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Data is essential: Building an effective generative AI marketing strategy

IBM Big Data Hub

Generative AI is powering a new world of creative, customized communications, allowing marketing teams to deliver greater personalization at scale and meet today’s high customer expectations. 1 In regard to B2B marketing function, these leaders called out lead generation and sales nurturing as the top use cases.

Marketing 121
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Generative AI use cases for the enterprise

IBM Big Data Hub

Streamline workflows with personalized content creation, tailored product descriptions and market-ready copy. This personalized training sculpts the model into bespoke generative AI perfectly aligned with business goals. The best option for an enterprise organization depends on its specific needs, resources and technical capabilities.

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7 customer experience trends in 2024

IBM Big Data Hub

This includes movies, TV ads, in-store costumes, and in-person character experiences. Many businesses are even personalizing their programs, adding a hierarchy of loyalty status, to highlight their most loyal customers. Additionally, the Airbnb Help Center includes a plethora of resources at the customer’s disposal.

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10 everyday machine learning use cases

IBM Big Data Hub

Machine learning in marketing and sales According to Forbes , marketing and sales teams prioritize AI and ML more than any other enterprise department. ML also helps drive personalized marketing initiatives by identifying the offerings that might meet a specific customer’s interests.

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Don’t let bad data drag you down: A retailer’s guide

Collibra

This blog outlines what bad data means and how you can stop it from hurting your retail business. SKU data helps understand sales trends and customer preferences. What happens when your marketing emails get sent to the wrong email id? It needs to work around the fickleness of customers and rapidly evolving trends.

Retail 73
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Data Modeling 201 for the cloud: designing databases for data warehouses

erwin

This blog is based upon webcast which can be watched here. As with the part 1 of this blog series, the cloud is not nirvana. Yes, it offers essentially infinitely scalable resources. Static over-provisioning or dynamic scaling will run up monthly cloud costs very quickly on a bad design. But you must pay for using them.

Cloud 52
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Leveraging generative AI on AWS to transform life sciences

IBM Big Data Hub

This digital data is coming at the industry in various formats, like unstructured text, images, PDFs and emails. generative AI has the potential to process digital content at scale and produce an effective MLR output, which can then be leveraged by the human marketing team, accelerating and simplifying the process.