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He explains how to conduct an AI-powered design sprint that transforms product concepts into clickable prototypes in just hours instead of weeks. This strategic foresight approach to product development isn’t just about making predictions – it’s about understanding how customer needs and market conditions will evolve over time.
This week on Productside Stories, host Rina Alexin sits down with Abner Rosales , Senior Director of Product Management Analytics at Experian. Making Smart, Data-Driven Decisions Decision-making can make or break your product, especially when data is involved. Why Listen to This Episode?
Without effective UX analytics that goes beyond collecting data, you’re losing valuable customers. Unfortunately, the research backs this up, with a staggering 90% of users reporting that they stopped using an app due to poor performance. It covers key topics, such as: Defining UX analytics. What is UX analytics?
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?
Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.
And not because AI itself is broken, but because companies keep treating it like a science project instead of a tool that actually needs to solve problems. Itll be the ones who know how to separate hype from reality, focusing on pragmatic AIAI that works, delivers value, and integrates seamlessly into business processes.
When your company adopts multiple SaaS solutions to drive productivity, you unknowingly create a perfect storm for data fragmentation. Your customer information lives in Salesforce, while your support tickets are in Zendesk, your product usage data in Mixpanel, and your marketing campaigns in HubSpot. Sound familiar?
You can gather all the user feedback or behavioral data you want or even generate tons of Google Analyticsreports. Despite all these efforts, you’re probably still not acting on product analytics correctly. Why actionable product analytics are important. This causes siloed data and integration issues.
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.
Your financial statements hold powerful insights—but are you truly paying attention? This isn’t a dry accounting lesson—it’s a dynamic session designed to help you decode your numbers and turn financial data into a strategic advantage! Don’t just report the numbers—understand what they’re telling you. Register now!
Let’s review everything your customer success team has to do in the absence of any customer success tools. Collect customer data to calculate complex formulas for tracking metrics, monitor customer health scores, and resolve support tickets while continuously trying to improve retention and expansion.
You know your product collects tons of data. Datavisualizationtools help turn your messy spreadsheets into clear, interactive insights. The best ones dont even need SQL or data science skills. Because product analytics should be easy and accessible for everyone, not just data experts.
The opportunity solution tree helps visualize all the work that goes into continuous discovery. And while opportunity solution trees have become increasingly common among product teams, there’s still plenty of room for customization, both in the way you set up your trees and the tools you use to build them.
Reveal Embedded Analytics For product owners, leveraging data is not just an advantageits a necessity. Product analytics empowers you to understand gaps in your offering and how users engage with your product. Both embedded analytics and product analytics are designed to help product owners in diverse ways.
Greg Loughnane and Chris Alexiuk in this exciting webinar to learn all about: How to design and implement production-ready systems with guardrails, active monitoring of key evaluation metrics beyond latency and token count, managing prompts, and understanding the process for continuous improvement Best practices for setting up the proper mix of open- (..)
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His insights are grounded in decades of hands-on leadership across engineering, business development, and product strategyand his take on innovation is both practical and bold. Joeri emphasizes that data and intuition are not oppositestheyre collaborators. Data + context = better decisions. Intuition isnt the enemy of analytics.
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.
Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage
This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. When developing a Gen AI application, one of the most significant challenges is improving accuracy. The number of use cases/corner cases that the system is expected to handle essentially explodes.
Heres how to take insights from customer feedback and turn them into results. Build a foundation that drives action Use reportingtools to translate feedback into trends. Turn survey responses, review data, and post-purchase feedback into clear dashboards your teams can actually use. Level it up!
90% of executives say they prefer visual storytelling over dense reports. Its a technique borrowed from the world of film and designbut it might just be the most underrated tool in a product managers toolbox. Customers dont care about data structures. How: Whats your unique approach? They care about impact.
In our latest Productside webinar, Becoming an Effective Product Management Leader , Principal Consultants Roger Snyder and Kenny Kranseler delivered a no-nonsense roadmap for new leaders who want to nail their first 90 days (and beyond) and get the tools on how to become a product management leadereffectively. Do I push back?
How to Get Started: Audit the Product Backlog: Pinpoint low-effort, high-value opportunities to drive quick results. Pro Tip: Pair your quick wins with data. A dashboard showing metrics like feature adoption or user engagement amplifies your credibility. It shows youre thoughtful, analytical, and focused on results.
Speaker: speakers from Verizon, Snowflake, Affinity Federal Credit Union, EverQuote, and AtScale
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Doug offered practical solutions through three powerful frameworks that can transform how teams approach innovation and problem-solving. Proactive Problem Solving Doug was motivated to write Proactive Problem Solving by two pieces of data showing the impact of reactive problem solving: The average manager wastes 3.5
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Quantitative data alone doesn’t reveal intent, only outcomes. By combining contextual insights from session replays , heatmaps, and behavior analytics, user session analysis helps you interpret metrics through the lens of real user journeys. Tools can track every click and interaction.
However, without qualitative feedback and behavioral insights, teams risk misreading signals, leading to frustration and churn. User feedback is valuable , but without data, its just opinions. To eliminate these blind spots, you need to combine quantitative, qualitative, and visualdata. How to collect each data type.
Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind.
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.
With Userpilots mobile solution , you can personalize in-app flows, trigger context-aware push notifications, and capture real-time insights: all without writing a single line of code. To show you how, Ill cover seven strategies that smooth out friction, enhance user engagement, and turn one-off app downloads into returning customers.
We covered how to manage messy opportunity solution trees , the most common challenges teams face when getting started with the discovery habits, what Im working on next, and so much more. This definition is a mouthful, so I like to visualize it. A core part of this is this visual. I can break this visual down into 11 habits.
I’m going to take a wild guess and assume that you already understand the importance of mobile in-app feedback tools. You also might be reading this post thinking: “Who’s adding new tools to their tech stack right now?” Do you have the right tools to capture that voice? Mobile in-app feedback tools & solutions.
Speaker: Dave Mariani, Co-founder & Chief Technology Officer, AtScale; Bob Kelly, Director of Education and Enablement, AtScale
Check out this new instructor-led training workshop series to help advance your organization's data & analytics maturity. It includes on-demand video modules and a free assessment tool for prescriptive guidance on how to further improve your capabilities. Workshop video modules include: Breaking down data silos.
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How AI captures customer needs that human product managers miss Watch on YouTube TLDR In my recent conversation with Carmel Dibner from Applied Marketing Science, we explored how artificial intelligence is transforming Voice of the Customer (VOC) research for product teams. However, these early efforts faced significant limitations.
In fact, the 2024 Buyer Experience Report by 6sense found that a whopping 85% of buyers establish purchase requirements before even contacting sales. Step 2: Collect internal assets Once you’ve decided on your use case, it’s time to dig into your internal assets to gather crucial customer data. moments along your customer journey.
Below is a preview of key insights. How to Drive Stronger Product Adoption Optimize the first 3 minutes of onboarding Reduce friction, provide quick wins, and keep users engaged. Make switching easier Allow parallel use with existing tools and automate data migration from competitors.
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How product managers can use AI to work more efficiently Watch on YouTube [link] TLDR AI is changing how we manage products and come up with new ideas, giving us new tools to work faster and be more creative. Brian recommends the tool Perplexity.ai, which removes hallucinations and brings in real-time information.
In 2006, British mathematician Clive Humby made the infamous statement: Data is the new oil. Like oil, raw data needs to be refined, processed and turned into something useful because its value lies in its potential. Unfortunately, most people have yet to understand what it truly means to use data. How to solve this issue?
What happens when you build a product or service around what you think potential customers want, only for them to buy something else? It could include conducting user interviews and surveys, analyzing product usage data, and tracking customer feedback , to name a few. For starters, it shows you dont know your customers well enough.
Example: Imagine you’re designing a new dashboard for a fintech app. This is where you’ll use the classic “How might we…” question to frame the problem. Example: For our dashboard, we might ask, “How might we create a dashboard that helps analysts quickly spot trends and take action?”
Embedding dashboards, reports and analytics in your application presents unique opportunities and poses unique challenges. We interviewed 16 experts across business intelligence, UI/UX, security and more to find out what it takes to build an application with analytics at its core.
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