This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Atif brings valuable insights from a recent PDMA executive workshop where leaders discussed their real-world challenges with strategic decision making and innovation strategy. In this episode, he shares some insights from that workshop and his experience in product leadership.
I was asked to give a ten-minute overview of my continuous discovery framework and then participated in a fireside chat where the host, Cecilie Smedstad , asked me to go deeper in a few areas. I did classic web development before there were frameworks back in the ’90s. This definition is a mouthful, so I like to visualize it.
From Raw Data to Clarity — Cleaning, Sorting, and Synthesising Insights Part 4 (of 5) of the UX Research Playbook series Synthesising qualitative data is similar to reaping the harvest after the diligent effort poured into research — it’s the step where hard work blossoms into meaningful insights. Mural , Miro , etc.)
While adaptability might come naturally to some, others may need tools and guidance to strengthen it. This is why I’ve developed a self-assessment tool designed to help product managers evaluate their adaptability and identify pathways to growth in this crucial area. I quickly interpret data to inform my decisions.
He most recently ran Product Management, Marketing, and Partnerships across Square while reporting to the CEO. Instead of placing all the burden on the manager, we need to shift our analytic lens upward, onto the skip. Running through this exercise has two key caveats. skip reports) with the next principle. Subscribe now.
A report by Arize AI found that 281 Fortune 500 companies view AI as a business risk, a 473% increase from the previous year. Career Transition Compound Effect Framework At the heart of successful career transitions lies what I call the Career Transition Compound Effect (CTCE). to offer 24/7 coaching services.
Picture this: A room full of product leaders huddled around market data like detectives at a crime scene, learning to spot the subtle clues that spell opportunity. Just as a master chef knows instinctively when a dish needs a pinch of salt, great product leaders cultivate an intuition that bridges data and action. The secret?
Here's a framework I use with my coaching clients: Tactical thinking : How do we solve this problem? Try this exercise: Take your current roadmap and ask "Why?" Consider drafting a strategy yourself, using frameworks like the Strategy Stack. It's not just about getting things done. three times for each initiative.
Below, you’ll find what I believe is the most actionable, specific, and straightforward framework for crafting a strategy, for both your product and your company. As Chandra shares below, his framework sits on top of the best strategy wisdom out there (e.g. So we teamed up to make that happen.
How can you balance functionality with aesthetics, ensuring your app is both intuitive and visually appealing? Benefits of responsive e-learning appdesign Firstly, why do you need a functional design in the app where people study focusing on educational materials, not visuals? Examples include Moodle and Blackboard.
Today’s newsletter gives you the tools to influence, adapt, and lead from wherever you sit. The Direction, Alignment, and Commitment (DAC) framework from the Center for Creative Leadership is a game-changer for making an impact - no matter your role. Try this interactive exercise. The best part?
Below you’ll find everything you need to know to nail your analytical thinking interview—a staple of most product interview loops. Now I’ll walk through my framework for acing analytical thinking interviews. I’ve never seen a guide this in-depth, specific, and full of so many real-life examples.
Below, we discuss how to prepare for and ace data engineering interviews. 🧠 About this guide : Written by Thang Tran , a senior data engineer (ex-Amazon, Meta, and Apple) and Exponent interview coach. Reviewed by Deeptaanshu Kumar, a VP of data engineering (ex-Capital One, Freddie Mac).
To find a great name, use the “diamond” framework: Draw a diamond and label “Win” (top), “What we have to win” (right), “What we need to win” (bottom), and “What we need to say” (left). they are told they are naming a bike).
These are some of the most common data analyst interview questions. ✅ Verified : Celine Liu , Uber's former Global Analytics Lead, wrote this guide. Celine has conducted 100+ interviews across analytics, operations, and strategic roles. 🧠 Learn more : Check out our complete data analyst interview prep course.
But figuring out which sales tools you should buy and invest in – let alone what each tool even does – can be a daunting task. This is especially true when you consider the seemingly endless list of sales tools to choose from. Before we begin: how to choose your sales tools. Better tools, not more tools.
What is data-driven analytics in SaaS? How to conduct user data analysis? What are the best analyticstools for the job? TL;DR Data-driven analytics describes the process of collecting, analyzing , and interpreting customer data to help organizations make better-informed product and strategic business decisions.
The article here focusses on business criterion to use to better evaluate if a predictive model is ready for production and the associated risk when the predictions are wrong. A simple / practical framework is used to do this evaluation with three examples. Predicting the future gives businesses a competitive advantage.
“Successfully managing complex sales requires a different level of visibility into your deals” To get visibility into large deals, I developed a visualframework – which I call the Agile Arrow – that applies popular project management principles to the work that we do as salespeople. Act II: Building a visualframework.
In doing so I hope to help demystify what you actually do in the role, provide a framework for assessing what dimensions of the role you are already good at delivering against, and opportunities for improvement on each. Design: Customer Discovery Insights. Whenever you are surprised it means you've collected a valuable insight.
Data PM: organizations dealing in data products (building AI/ML based products) prefer a PM with data science background so that they can appreciate the problems well and being able to work with data engineers/scientists. Hence roadmapping is a crucial exercise which can make or break your product. Product Roadmap.
Data analysis is integral to a product manager’s job – it’s what helps them build impactful products. This article dives deep into data analysis for product managers. User data analysis helps: Provide direction for product development , allowing for effective resource allocation. What is data-driven product management?
Referring to people as product owners who do not manage a product and do not exercise the right ownership is wrong in my mind: It creates confusion and it sets wrong expectations: Someone who owns a product part cannot take on the responsibility of maximising the product’s value and achieving product success. SAFe Product Owner.
I wanted to share with you the framework I use when doing this. I gather data through surveys about observations. Lots of data goes into pinpointing. Below is a brief overview of the framework that I use and a few signs of where you should start if you want to run this exercise yourself.
Lately, some of the predictive projects are taken up because of the hype and those are the projects that not only fail to deliver success but also tend to cast a shadow on the AI industry in general. Before one moves ahead with a predictive project, it’s extremely important to clearly articulate the value that the project will deliver.
3:18] You made a move from being a senior product manager in the medical industry at a company creating surgical implants to being the senior director of product management for an IT services company specializing in web hosting. I knew I had to apply the framework I had used in understanding my previous users to users in this new industry.
If you’re looking to improve your team's work, a product management framework can be an excellent starting point. A framework is a set of guidelines or principles that can help guide your team’s decisions and provide a common understanding for all team members. Example of Applying DACI Framework 2. DACI What is it?
Chris shared the story of how he introduced the opportunity solution tree to several teams at his company and a few of the iterations that helped make the tree an indispensable tool at SuperAwesome. He works at SuperAwesome, a UK-based company that develops tools and services to make the internet safer for kids. Tweet This.
To help hiring managers and recruiters, like myself, decide whether or not to interview you, it can be a great exercise to treat your resume like a professional product. Data-Driven. As a hiring manager, I want to hire people focused on gathering good data, s o we can craft good hypotheses about what to build next.
Measuring design and utilizing data are essential steps towards creating a sustainable product. Let me show you how to use data to improve your product. The answer is out there, and it lies in data. Metrics help turn data into digestible information, which can help in drawing conclusions and making decisions.
We’ll learn about how they started rolling out the product trio model at Botify, some of the tools and tactics they’ve developed to guide their work, and what they’ve observed from the research they’ve conducted with other product leaders and trios. Going through this exercise also revealed that some tasks are in between roles.
These can take the form of project status reports or meetings or Gantt chart creation or intake of new ideas. Hope: For teams that have a lot of visuals that they are already working on, one of the things that I recommend is to try to see if you can shift some of those meeting-related stakeholder updates to sharing of artifacts. .
Up until this point, to understand our customers, we had primarily relied on the Jobs-to-be-Done framework , product sense, research insight, sales input, and a belief that our customers were companies just like us. Instead, it’s an ongoing exercise to capture relevant differences between your customers.
In her role as Chief Product Officer, Lily looks after Product, Design, Research, and Data within the business. The practice run was so helpful, and at the end of the day we concluded the sprint and felt more confident about the framework. But it would have been even better to have done this multiple times,” says Lily.
The Product-Market Fit Pyramid is the key framework, and it has five layers that build on each other. Adding that attribute adds predictive power to your model. I use an importance vs. satisfaction framework to define how well-served or underserved each need is. When I do this exercise, people get so fired up.
Just as we listen to gain insights into what we build, we should also listen to the team’s feedback when deciding on how we build it. Additionally, just as there is a necessity to take in the value of collaborating with teams internally, there is an interplay of pulling in valuable data from the individuals who use the product.
Most of our tools and processes around product/feature prioritization are heads-down analytical: RICE, opportunity trees, Kano, weighted 16-column spreadsheets, WSJF, Eisenhower, whatever. Our " or "data migration tool" or "custom report for HSBC," but the executive team doesn't. And
There are enough stories of data breaches and cyber attacks to chill even the savviest security engineer to the core. Suddenly, the team got to know SOC 2 Reports all too well and realized just how burdensome and unscalable it could become, especially for high-growth startups. And that’s where people like Adam Markowitz come in.
That can mean a lot of things: the primary goals I set for myself were (1) use data better and more frequently to make decisions, (2) better understand & improve the relationship between UX/Design and Product in my organization, and (3) to launch my own side project but with the mindset of launching fast, learning, and improving quickly.
I am not in favor of assigning home exercises. A typical product sense and execution interview might commence with an intentionally broad question, such as, “Imagine you’re tasked with developing an AI model to predict the success rates of a dating app.” Here, I anticipate discussions around the necessity and design of the AI model.
Instead, you need a comprehensive customer onboarding framework to give you a sense of structure… and set you and your SaaS up for success. A customer onboarding framework is a structured way of thinking about the set of actions, activities, and tools that go into helping a customer experience value. Action-packed, right?
What’s a product metrics framework? We also look at how product managers can use Userpilot to implement product metrics frameworks. TL;DR A product metrics framework is a set of metrics used to measure the performance and success of a product so that you can improve it. What is a product metrics framework?
Most products begin with functionality, but as I do this exercise with the companies I work with, they often realize that something is missing, even if the technical capabilities are there. Look at the data you have, but then, as with anything else in product, remember that data only tells part of the story. Stay tuned.
It’s more about looking for new ways to collect insights from users, uncover underlying assumptions, and explore the opportunity space. First, product work is informed by foundational research done by the trivago UX research team based on the Jobs To Be Done (JTBD) framework. First Steps in Mapping out Opportunities.
We organize all of the trending information in your field so you don't have to. Join 96,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content