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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?
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.
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: Eric Feinstein, Professional Services Manager, Looker
For a long time, Product Managers have found it challenging to design interfaces inside their products that users could use for reporting. It seems like PMs and engineers have grown to hate embedded reporting. How to evaluate embedded analytic solutions as strategy to greatly reduce initial and on-going engineering effort.
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.
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.
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 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?
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.
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.
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.
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?
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.
Banks have always relied on predictions to make their decisions. Estimating the risks or rewards of making a particular loan, for example, has traditionally fallen under the purview of bankers with deep knowledge of the industry and extensive expertise. How today’s banks can handle the data science talent shortage.
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.
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.
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.
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.
By building a modern GTM motion that uses data, automation, and proven best practices to unlock insights, engage customers, and win faster. How can you speed it up?
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.
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. Example: Sarah is a support manager at a fast-growing startup.
Throughout our conversation, we explore insights from their creative process that can be applied to product innovation and management. For example, a recent video called “When they cancel plans but you’re both introverts,” was inspired by Leah and Phillip’s introvertedness.
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.
Predictiveanalytics is an increasingly common buzzword with many forms. What does predictiveanalytics really mean? We’ll explore real-world examples of predictive in action and outline steps to help you maximize its value. September 5, 11:00 AM PST, 2:00 PM EST, 6:00 PM GMT
1] Below are four examples of how this can be achieved. 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]
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. For example, Grammarly offers only a limited number of premium suggestions in its free plan.
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.
Highlight Relevant Experience: Share examples of similar challenges youve tackled in the past to build confidence. 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.
Dashboard design can mean the difference between users excitedly embracing your product or ignoring it altogether. Great dashboards lead to richer user experiences and significant return on investment (ROI), while poorly designed dashboards distract users, suppress adoption, and can even tarnish your project or brand.
Are you struggling to make sense of scattered user data? The right customer analytics platform helps you uncover exactly how customers interact with your product: so you can spot issues early, optimize user journeys, and drive sustainable growth. Choose the best fit for your needs and transform data into actionable strategies.
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.
To help you get started, we’ve compiled 11 powerful gamification examples to improve your user onboarding process. We’ll walk through some onboarding gamification examples you can replicate and, where relevant, some examples to improve your employee onboarding process. Below’s an example from Airtable.
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: Speakers from SafeGraph, Facteus, AWS Data Exchange, SimilarWeb, and AtScale
Data and analytics leaders across industries can benefit from leveraging multiple types of diverse external data for making smarter business decisions. Data and analytics specialists from AWS Data Exchange and AtScale will walk through exactly how to blend and operationalize these diverse data external and internal sources.
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.
This guide will walk you through crafting effective release notes, provide a free template to streamline your workflow, and showcase 7 inspiring examples to fuel your product management efforts. They include fixes, enhancements, and new features , related to the product's hardware, software, and services. What are release notes?
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.
Speaker: Andrew Wynn, Senior Product Manager, Looker
As a product manager, you know how helpful custom tailored data solutions can be to doing your job well. But proper dataanalytics solutions take work to deliver - it's not as simple as just building a dashboard. Learn product analytics best practices from Andrew Wynn, Product Manager at Looker.
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. Better decisions.)
The choice is tough because there’s no single tool that covers all use cases. What’s worse, you will find multiple tools in each category, making it incredibly difficult to pick the tool that satisfies your needs and offers the best value for money. Which product feedback software should you choose for your SaaS?
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. moment that makes users stick.
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.
Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. When you use entity resolution to resolve graph nodes, your downstream analytics become much more effective.
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