Startup Bubble’s Post

How to use generative AI to improve product sense for 0 to 1 Data and AI products? (1) Use generative AI to conduct product teardowns of other people's products. (2) Identify customer segments, pains, competitors, workflow, frictions, desirability, positioning, and return on investment. (3) Improve product sense and make better decisions about product development. Here are some prompts one can use to generate insights about Data and AI products using Generative AI: - Customer segments: Who are the main customer segments for this product? What are their needs and pain points? - Pains: What are the main pain points that this product solves for its users? - Competitors: What are the main competitors to this product? How does this product compare to its competitors? - Workflow: How does this product fit into the user's workflow? How does it make the user's work easier or more efficient? - Frictions: What are the main friction points in the user experience of this product? How can these friction points be improved? - Desirability: How desirable is this product to its users? What features would make it more desirable? - Positioning: How is this product positioned in the market? How does it differentiate itself from its competitors? - Return on investment: What is the potential return on investment for this product? What are the key metrics for success? Use these prompts to generate other insights, such as: - The target audience for the product - The product's value proposition - The product's competitive landscape - The product's marketing and sales strategy - The product's go-to-market strategy - The product's technical architecture - The product's roadmap The specific prompts will depend on the specific products. However, these prompts should give a good starting point for generating insights about any Data and AI product. Please share your thoughts and suggestions in the comments! #productsense #dataandai #generativeai

In recent months, I've had several founders reach out to me asking how they can leverage #AI to automate their internal business #processes. It's not always an easy task. I created a #cheatsheet to help start the conversation and approach these questions in a structured way. So how to identify meaningful business areas for #AI-solutions? 1. Start by identifying a business problem. Ask yourself or a colleague, "What are the top three things you wish were working better?" 2. Collaborate with someone knowledgeable about #AI to brainstorm potential solutions. Sometimes there may not be a suitable AI solution, and that's perfectly fine. 3. Assess the feasibility and value of potential solutions through research and consultations with experts. 4. The next step is to define the metrics to aim for once you determine that a project holds sufficient value. These metrics should include both business and machine-learning-specific metrics. Once again, consult an AI-knowledgeable friend if in doubt. And if you struggle to establish reasonable milestones, it could be a signal that you need to develop a deeper understanding of the problem. 5. Budget for necessary resources. Consider all the elements required to complete the project, including data, personnel, time, and any integrations or support you might need from other teams. And remember working on automation projects is an iterative process 🙃 #AI #processautomation #digitaltransformation

COOs, let's chat! 💬 At Dashworks, we constantly hear from operations rockstars like yourself who have been tasked with exploring how AI can pump up company productivity. (No pressure, right?? 😅 ) So based on our discussions with prospects, customers, and other AI aficionados, we crafted the quintessential guide for COOs diving into the wonderful world of artificial intelligence. We picked the brains of operations masters like Kevin Miller, Carlos Traibel, and Abhishek Shah to outline high-impact AI categories, tips for evaluating tools, and our top recommendations to make your life easier. The bottom line? AI is ready to transform your operations GAME. Our guide gives you insider knowledge to select solutions that make your company run like a well-oiled machine. 🤖 ✨ (And obviously we think getting an AI knowledge assistant should now be your #1 priority.) 😂 Check out the piece here: https://lnkd.in/eFAfU8fc

Right now, everyone is trying to do more with less. And the rise of AI tools look like a great productivity hack - get more done, faster with less effort. Just pick one and roll it out to the team, right? (this is where the record scratch comes in) *Hold up*. Just because you see a new shiny AI tool that offers big promises doesn't mean that a) it's the right tool for you and your team, and b) it will automagically solve a big problem in your business. Because your order of operations is backward. Here's the CORRECT order of operations to use before adding a new AI tool to your stack: ✅ Identify the problem in your business - the REAL problem, not just the problem you think you have. This will take a little effort and possibly a more objective perspective than you currently have internally. If you're not solving the right problem, your entire effort will fall apart. ✅ What's the value to the business when you solve this problem? Are you saving time, saving money, or acquiring new customers with a higher ACV? Break it down and show your work. ✅ How easy is this problem or solution to solve (cost, time, expertise required)? Look for lower-lift opportunities with a higher ROI. This is especially important as you look for buy-in and support at the top of the organization. Once you identify the right problem to solve, then you can look for a tool to help you get there. AI tools hold the promise of massive productivity gains, and it's super tempting to take those claims at face value and try to shove them into your business, but be smart about the tools you pick (because they're changing and evolving ALL THE TIME) and solve for the use case and business challenge instead of the newest, shiniest tool on the market. There is no magic wand, there are no magic beans; so take a deep breath and move forward with a reasonable approach to AI tool adoption. #ai #b2bStrategy #B2BMarketingStrategy #artificialintelligence

Drowning in Data? Here's a Lifeline! 🌊➡️🆘 In today's world, businesses are flooded with data—clicks, views, downloads... you name it. The challenge isn't collecting it; it's making sense of it all. But imagine transforming this overwhelming data deluge into actionable insights! Enter AI and workflow automation: the dynamic duo turning chaotic data streams into strategic decisions. By leveraging these technologies, companies can not only predict customer behavior but also personalize their marketing efforts in real time. The result? A significant boost in engagement, conversion rates, and ultimately, revenue. Are you ready to dive deep and turn your data into your most valuable asset? Krivi Let's talk about how AI can revolutionize your approach to data analysis and decision-making. #DataDrivenMarketing #AI #WorkflowAutomation 🚀

Baffled by the myriad of AI tools flooding the market? You're not alone. This cutting-edge article by SmallBizTrends might just be your saving grace. It meticulously curates the top 15 AI tools that are revolutionising businesses in today's digital era. From enhancing customer engagement to optimising operations, these tools are reshaping the business landscape. \n\nI wholeheartedly agree with the insights presented and the potential these tools hold. The application of AI is no longer a gimmick. It's a necessity. As we pivot towards a more digitally-focused world, the integration of these tools can catapult a company's growth trajectory and provide a competitive edge that's second to none. \n\nIt's time for businesses to embrace AI tools and harness their potential. It's time to step into the future. \n\nDo give it a read. You're in for a treat. \n\nhttps://lnkd.in/gZMJK3u8 Check this out: https://lnkd.in/gZMJK3u8

5 steps to Building a Compelling AI Business Case 👇🏻

Ever spent millions on data and AI, only to see projects fail and money disappear? You may have tried new technologies, but what if the problem is not technical? Meet Delight - @Mindfuel’s groundbreaking data product management software designed to showcase the business impact of data products. 🌐 Real-time visibility of your entire data portfolio. 🔗 Seamless connection from assets to opportunities. 💰 Measure ROI effortlessly. 🚀 Ensure success with full value assessments. 💡 Boost transparency, alignment, and ROI. 𝐒𝐞𝐞 𝐟𝐨𝐫 𝐲𝐨𝐮𝐫𝐬𝐞𝐥𝐟—𝐭𝐫𝐲 𝐃𝐞𝐥𝐢𝐠𝐡𝐭 𝐟𝐨𝐫 𝐟𝐫𝐞𝐞: https://lnkd.in/gsPu488g #datastrategy #intoDelight #AI #ROI #dataproducts #businessimpact

Shocking Statistics About Not Adopting AI: → Revenue Loss: Businesses not adopting AI could miss out on a potential revenue increase of up to 10% annually (Techjury). → Higher Costs: Companies that don't use AI spend about 20% more on operational costs due to inefficiencies and manual processes (The Social Shepherd) (Techjury) → Customer Dissatisfaction: Over 75% of customers expect businesses to incorporate new technologies like AI. Failing to do so can result in a significant drop in customer satisfaction and loyalty (SBA.gov) (Techjury). → Competitive Disadvantage: By 2025, it's estimated that 80% of retail companies will use AI, leaving non-adopters at a severe competitive disadvantage (Techjury). → Productivity Decline: Businesses not leveraging AI for automation can experience a productivity loss of up to 40%, significantly impacting growth and scalability (SBA.gov) (Techjury). → Market Lag: As AI is predicted to contribute $15.7 trillion to the global economy by 2030, businesses that fail to adopt AI will be left behind in market innovations and economic growth (Techjury). So if you're not using AI, WHY? Genuinely interested to know... Is it: A. Lack of knowledge B. Cost concerns C. Complexity & implementation D. Uncertain ROI PS. totally unrelated photo, but I cannot wait until next Friday when me & my better half go to Mallorca for a few nights without the kiddos!

TSMixer: The Latest Forecasting Model by Google https://lnkd.in/gaXcECz7 AI News, AI, AI tools, Innovation, itinai.com, LLM, Marco Peixeiro, t.me/itinai, Towards Data Science - Medium 🚀 Evolve Your Company with AI: Introducing TSMixer 🚀 Are you ready to take your company to new heights with AI? Stay ahead of the competition by implementing TSMixer, the cutting-edge forecasting model developed by Google. With TSMixer, you can revolutionize your work processes and achieve more accurate long-term multivariate forecasts. Practical Solutions for Seamless AI Integration 1️⃣ Identify Automation Opportunities: Discover areas in your customer interactions that can benefit from AI automation. This will help streamline your processes and improve overall efficiency. 2️⃣ Define Measurable KPIs: Set clear Key Performance Indicators (KPIs) to ensure that your AI initiatives directly impact your business outcomes. This allows you to track progress and measure success effectively. 3️⃣ Choose Customizable AI Tools: Select AI solutions that align with your specific needs and offer customization options. This ensures that the technology adapts to your unique business requirements. 4️⃣ Implement Gradually: Start with a pilot project to test the effectiveness of AI, gather valuable data, and gradually expand its usage. This gradual approach allows for careful integration and optimization. For expert advice on managing AI KPIs, reach out to us at [email protected]. Stay updated with the latest insights on leveraging AI by following us on Telegram or Twitter @itinaicom. ⭐ Spotlight on Practical AI Solutions ⭐ One highly effective solution for automating customer engagement and managing interactions throughout the customer journey is the AI Sales Bot from itinai.com/aisalesbot. This AI-powered bot is available 24/7 and can redefine your sales processes and improve customer engagement. Discover how AI can transform your company and explore our wide range of AI solutions at itinai.com. 🔗 List of Useful Links 🔗 AI Lab in Telegram @aiscrumbot – Get free consultation TSMixer: The Latest Forecasting Model by Google Towards Data Science – Medium Twitter –  @itinaicom