With many manufacturing organizations trying to better understand their customers’ needs — and often their customers’ customers’ needs — there is an increasingly need to collect and mine big data and convert it to useful and actionable information. And at no time has this been more important than now, considering the need for actionable information from AI when beginning IoT deployments.

As part of this process, these organizations are seeking new and innovative ways to better understand their customers’ — and their customers’ customers — wants, needs, and behaviors. Increasingly, this means the use of digital tools and digital transformation initiatives, as well as the use of customer and predictive analytics, artificial intelligence (AI), and machine learning, to better know and understand their prospects’ and customers’ needs in order to provide more effective IoT deployments, and ultimately an outstanding customer experience.

Read more: Improving the Effectiveness of IoT Deployments With AI and Machine Learning

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Published by Mike Rawson

Mike Rawson has recently re-awoken a long-standing interest in robots and our automated future. He lives in London with a single android - a temperamental vacuum cleaner - but is looking forward to getting more cyborgs soon.

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Improving the Effectiveness of IoT Deployments With AI and Machine Lea…

by Mike Rawson time to read: 1 min
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