In Defense of Small Data

ProductCraft

“Big data” may be sexy, and quant research is great for. The post In Defense of Small Data appeared first on ProductCraft by Pendo. Perspectives Big data Interviews Qualitative research Research“How many people used our new feature last quarter?”

67

Inside the Mind and Methodology of a Data Scientist

Birst BI

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. To solve practical decision problems, the Data Scientist typically uses combinations of these methods.

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.

Data Acquisition: A Primer for IoT Product Managers

Tech Product Management

In this post I provide an introduction to the world of data acquisition and […] The post Data Acquisition: A Primer for IoT Product Managers appeared first on TechProductManagement.

Top 10 industries for monetizing data: Is yours one of them?

data exhaust Top 10 industries with data. value of data Customer data will no longer be relevant only to an organization’s marketing and financial. products out of their customers’ usage, behavioral, and transactional data. Monetizable data ? Data on payors.

Here’s Why Every Product Manager Must Learn to Love Data

UserVoice

“Big data.” It’s one of Silicon Valley’s favorite and most annoying buzzwords, yet there’s no data shortage in sight as data companies continue sprouting (and growing) like weeds. Not being a “math person” or a data scientist is no longer a valid excuse to diss data.

The Fundamentals of Building Better Data Products

Mind the Product

Data is the world’s most valuable resource, according to The Economist, and the companies that primarily deal in data – Google, Amazon, Facebook and the like – are among the most valuable in the world. Data Moves to the Centre of the Value Proposition.

Why you Need Quantitative AND Qualitative Data

Mind the Product

Qualitative versus quantitative data: we’ve all been involved in a conversation debating their respective merits at some point in our careers. So which type of data is better? Another angle is the softness and hardness of the data. We’ll need more soft data to find the answer.

Why Data Science and UX Research Teams are Better Together

Mind the Product

Chris shares real-world examples and lessons learned as User Testing established its Product Insights team, a team which is made up of UX researchers, data scientists and data engineers. Most companies’ user research and data science teams work separately.

UX 143

3 Ways to Enlist Your Usage Data to Drive Product Development

Mind the Product

Having reliable data available in real-time allows you to quickly and accurately sort through what is a valid concern and what is not, keep your team on task, and let data-driven product development reign. Let’s dig into three examples and look at how usage data can help. With usage data, you can quickly get a sense of just how pervasive the bug is, and what sort of effort needs to go into fixing it. Usage Data Sheds Light.

Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

MONETIZING ANALYTICS FEATURES: Why Data Visualizations. Data Visualizations Have Gone From Rare to Ubiquitous 1 If DataViz Is Old News, What’s the Future of Analytics? Ubiquitous Five years ago, data visualizations were a powerful way to diferentiate a software.

5 Ways Real-Time Data Can Make Your Business More Efficient

Indicative

Now, Indicative customers who use Snowplow will have the power to analyze their business data in real time. Snowplow’s open-source software already allows companies to collect rich and detailed event-based data about their customer journey. With real-time data, you can: 1.

Data v. Opinion: The Ultimate Battle

Clever PM

One of the challenges that we commonly run into as Product Managers is the battle between opinions and data. And though it would be nice to pretend that data always wins, and that there's always truth in Jim Barksdale's famous quote, "If we have data, let’s look at data. Let's talk about some common situations where data bends to opinion.

B2B data: 4 critical factors to improve data quality

DemandMatrix

Your B2B data should be an asset on your balance sheet, not a liability. Making your data invaluable to your organization requires the right approach. To start with, improving the quality of your data is not a one-time event. B2B data

B2B 52

IoT Data Monetization

Tech Product Management

In this episode of the IoT Product Leadership podcast, we dive deep into IoT Data Monetization approaches. The post IoT Data Monetization appeared first on Daniel Elizalde. My guest is Aleksander Poniewiereski, who joins us today all the way from Poland. Aleksander is the Global IoT Leader at EY where he is responsible for leading their advisory practice focused on IoT. Aleksander brings a unique perspective that I haven’t […].

Nine companies share 30+ best practices for creating embedded analytics products

methods such as surveys for gathering market data; and. are trying to solve and what data they need to do so.” ? data preparation activities to prove. data prep and report creation, or your customers’ IT teams. customers to generate their own reports and data, rather.

Five Ways to Foster Data Literacy Across the Organization

Indicative

Keeping track of how customers are interacting with their brands, and how long products are taking to catch on with audiences traditionally requires data teams to conduct lengthy analysis. So, here are five ways to foster data literacy across the organization.

Data in the News: A Better Commute, Remote Internet Access, and Venture Capital Bias

Indicative

Check out the big data news stories you need to know about this week: 1. Swiftly is a transit startup that wants to arm commuters and transit operators with data. The software integrates directly with GPS systems of public transit to collect reliable real-time data, Inc reported.

People Are Your Data

dscout People Nerds

Tricia Wang on why the digital age means everyone (even non-researchers) should understand ”thick data.& &#8221

67

Humanize Your Data

Joe Cotellese

So I popped on over to a time conversion website and plugged the data in. This data meant a lot more to me then pure hours. This simple change makes the data so much more consumable. So, the lesson here my friends is look at the data you present to your users.

The 5 Levels of Analytics Maturity

data or analysis they need, whether it’s a fundamental tool like Excel. Making data analytics work for. For some users, simple data visualizations and dashboards. We don’t have data yet for Level 4, but. expand self-service data discovery to include every user.

The Modern Product Team Part II: On Being Data-Driven

ProductCraft

The Modern Product Team Part II: On Being Data-Driven. Share Post: Not so long ago, finding “designer” and “data” in the same sentence seemed unthinkable. The second value, which I’ll discuss today, is being data-driven. Skip to content. ProductCraft by Pendo. Subscribe.

5 Ways to Foster Data Literacy Across the Organization

Indicative

Keeping track of how customers are interacting with their brands, and how long products are taking to catch on with audiences traditionally requires data teams to conduct lengthy analysis. So, here are five ways to foster data literacy across the organization.

Let’s Engage – Live Data Visualisation at MTP Engage Hamburg 2018

Mind the Product

In Daniel Goddemeyer and Dominikus Baur we found the perfect partners for this, so we asked them to run an interactive data visualisation session immediately before the first coffee break.

Where Should Data Science Report?

ProductCraft Debates

Data and product are inherently intangled; whether it’s because product managers heavily rely on data, or because data scientists mine the product for insights, these disciplines’ Venn diagram has quite a bit of overlap. Increasingly, as product organizations become drivers of growth, they are getting data scientists, with an understanding that the product is the best. The post Where Should Data Science Report?

5 Early Indicators Your Embedded Analytics Will Fail

thrilled to finally visualize their data. They ask to explore data on their own, create and. share analysis, and connect new data sources to the. requests for new and more complex data visualizations, the ability to customize dashboards, and real-time.

What Product Managers Should Know About Data Science

Craft.io

Data Science is one of those professional terms that seems to have appeared suddenly and spread rapidly to industry conversations everywhere. What is Data Science? Simply put, Data Science means utilizing data and technology to make better decisions.

Personalization with Anonymous Data (Not an Oxymoron)

Revulytics

Depending on what you read, GDPR is either a boon for marketers, finally giving them a way to access quality data, or akin to that massive computer being rolled into the Sterling Cooper offices circa 1969 in Mad Men, requiring the overhaul of entire marketing strategies and technology.

AI+BI: Augmented analytics will soon bring data-driven insight to the masses

Birst BI

If you’re a business intelligence (BI) and analytics application user, it’s likely that “data-driven insight to the masses” will soon be top-of-mind. Some data discovery vendors tout that they already deliver “self-service to the masses,” but that’s a dubious claim.

The Impact of User Research Technology on Data Quality

Generation Focus

Qualitative data gathering methods such as in-depth interviews and focus groups have existed since the 1920s, when the importance of demographics and consumer insight first came into the spotlight. Quantity is not always better than quality, even in data collection.

New Study: 2018 State of Embedded Analytics Report

In a digital era fueled by data and automation, analytics has evolved from an afterthought to a necessity. their data in the digital era. dashboards and data visualizations, and embedding sophisticated features such as predictive analytics. data sources in the application.

3 Ways ClassPass Used Data to Make a Business Pivot

Indicative

Sometimes, what you think your customers want doesn’t match up with the data. But the data showed her that they liked sampling different classes, and wanted more. These are the three data insights we learned from Payal’s pivot.

Demo 59

Make your Product Intuition Stronger with Data

The Product Coalition

What is your product strategy, intuition or data? Summary As product people improving our craft, we should make it a habit of validating our product intuition with data. As product people, we should make it a habit of validating our product intuition with data.

Technographics - The Next Big Thing For Every Data Driven Marketer

DemandMatrix

It is not uncommon for today’s marketer to make generous use of data science to draw more from behavioral data. There have always been different data types to influence a B2B marketer’s future marketing strategies. It all depends on how one interprets the data after all.

B2C 52

The Value of Pricing Data from Your Distributors

Pragmatic Marketing

You are about to read some details of a project I was part of that collected and analyzed some pricing data from one of our distributors. Many years ago, when I was running pricing for a semiconductor company, we put on a huge effort to gather competitive pricing data for thousands of parts.

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. Don't miss King’s data expert (dare we say king?)

The Value of Pricing Data from Your Distributors

Pragmatic Marketing

You are about to read some details of a project I was part of that collected and analyzed some pricing data from one of our distributors. Many years ago, when I was running pricing for a semiconductor company, we put on a huge effort to gather competitive pricing data for thousands of parts.

You’re Missing Valuable Data Insights. Here’s How To Change That.

Indicative

A new partnership between Snowplow and Indicative is solidifying in-house data ownership as the new normal. Snowplow customers already understand the value of owning their own data: it gives them the freedom to leverage that data to provide insights that might otherwise be locked away.

Are You Data-Driven or Data-Informed?

Johanna Rothman

One person gave me a new saying about metrics (at the end, during the Q&A): Are you data-driven or data-informed? If you want predictions and targets, you use data to drive the decisions and work. If you want the ability to replan you use data to inform your next steps. Note: data-informed does not mean you don’t create broad-stroke plans, such as roadmaps and gross estimates. And, I use the data about my cycle time to inform my replanning. (I

Data Protection: How to Prepare for GDPR by Creating a Culture of Stewardship

Mind the Product

It seems to be a weekly occurrence that an organisation suffers some form of hack or data breach. To prepare for the forthcoming GDPR (I’ve written more about the GDPR’s impact separately) I’ve become my company’s data protection officer (DPO). Part of this role involves training in data protection and passing on this training to colleagues. Could anyone in my team afford a personal fine for a “deliberate” loss of data? Understanding Data Protection.

Mixing Qualitative & Quantitative Data with Storyboarding

Speaker: Tristan Kromer, Lean Agile Coach, Kromatic

Qualitative data from UXers should not compete against the quantitative data product owners need for their business model. Qualitative vs. Quantitative is a silly argument.