AI Virtual Assistants That Help with Market Research

𝗜𝗻 𝗮 𝘆𝗲𝗮𝗿 𝘄𝗵𝗲𝗿𝗲 𝗔𝗜 𝗶𝘀 𝘀𝗵𝗶𝗳𝘁𝗶𝗻𝗴 𝗳𝗿𝗼𝗺 𝗮𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁𝘀 𝘁𝗼 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗮𝗴𝗲𝗻𝘁𝘀, 𝘁𝗵𝗲 𝗹𝗮𝘂𝗻𝗰𝗵 𝗼𝗳 𝗟𝗶𝘀𝘁𝗲𝗻 𝗟𝗮𝗯𝘀 𝗰𝗼𝘂𝗹𝗱𝗻’𝘁 𝗯𝗲 𝗺𝗼𝗿𝗲 𝘁𝗶𝗺𝗲𝗹𝘆. Backed by a $𝟮𝟳𝗠 𝗿𝗼𝘂𝗻𝗱 𝗹𝗲𝗱 𝗯𝘆 𝗦𝗲𝗾𝘂𝗼𝗶𝗮, Listen Labs is changing how teams do user research. Instead of long surveys and delayed reports, it: → Writes smart research questions → Finds real participants automatically → Runs interviews → Delivers insights, themes, and even slide decks It’s not just faster—it makes deep customer understanding available to 𝘢𝘯𝘺𝘰𝘯𝘦, not just big research teams. This fits a bigger trend we’re seeing in 2025: AI tools are moving from helping humans to handling full workflows. Some things I’m thinking about: • Can AI really understand human feedback with nuance? • What happens when user research becomes as fast as running code? • What role do humans play when agents take over strategy tasks?    Excited to see where this goes. It’s a clear signal of what’s next in applied AI.

𝗔𝗴𝗲𝗻𝘁𝘀 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻 𝗱𝗼 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵? 𝗬𝗲𝘀, 𝗳𝗶𝗻𝗮𝗹𝗹𝘆. This changes the game. With the public preview of Deep Research in Azure AI Foundry, we can now automate enterprise-grade web research—with full auditability, transparency, and control. I’ve often found that traditional chat-based tools hit a ceiling when the task involves multi-step reasoning, live data, and enterprise governance. Deep Research unlocks that next level: ✅ Composable agents that clarify, search, and synthesize 🔍 Grounded with real-time Bing search, no hallucinations 🔧 Available via API + SDK, ready to plug into real apps 🛡️ Enterprise-grade: secure, traceable, and extensible Imagine this: a research agent pulls web insights, another turns it into a slide deck, a third emails it to execs. All automated. All explainable. We’re stepping into a future where research becomes a service, not a manual task. This is huge for use cases like: 1. Competitive intelligence 2. Policy/regulatory tracking 3. Market trend analysis 4. Risk and compliance workflows Excited to see what builders and enterprises do with it. 🔗 https://lnkd.in/eduC4euA P.S I learn by sharing. If you're exploring the future of agentic AI, follow me here. I’ll keep sharing what I learn—one experiment, one insight at a time. #agenticai #azureai #generativeai #microsoft #aiagents #llms #deeplearning #researchautomation

Happy Friday everyone, this week in #learnwithmz, if you are a Product manager learning about AI this post is for you. PMs looking to get hands-on with AI side projects don’t have to be expert in AI, just a curiosity and willingness to experiment. Here’s a step-by-step guide to help you get hands-on with AI side projects. 💡 Start small: Automate Regular Tasks Identify tasks you do frequently that AI can streamline, examples: - Feedback theme collection - Feature request prioritization - Market research automation 📌 Example project: AI-Powered Market Research Assistant What is it? A tool that uses AI to gather and analyze market data, customer reviews, competitor strategies, and trending topics, delivering actionable insights for product or feature development. Why build it? - Get near real-time insights into customer needs and competitor strategies. - Accelerate decision-making for market opportunities. - Ensure your product strategy stays aligned with industry trends. Step 1 - Define Scope Inputs: - Customer reviews and feedback. - News articles or blog posts about competitors. - Social media trends and hashtags. Outputs: - Key themes in customer sentiment. - Competitor summaries. - A list of emerging trends or gaps in the market. Step 2 - Choose Tech Stack Web Scraping: BeautifulSoup or Scrapy to gather data from review sites and blogs. Sentiment Analysis: OpenAI, Hugging Face, or #Azure AI Language. Trend Analysis: Google Trends API or Twitter API. Visualization: Power BI or Streamlit. Step 3 - Build and Iterate Start simple, test test test, and refine based on feedback. I’m working on a prototype for this assistant, stay tuned for updates after the holidays. What kind of market data do you find most valuable? Let’s discuss in the comments! #ProductManagement #AI #Innovation #marketresearch P.S. Image is generated via DALL·E