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529: Is this the best AI-powered market research approach? – with Carmel Dibner

Product Innovation Educators

The collaboration between AMS and MIT researchers has yielded impressive results, with AI tools not only matching human analysts in identifying customer needs but often exceeding themespecially for emotional needs that humans might overlook. But it is changing, with AI tools that are transforming how we uncover and analyze customer needs.

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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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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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A Decade of Product Management

Melissa Perri

2018: "Can you teach people how to do MVP experiments? They started to see the value. -- 2011: "Product reports to the VP of Engineering." 2019: "Product reports to the CPO." 2019: "Do we have data to prove that is the right way to go?" What are your predictions? . -- 2013: "We don't do experiments here, Melissa.

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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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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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Why you Should Start With Customer Insight

Mind the Product

Without this, product leaders tend to either hedge their bets with small, safe, incremental adjustments or make no progress at all because they lack confidence in the right solution. Gibson’s robot guitar was a great example of a product developed with new, press-worthy features, without being grounded in meaningful customer insight.

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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. Evaluated their options for building a solution themselves or buying something.

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A Win/Win for Your Product - Embedding Analytics for Product Success

Speaker: Stewart Rogers, VP Products, Lambda Solutions

Your product is drowning in data. Your innovative, early adopter type Customers want not only access to it all, but the reporting and analytics capabilities to analyze it all. The rest of your Customers crave better reporting. What about your data?!?! How can use your Customers’ data to uncover patterns?