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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.
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.
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.
Speaker: speakers from Verizon, Snowflake, Affinity Federal Credit Union, EverQuote, and AtScale
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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.
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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.
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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.
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. .”
Speaker: Evan Leong - CEO & Founder, Product Signals
How do industry leaders like Apple and Amazon successfully leverage customer and market insights to enhance their products, even with vast customer bases and extensive market data? Despite its significance, many organizations struggle to collect and utilize feedback appropriately.
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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.
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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.
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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.
Speaker: Speakers from SafeGraph, Facteus, AWS Data Exchange, SimilarWeb, and AtScale
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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?
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.
Download this whitepaper to learn what contextual analytics is, how BI platforms like Yellowfin revolutionize the way users discover insights from their data with native contextual analytics, and how it adds value to your software solution by elevating the user experience.
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.
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.
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An interactive guide filled with the tools to turn your data into a competitive advantage. They rely on data to power products, business insights, and marketing strategy. This playbook contains: Exclusive statistics, research, and insights into how the pandemic has affected businesses over the last 18 months.
During the third stage, input is analyzed and during the fourth stage, the insight gained from analysis is used to make decisions. Plugging in: how to generate insightsAnalysis: how to prioritize and understand feedback Communication: how to synthesize information Test/Build/etc & then repeat. Get Insights.
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Speaker: Eric Feinstein, Professional Services Manager, Looker
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