our technology, scale, and talented workforce to drive human progress – all intending to have a measurable influence on some of the complex challenges important to our business, customers, the communities we serve and society at large.

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6 ecommerce trends to watch

IBM Big Data Hub

As the ecommerce market grows exponentially, six trends projected to heavily impact the global market are artificial intelligence (AI), augmented reality, live commerce, online-to-offline ecommerce, social commerce and voice assistants. They also expect the ability to use the payment option of their choice.

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Getting Started With Incremental Sales – Best Practices & Examples

datapine

A loyal, high-value repeat customer is worth more than a cheap sale, and by implementing the right strategy, setting the right goals, and working with the right KPIs, you will achieve the results you desire. Incremental sales is a KPI used by marketers to assess the financial value of various promotional activities.

Sales 176
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Conversational AI use cases for enterprises

IBM Big Data Hub

NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately. Enterprises can use NLU to offer personalized experiences for their users at scale and meet customer needs without human intervention.

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How Financial Services and Insurance Streamline AI Initiatives with a Hybrid Data Platform

Cloudera

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. It’s the most revolutionary technological development in at least a generation.

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Build scalable and serverless RAG workflows with a vector engine for Amazon OpenSearch Serverless and Amazon Bedrock Claude models

AWS Big Data

In pursuit of a more efficient and customer-centric support system, organizations are deploying cutting-edge generative AI applications. This holistic approach not only enhances the customer experience but also offers efficiency gains, ensures data privacy compliance, and drives customer retention and sales growth.