Remove 2018 Remove Analytic Tools Remove Data Visualization
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The ultimate marketing technology stack for 2019

Intercom, Inc.

Known as the Martech 5000 — nicknamed after the 5,000 companies that were competing in the global marketing technology space in 2017, it’s said to be the most frequently shared slide of all time. The reasons for this growth – high-velocity economics of software innovation, the migration of money from old media to new media, etc.

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Gaming Analytics: How to Leverage Your Customer Data for Sustained Business Growth

Indicative

Gaming data is one of the most valuable sources of information out there. . gamers’ weekly leisure time going to playing games as of 2018 — companies are sitting on treasure troves of insight. You need an analytics solution and data strategy that can help make that information useful. .

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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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The Future of Digital Health: Realities vs Opportunities

The Product Coalition

Growing market investments indicate that digital health solutions are becoming more sophisticated and widely accepted. In today’s healthcare, digital technology is becoming increasingly vital. The multifaceted service platform is the solution to the industry’s key challenges.

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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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What Is Software Usage Analytics?

Revulytics

Depending on what you do (product management, software development, etc.), 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).

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What Do Industry Analysts Think About Software Analytics?

Revulytics

It is no surprise that we talk a lot about software usage analytics , but I thought it would be interesting to take a look and see what industry analysts are saying, too. What is driving this interest in product usage and data analytics? What is driving this interest in product usage and data analytics?

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How King Crushes New Product Development using Data-Driven Insights

Speaker: Ian Thompson, Head of Business Intelligence at King, and Zara Wells, Strategic Customer Success Manager at Looker

Product Managers looking to leverage data to make informed product design decisions can learn a lot from renowned gaming company King, maker of Candy Crush and many other games - even if their product has seemingly no overlap with games. The key is the strategy and tools for accessing product data at the level that you'd like.

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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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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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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 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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Using Data and Messaging to Drive Product Activation

Speaker: Ruben Ugarte, Founder, Practico Analytics

Ruben Ugarte will be focusing on how to improve all aspects of onboarding experiences by understanding how your current onboarding process is stacking up, and giving you the tools to prioritize what to try changing. Balancing qualitative and quantitative data for the whole picture. How to track the impact of your messaging efforts.

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Embedded Analytics, Everywhere

Speaker: Dean Yao, Director of Marketing at Jinfonet

What's the next big trend in analytics software and applications? You've probably used it without even knowing: embedded reporting and analytics. They also want to provide what their users ask for: reporting and analytics from within the context of the applications they are already using.

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The Complete Predictive Analytics Lifecycle for Application Teams

Speaker: Sriram Parthasarathy, Senior Director of Predictive Analytics, Logi Analytics

Applications with predictive analytics are able to deliver massive value to end users. But what steps should product managers take to add predictive analytics to their applications? In this webinar, we’ll walk through an end-to-end lifecycle of embedding predictive analytics inside an application.