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Mind the Product

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Deep dive: Crafting your product vision and mission

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How Google makes AI work at Enterprise scale – Miku Jha (Director, AI/ML and Generative AI, Google Cloud)

5 ways to invent and simplify as an AI/ML product manager

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Building your own user experience and software stack: This week’s product news

Andres is a freelance writer and digital marketer with a background in engineering and a keen interest in the latest technology advancements. He currently helps tech companies and startups tell their stories by turning their complex ideas into easy to understand material. You can reach out to him on LinkedIn

Andres Phillips

<p>In this <a href="https://www.mindtheproduct.com/producttank/">ProductTank London</a> talk, <a href="https://www.linkedin.com/in/helen-hewitt-a8371a2/">Helen Hewitt</a>, Global Head of Data Transformation at <a href="https://www.dowjones.com/">Dow Jones</a> takes us through her personal journey with data and her work at Dow Jones in developing their data culture. Her key points include:</p>
<ul>
<li>Driving a data culture</li>
<li>How we view our data</li>
<li>DataSET</li>
</ul>
<p>Watch the video to see Helen’s talk in full. Or read on for an overview of her key points.</p>
<h2>Driving a Data Culture</h2>
<p>Most of the departments at Dow Jones were very siloed. Helen talks about how a decision was made to begin some initiatives to change the data culture at the company. She and a few others became part of a group called Nova, which took a holistic look at data across Dow Jones. Utilizing a design thinking methodology, they began to conduct interviews with global departments as well as workshops with customers. Through these initiatives, they were able to discover the thing people were doing with data and identify the impact data could have in various areas as well as the opportunities for the company.</p>
<h2>How we View our Data</h2>
<p>Data means different things to different people. The Nova initiative wasn’t the first time Down Jones had been working with data. Previous initiatives included the dynamic paywall on the Wall Street Journal website. They were able to collect multiple pieces of data about a person and use real-time analysis to determine their propensity to subscribe. This helped to boost onsite conversion rates by 5X over a 3 year period.</p>
<p>Helen explains how Dow Jones had already been collecting large amounts of customer data from multiple locations around the world. This data was found in over 40 locations and made marketing difficult as teams couldn’t locate the right data quickly. The solution they found was to build a data lake. Marketing teams were able to personalize activity to drive content habits and create a better product experience for their users.</p>
<h2>DataSET</h2>
<p>A DataSET team launched in 2019 to manage data challenges at the company. Some of their initiatives include a centralized data hub and a data academy to train Dow Jones personnel on how to use data with content related to their business.</p>
<p>The key takeaways from this talk are that as product people we need to make data more of a business partner. Embed data experts in different business units and if you’re unfamiliar with data get out of your comfort zone and learn as it will benefit you in the future.</p>

core/freeform

How to lead data-centric product teams: Jon Mora (Chief AI Officer, Zefr)

How to be a better data-driven product manager

User insights for product decisions by Cris Valerio

Data scaling for startups by Crystal Widjaja

Make Better Product Decisions by Using Quantitative and Qualitative Data, by Brian Tran

Testing Business Ideas, by David Bland

Developing a Data-Driven Culture at Dow Jones, By Helen Hewitt

When A/B Tests Aren’t Enough, By Scott Castle

Using Data to Build a Brand, by Abba Newberry

Socially Preferable by Nathan Kinch

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