data and analytics

Closing the gap between data and product development

The goal is always to make data make sense to everyone in the company.

The Four Cringe-Worthy Mistakes Too Many Startups Make with Data

In this exclusive interview, Richardson points out four of these approaches that data teams industry-wide should watch out for, and how leaders can break from the pack to better serve their strategic goals.

Scaling Dropbox with Data

Interview w/ Harshjit Sethi — Sequoia Capital, Dropbox, McKinsey

I’m Sorry, But Those Are Vanity Metrics

In this exclusive interview, Tabb shares how to abide by metrics that generate direction — not pats on backs — so that your company can act on what’s most essential to a business. He contrasts vanity and clarity metrics across a handful of types of companies — including service, advertising, software and ecommerce — to demonstrate how to find proxies that better predict behavior over time. Lastly, he emphasizes how to prevent teams from getting seduced by vanity metrics — and tips on honing their instincts for real, productive measurement.

SaaS Metrics and Definitions of KPIs from a Growth Hacking Perspective

Because good ideas can come from anywhere – no matter if your business is at a startup, growth or mature stage. If anyone on your team, even new hires, do not understand the meaning of key SaaS metrics, you can be missing out.

The only metric that matters

You need a metric that specifically answers this. It can be “x people did 3 searches in the past week”. Or “y people visited my site 9 times in the past month”. Or “z people made at least one purchase in the last 90 days.” But whatever it is, it should be a signal that they are using their product in the way you expected and that they use it enough so that you believe they will come back to use it more and more.

eBay's VP Design, Dave Lippman, on dancing between data and intuition lessons from Apple & eBay

Ebay's VP Design and Creative Director, Dave Lippman, shares his experience designing at Apple and Ebay, the differences in their approach to data vs. intuition, and how he's learned to dance between the two.

Building better products through Data

Ben Foster and Bob Moesta share stories and insights about how the key to gathering customer feedback is through the deeper, often unstudied observations. Leslie Bradshaw then joins in with the idea it's never too early to start testing a new product, we just have to be willing to put it to paper. Then Ben Foster closes the interview with a story about how a company was able to pull data from bike thieves in a creative way, and how the company used that data to create the ideal product.

Unique and interesting ways companies are using Data

Examples of companies using big data in unique ways: Yelp is using modern search terms to find the perfect restaurant, businesses are changing their marketing depending on the current weather, Google tracks their employee's patterns to see if they are thinking about quitting, and Joel Selanikio discusses about using big data to transform global health policy.

Democratizing Data is Product Management

Jeff Feng, Product Manager at Airbnb, shares how he launched “Data University” to empower employees to make data-informed decisions and how he got over a third of employees to attend a course.

Google Analytics

Google Analytics is a freemium web analytics service offered by Google that tracks and reports website traff

Mixpanel

Deeply understand every user's journey with instant insights for everyone on mobile and web.

Fabric - App Development Platform for teams

From development to launch and beyond, Fabric gives everyone on your mobile team a complete, real-time understanding of your app's performance and health at every stage. Crashlytics · Answers · Fastlane.

Amplitude

Get web and mobile analytics for building better products. Amplitude is the only analytics software built for modern product teams.

Prodlytic

Specialized analytics for product people - automatically record every user interaction with a single snippet of code.

Lean Analytics: Use Data to Build a Better Startup Faster

Lean Analytics lays out practical, proven steps to take your startup from initial idea to product/market fit and beyond. Packed with over 30 case studies, and based on a year of interviews with over a hundred founders and investors, the book is an invaluable, practical guide for Lean Startup practitioners everywhere.

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.

Naked Statistics: Stripping the Dread from the Data

For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions.