Improve Business Outcomes with Machine Learning

Solve your most common business challenges with practical machine learning use cases

From enhancing customer experiences and boosting employee productivity to cutting costs and reducing fraud, machine learning can help you deliver on your business objectives and propel your digital transformation. Yet, finding the right place to start to apply machine learning can be difficult. Implementing practical, proven machine learning use cases can help to remove this barrier for your organization and quickly provide real business impact.

Whether you have a specific business outcome in mind or you are just exploring, you can accelerate your machine learning journey by starting with one of the following use cases.

Explore common use cases

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Add intelligence to the contact center

Enhance your customer service experience and reduce costs by integrating machine learning into your contact center. Through intelligent chat and voice bots, voice sentiment analysis, live-call analytics and agent assist, post-call analytics, and more, personalize every customer interaction and improve overall customer satisfaction.

ChartSpan, the largest chronic care management service provider in the U.S., decreased cost by 80% and increased staff utilization by 12%.

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Personalize customer recommendations

Improve customer engagement and conversion by creating personalized web experiences—tailored to individual customer preferences and behaviors across channels—through recommendations, curated content, and targeted marketing promotions.

Lotte Mart, a leading South Korean hypermarket, saw a 5x increase in response to recommended products.

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Automate data extraction and analysis

Instantly extract text and data from virtually any document such as loan applications and medical forms without manual effort. Process millions of pages in hours, uncover valuable insights, and implement human reviews with intelligent document processing.

Assent Compliance, a supply chain data management company, saved their customers hundreds of hours of manually reviewing documents.  

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Boost business productivity and customer satisfaction by delivering accurate and useful information to employees, customers, and partners quickly. Help users get answers faster from siloed and unstructured information sources across the organization by using intelligent search.

Baker Tilly, a leading advisory, tax, and assurance firm, surfaced relevant information 10x times faster when compared to SharePoint full text search.

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Identify fraudulent online activities

Improve profitability by automating the detection of potentially fraudulent online activity, such as payment fraud and fake accounts, using machine learning and your own unique data.

Truevo, a payment service provider, was able to build a fraud detection model in just 30 minutes and is operating with greater confidence to catch bad actors faster.

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Analyze media content and discover new insights

Create new insights from video, audio, images and text by applying machine learning to better manage and analyze content. Automate key functions of the media workflow to accelerate the search and discovery, content localization, compliance, monetization, and more.

SmugMug, a global image and video sharing platform, is able to find and properly flag unwanted content at scale, enabling a safe and welcoming experience for its community.

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Forecast data faster and more accurately

Accurately predict demand forecasting and streamline supply-demand decision making using machine learning to combine historical time series data with additional variables such as product features, pricing, and holidays.

Advanced Microgrid Solutions (AMS), a leading energy platform and services company, discovered the best model parameters and built their model in just weeks, which improved market forecasts across all energy products in net energy metering and will translate into significant efficiencies.

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Customer spotlight

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  • 3M
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    3M, a Minnesota-based multinational corporation that produces adhesives, medical products, and more, uses Amazon Kendra to help its scientists find the information they need by handling natural language queries quickly and accurately. 

  • Subway
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    The Subway restaurant chain used AWS personalization solutions to quickly deliver personalized recommendations for their endless varieties of ingredients and flavors to fit the unique lifestyles of their guests.

  • Change Healthcare
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    Change Healthcare, a leading independent healthcare technology company, used AWS data extraction and analysis solutions to unlock information from millions of documents, creating more value for patients, payers, and providers.

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Move beyond the hype and into the real world of machine learning. In this eBook, 7 Leading Machine Learning Use Cases, we have outlined the leading use cases where businesses have successfully applied machine learning to achieve fast, efficient, measurable results.