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Predictive Analytics in Healthcare

Reveal

Reveal Embedded Analytics. The abundance of data available at an organization’s fingertips transforms the entire industry. Real-time, accurate insights that can impact patients are extremely important. Real-time, accurate insights that can impact patients are extremely important. And this is where analytics comes to help.

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Mobile Customer Response Rates Grew by 20% Last Year: New Data from our 2018 Benchmark Report

Alchemer Mobile

They need to be able to understand the analytics behind customer interaction and response rates so they can make data-driven decisions. In 2018, companies reached out to 25% of their customer base ; on Android, the rate was 21% while on iOS, it was 28%. As such, it’s not enough for companies to send communication into a vacuum.

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Top Data Labeling Tools for Machine Learning Projects

The Product Coalition

Generating labeled training data requires a great deal of time, effort, and investment. If you’re building a machine learning model, chances are you’re going to need data labeling tools to quickly put together datasets and ensure high-quality data production.

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What Is Software Usage Analytics?

Revulytics

you may call it software usage analytics, runtime intelligence, software business intelligence, or software intelligence (if I missed your favorite please add it in the comments). Our customers implement software usage analytics to better understand which features are adopted and which are ignored.

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5 Key Considerations for Top-Notch Product Dashboards

Speaker: Miles Robinson, Agile and Management Consultant, Motivational Speaker

So you want to set your product apart with the latest analytics, but you’re not sure where to start. Join Miles Robinson, Agile and Management Consultant, as he covers five key considerations for you to keep in mind when you’re updating your software or app to offer the latest in embedded dashboards.

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What AI Means to a Data Scientist

Birst BI

However, there are simply not enough data scientists in the world to deliver on the AI potential. Data scientists building AI applications require numerous skills – data visualization, data cleansing, artificial intelligence algorithm selection and diagnostics. The Outsourcing of Data Science Functions.

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Quantum UX Research

UX Planet

The potential of quantum computing and artificial intelligence to enhance user research User research is crucial for the human-centered design of digital products and services. We will argue that quantum computing and AI have the potential to elevate user research to new levels of accuracy, efficiency, and insight.

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Products for Product People: Best Practices in Analytics

Speaker: Andrew Wynn, Senior Product Manager, Looker

As a product manager, you know how helpful custom tailored data solutions can be to doing your job well. But proper data analytics solutions take work to deliver - it's not as simple as just building a dashboard. Learn product analytics best practices from Andrew Wynn, Product Manager at Looker.

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Build Actionable Dashboards to Drive Your Business

Speaker: Jim O'Leary, VP of Product Management, and Brian Elmi, Director of Product Management, NTENT

Most product dashboard review lagging indicators rather than leading indicator and focus on the wrong metrics to move the business forward. Join Jim O'Leary and Brian Elmi of NTENT as they share exactly what they've done to build successful dashboards. How to democratize data so that all teams in an organization can benefit from it.

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UX and Design Tips for Better Dashboards: Product Manager Laura Klein Explains How to Improve Your Analytics

Speaker: Laura Klein, Principal at Users Know and Author of UX for Lean Startups

That's why Laura Klein, product manager and UX designer, has a set of tips to help application teams improve their embedded dashboards and reports. How to avoid common mistakes people make when presenting data. October 25, 2018 12:30 PM PST, 3:30 PM EST, 8:30 PM GMT And yet we have so many of them in our lives.

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How and Why: Embedded Analytics Interfaces For Your SaaS Product

Speaker: Sam Owens, Product Management Lead, Namely Platform

Sam and Jessica faced a problem that many product managers face: their customers wanted better analytics and reporting, but analytics wasn’t the core function of the SaaS product Sam and Jessica manage. If your users would want analytics as part of their interface, you don't want to miss this session.

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Iterate Your Way to a Top Analytics Product Experience

Speaker: Richard Cheng, Associate Product Manager, Mark43

Mark43 is on a mission to bring public safety data management into the 21st century. To fix traditionally paper-heavy and error-prone processes, they needed a secure and easy-to-use product experience that simplified and unified crime data collection and management. How efficient intelligence and analytics will benefit your users.

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How To Build Data-Informed Products

Speaker: Tim Herbig, Director, iridion

As a product manager, you probably know specific ways to gather data to inform your product decisions, like the ever-popular A/B test. Tim Herbig will share his hands-on approach to working with analytics in agile product management. Tim will discuss the line between being data-informed versus data-driven.

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Turning Metrics into Dollars: How to Turn Your Analytics Data into a Real Financial Model for your Startup

Speaker: Tristan Kromer, Lean Agile Coach, Kromatic

You'll learn: How to turn basic dashboard metrics into a financial model. May 1, 2018 11:00 AM PST, 2:00 PM EST, 7:00 PM GMT At the very least, they need to be able to see the impact of a change in retention rates to their user growth. Learn how margin of error impacts financial projections.

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Harness Your Product Data: Better Understanding User Behavior Across Channels and Devices

Speaker: Kate Owens and Megan Bubley, SpotHero, Diana Smith, Segment, and Erin Franz, Looker

As a product leader, you are tasked with collecting and synthesizing your customer’s interactions with your product.The great news is that there are many tools used across your company which collect unique parts of your user’s journey. As your sources of data increase, so do the complexities of unifying the data in a meaningful way.