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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?
Think of Net Promoter Score (NPS) software as a tool to measure your customers’ feelings about your product, and categorize them based on their level of loyalty (promoters, neutrals, and detractors). The great advantage of these tools is that they streamline the creation, distribution, and analysis of NPS surveys.
Featuring an engaging discussion with Inis Hormann (Marketing Director Germany, Cepheid) and Steve Kury (Leadership Development Consultant, SHK Leadership Consulting), the session provided actionable insights for PMs at every level. Leverage Data: Use findings to guide decisions, reduce uncertainty, and inform future product iterations.
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.
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?
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.
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.
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.
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- (..)
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.
When you’re building a mobile product , data is your lifeline. Whether for tracking feature adoption or spotting drop-off points, the right analyticstool can make or break your growth. Some tools are great for marketers, and others are for product or development teams.
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.
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?
Organizations look to embedded analytics to provide greater self-service for users, introduce AI capabilities, offer better insight into data, and provide customizable dashboards that present data in a visually pleasing, easy-to-access format.
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. Some common AI failurestories: The Data Hoarders : Companies that think collecting more data will somehow lead to an AI breakthrough. Ready to see where data is headednext?
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.
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.
How product managers can use AI to get more actionable insights from qualitative data Today we are talking about using qualitative data to drive our work in product and consequently improve sales. ” Then the product leader goes to some poor associate PdM and asks them to collate all of the data together. .”
Think your customers will pay more for datavisualizations in your application? But today, dashboards and visualizations have become commonplace. Turning embedded analytics into a source of revenue means integrating advanced features in unique, hard-to-steal ways. Proven approaches to achieving analytics maturity.
You see, although we work hard to make Userpilot the best product adoption tool on the market, we know it isnt the perfect fit for every business. Robust resource center functionalities for offering self-service help. Custom dashboards to track key metrics at a glance. for collecting user sentiment data.
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.
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!
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.
In this episode of Productside Stories, Neha Bansal , Head of Product at Meta Ads Manager Reporting, joins Nicole Tieche to discuss her career, the high-speed role of AI in advertising, and how PMs can stay ahead of industry shifts. Stepping into product leadership means balancing strategic vision, customer focus, and emerging tech.
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. Execs dont care about architecture diagrams. They care about impact.
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. Engage Actively in the PM Community A personal brand isn’t built in isolation.
Case Study: Improving Data-Driven Decision Making for CSR Leadership Civian is a data-driven platform designed to help businesses measure, optimize, and showcase the social and economic impact of their investments in communities. Feature Engagement Users most frequently gravitated toward the map to explore and compare data.
In the fast-moving manufacturing sector, delivering mission-critical datainsights to empower your end users or customers can be a challenge. Traditional BI tools can be cumbersome and difficult to integrate - but it doesn't have to be this way.
Reveal Embedded Analytics We know how difficult it is to create dashboards, especially for web applications. However, running business operations or targeted campaigns without insights into their effectiveness is not an option. Thats what dashboards are for. It offers several options when it comes to dashboard libraries.
Throughout our conversation, we explore insights from their creative process that can be applied to product innovation and management. Analytics let Leah and Phillip see what aspects of their content viewers are engaging with most. How do you currently balance intuitive decision-making with data-driven approaches?
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.
A customer expansion strategy is a playbook for increasing the revenue from your existing customers, for example, by selling them additional products and services or encouraging them to upgrade to higher plans. As your team grows and you hire new people or other departments adopt the tool, the number of seats needed increases.
The world of dataanalytics is changing fast as organizations look to gain competitive advantages through the application of timely data. Choosing the best solution for your dashboards and reports starts with understanding the types of analytics solutions on the market. The pros and cons for each option.
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 These principles aren’t just theoretical – they’re practical tools that any product team can implement to enhance their innovation process.
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.
Tips and Insights to Create Intuitive, User-Centered DataTables Data tables provide a structured way to organize and manage information, making it easier to analyze and visualizedata effectively. However, creating effective data tables is not as simple as organizing rows and columns.
If youre looking for AI tools that will help you make your work more efficient, you come to the right place. This collection of AI tools will be very helpful for all product designers. Its also good at analyzing complex documents (like multi-page PDF reports) and extracting specific data fromthem.
Think your customers will pay more for datavisualizations in your application? But today, dashboards and visualizations have become table stakes. Turning analytics into a source of revenue means integrating advanced features in unique, hard-to-steal ways. Five years ago, they may have.
Pro Tip: Pair your quick wins with data. A dashboard showing metrics like feature adoption or user engagement amplifies your credibility. Advanced Tactics: Stakeholder Mapping: Use tools like the Stakeholder Alignment Blueprint (available on jonihoadley.com) to identify key goals and concerns. Click here to download.
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.
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.
Below is a preview of key insights. Make switching easier Allow parallel use with existing tools and automate data migration from competitors. Create a self-initiated MVP even a simple landing page or automation tool. Q: How do I shift leaderships focus from data obsession to actual product development?
In the rapidly evolving healthcare industry, delivering datainsights to end users or customers can be a significant challenge for product managers, product owners, and application team developers. But with Logi Symphony, these challenges become opportunities. But with Logi Symphony, these challenges become opportunities.
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