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Product managers are now expected to be not only customer-obsessed but also data-fluent. In this episode, Jenna Gaudio shares essential insights on how modern PMs must evolve their skillsets to handle massive data flows, navigate regulations, and responsibly craft intelligent product experiences.
While “use data to drive decision-making” sounds obvious, there’s a HUGE gap between saying it and doing it well. So, how do you get started with product analytics ? In this article, we’ll talk about: What product analytics is and why you need a solid strategy. What is product analytics?
This unique combination developed both her analytical thinking skills and her ability to question assumptions – capabilities that would later prove valuable in her product career. Over ten years, she rose through the ranks until everyone in the company reported to her.
Using a custom ChatGPT model combined with collaborative team workshops, product teams can rapidly move from initial customer insights to validated prototypes while incorporating strategic foresight and market analysis. Instead of focusing solely on today’s customer problems, product teams need to look 2-5 years into the future.
Which sophisticated analytics capabilities can give your application a competitive edge? In its 2020 Embedded BI Market Study, Dresner Advisory Services continues to identify the importance of embedded analytics in technologies and initiatives strategic to business intelligence.
He shares practical insights from the Product Development and Management Association (PDMA) framework and explains how product managers can use these principles to improve their product development process. Portfolio Management During our conversation, Jack shares valuable insights from managing product portfolios at Sony Ericsson.
Drawing from his 20+ years of technology experience and extensive research, Nishant shared insights about how these activities vary across different organizational contexts – from startups to enterprises, B2B to B2C, and Agile to Waterfall environments.
For example, if your brand centers around being a data-driven decision-maker, ensure that your communications emphasize this. Share case studies, write posts that highlight your analytical approach, and offer insights backed by data. Stay up-to-date with industry trends, emerging technologies, and new methodologies.
Introduction to customer satisfaction surveys Customer satisfaction surveys are vital tools for understanding what customers think, feel, and experience. Surveys provide a range of insights, from quick feedback after a purchase to in-depth assessments of brand loyalty. Don’t worry, we’ve got you.
Speaker: Megan Brown, Director, Data Literacy at Starbucks; Mariska Veenhof-Bulten, Business Intelligence Lead at bol.com; and Jennifer Wheeler, Director, IT Data and Analytics at Cardinal Health
Join data & analytics leaders from Starbucks, Cardinal Health, and bol.com for a webinar panel discussion on scaling data literacy skills across your organization with a clear strategy, a pragmatic roadmap, and executive buy-in. In this webinar, you will learn about: Launching data literacy programs and building business cases.
How product managers are transforming innovation with AI tools Watch on YouTube TLDR In this deep dive into AI’s impact on product innovation and management, former PayPal Senior Director of Innovation Mike Todasco shares insights on how AI tools are revolutionizing product development.
James shares insights from his research studying companies that consistently launch successful products. James shares that many teams are now working with their second or third generation of AI tools, particularly in sales and marketing. This makes product launches valuable testing grounds for innovation.
Yet, no matter how sophisticated the technology got, one problem remained stubbornly consistent: Decision-making was still too slow. The insights were buried in dashboards. And the noise around each new BI tool? In theory, leaders had access to more data than ever. No dashboards. It kept getting louder.
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.
Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.
This definition is a mouthful, so I like to visualize it. I’m going to walk through this visual quickly, and then Cecilie and I are going to dive into this in more depth. Using the Opportunity Solution Tree to Guide Discovery The visual at the center of this is called an opportunity solution tree. It’s that simple.
From new UX-related technologies and automation to personalization. Well start with an overview and explore how AI can take on tasks such as analyzing user data and automated prototyping to help professionals connect with users on a humanlevel. This fast-paced testing accelerates design cycles and helps refine products in lesstime.
Note that Ive decided not to state the names of the tools I found, partly as the AI landscape is changing rapidly and partly as you should research and select the tools that work best in your context rather than trusting my judgment. [2] 2] Market Research AI-based tools can discover user and customer trends using predictiveanalytics.
This approach has informed her success across different industries and roles, from retail to technology. Anya’s development of Taelor offers valuable lessons in how to validate and expand upon initial product insights. This led her to explore whether others faced similar challenges.
64% of successful data-driven marketers say improving data quality is the most challenging obstacle to achieving success. The digital age has brought about increased investment in data quality solutions. However, investing in new technology isn’t always easy, and commonly, it’s difficult to show the ROI of data quality efforts.
In this post, were exploring the conversation we had in one of our Productside Stories episodes this season with Joeri Devisch , a veteran of product, technology, and transformation work at global companies. Joeri emphasizes that data and intuition are not oppositestheyre collaborators. Data + context = better decisions.
Its a tool. And tools only work when you know what youre building. Some examples: Optimizing operations: AI can streamline workflows, predict bottlenecks, and cut inefficiencies. Uncovering insights: Machine learning can analyze massive datasets and surface patterns youd never catch on your own. Saving time andmoney.)
Often, powerful technology is already available; the magic lies in how you interact with it. Look for unique applications of the tools you already have. This approach can reveal unexpected insights and user preferences, helping you shape the final product. Listen now on Apple , Spotify , and YouTube.
The Rules Are Blocking Your Progress These so-called “best practices” promise structure and alignment, but they often trap teams in a cycle of predictability and prevent breakthroughs. We know roadmaps provide structure, alignment, and predictability. Lets take them apart. and pursue the answers. Spoiler alertthey wont.
Enterprise interest in the technology is high, and the market is expected to gain momentum as organizations move from prototypes to actual project deployments. Ultimately, the market will demand an extensive ecosystem, and tools will need to streamline data and model utilization and management across multiple environments.
Transforming user experience in cars-as-a-service industry through Strategic AI/ML Integrationa UX casestudy. Overview This case study focuses on integrating AI/ML to improve user experience in the car-as-a-service automobile marketplace. Prompt samples based on real Data on how customers source for cars in rental marketplaces.
It’s what you do with the behavior data your app collects. And by behavior data, I dont mean installs (thats the easy part). Mobile app tracking captures data on how users interact with your app, including actions such as screen views, button taps, session length, and feature usage. What is mobile app tracking?
Listen to the audio version of this article: [link] A Product Strategy System The product strategy system in Figure 1 consists of four main parts: people, processes, principles, and tools. Are the right tools applied? Next, collect the relevant data. Are they properly empowered and adequately qualified? If so, what are they?
And Im not talking about pretty visuals for the sake of it. I mean frictionless, user-obsessed, data-driven design choices that guide your customer from just browsing to Add to Cart without ahiccup. In the bustling world of eCommerce, UX design isnt just a buzzword; its a strategic tool that can make or break your businesss success.
Using the lens of a superhero narrative, he’ll uncover how AI can be the ultimate sidekick, aiding in data management and reporting, enhancing productivity, and boosting innovation. Tools and AI Gadgets 🤖 Overview of essential AI tools and practical implementation tips.
It gives you the ongoing, actionable insights you need to grow market share, secure stakeholder buy-in, and optimize your brand strategy. According to Gartner®, while 57% of brand leaders conduct brand health assessments, only 21% find those insights actionable. That’s where brand health tracking comes in.
Put simply, we craft smart products that transform mundane shopping experiences into personalized adventures, like suggesting the perfect pair of sneakers based on your unique sports styleall thanks to Predictive Analysis. Curious to learn more? Keepreading! So, how does everything unfold?
We uncovered a number of insights in the data, but the biggest and perhaps most unexpected theme is the rise of the IC career path. As product managers move up the ranks, salaries predictably increase, especially for individual contributors (ICs). If it’s not centered, the data may be skewed higher or lower.
Accessibility in UI/UX design refers to creating interfaces and experiences that can be used by everyone, including individuals with disabilities such as visual, auditory, cognitive, or motor impairments. It involves considering how different users interact with technology and ensuring equal access to information and functionality.
Marketing technology is essential for B2B marketers to stay competitive in a rapidly changing digital landscape — and with 53% of marketers experiencing legacy technology issues and limitations, they’re researching innovations to expand and refine their technology stacks.
Customer churn is one of the biggest challenges businesses face, yet many organizations struggle to accurately predict and prevent it. With the emergence of AI-powered customer intelligence software , businesses now have a transformative tool to predict churn risks and act before customers leave. companies lose $136.8
Simplify security Daniel Lereya , the Chief Product and Technology Officer at monday.com, shares how he and his team realized they were being outpaced by competitors and how that realization completely transformed how they operate and allowed them to build a global powerhouse, doing over $1 billion in ARR, with 245,000 customers worldwide.
Customer onboarding is the process of welcoming new customers to your product or service and helping them utilize the product and maximize the value of their purchase. Onboarding automation uses technology (such as conditional flows and sequences) to guide users through their initial experience with your product. The answer is a lot!
How New Heuristics Are Reshaping the Creative Process Between Humans andMachines Image generated byChatGPT When the wave of generative AI tools began flooding the market, I must confess my reaction was mixed: a sense of fascination for the possibilities and concern for the ethical challenges looming on the horizon.
Today, many B2B companies use ABM teams or technologies to make sales. Get insights on: Building a solid data foundation Targeting, signals, and optimizing engagement channels Aligning your ABM program with the customer life cycle Establishing effective KPIs and reporting strategies
Through these insights, you’ll be better equipped to handle the pressures of managing up and leading your product toward success. Often, these requests are made without supporting data or customer feedback, which can create tension between PMs and top-level executives. Use data to support your position and explain the trade-offs.
Pinterest, positioned uniquely as a visual discovery engine, has significant potential to leverage personalization to foster deeper user engagement, retention, andloyalty. Key insight for Pinterest: A platform can successfully combine social personalization (friends/following-based) with content personalization.
As technology moves beyond flat screens into 3D spaces, designers face a new challenge: creating experiences that users don’t just see, but step into. Affordance Visual cues that indicate how to interact with digital elements, reducing the need for instructions. Example: Seeing your hand hold tools during VR training.
Insights from Productized offer a glimpse into what will distinguish leaders and organizations in the future. Moving beyond the outdated 'mini-CEO' product mindset and embracing the sharing of knowledge and insight. Balance Technology and Humanity: Use AI to enhance human capabilities, not replace them.
As enterprises evolve their AI from pilot programs to an integral part of their tech strategy, the scope of AI expands from core data science teams to business, software development, enterprise architecture, and IT ops teams. The Forrester Wave™ evaluates Leaders, Strong Performers, Contenders, and Challengers.
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