VENMATE’s Post

In the dynamic world of start-ups, the pursuit of customer value often feels like navigating uncharted waters. A recent whitepaper by Strategyn sheds light on a harsh reality: 55% of start-ups fall short of achieving Product-Market Fit, and a staggering 50-75% of new products miss their business goals.   Enter Outcome Driven Innovation (ODI) – a game-changer in the startup landscape. This systematic approach, championed by Tony Ulwick and pre-dating Jobs To Be Done, has demonstrated an impressive 86% success rate in over 1000 projects since the early '90s. Key Takeaways for Early Stage SaaS Startups:  A. Systematic Precision: ODI introduces a structured methodology, offering clarity in the chaotic landscape of early-stage startup life. B. Marrying Qualitative with Quantitative: ODI seamlessly integrates qualitative insights with quantitative data. Post-interviews, surveys are employed to achieve statistically significant responses, ensuring a robust foundation for decision-making.   This isn't just theory—Strategyn boasts an impressive 86% success rate with ODI across 1000+ projects since the early '90s. For early-stage SaaS start-up's, ODI emerges as a beacon of strategic clarity. While experimentation is essential, ODI advocates for a targeted approach, aligning with your market before throwing darts at the dartboard.   #OutcomeDrivenInnovation #StartupSuccess #InnovationTrends #BusinessStrategy #Strategyn #AMSquare

Congratulations to Brijesh Bharadwaj and Shobhit Gupta on the launch of their innovative SAAS-based startup, Segwise.ai! #saasstartup #dataanalytics #productgrowth  #techinnovation  #startupsuccess  #entrepreneurship  #techsparks2023 #machinelearning  #artificialintelligence #techinnovation #productmetrics 

Week 2 of my solo startup project is complete! 🚀 I've made significant progress on my market research and product analysis platform by establishing a basic landing page and delving deep into research. The platform holds immense potential to equip fellow entrepreneurs with data-driven insights. 📊 Here's a snapshot of my accomplishments this week: - Crafted a compelling landing page that articulates the platform's value proposition. - Explored various backend technologies (Django, PostgreSQL) and data sources (Alpha Vantage API, Upstox API) to identify the ideal solutions. - Mapped out a comprehensive workflow to streamline the development process and ensure productivity. Stay tuned for more updates as I transition into the next phases of design and development. buildspace Nights & Weekends Farza Majeed #startups #marketresearch #productanalysis #entrepreneurship #datadriven #buildinpublic

Two of my favorite Founders & CEOs cover a range of business, product and leadership issues 🚀

📚 welcome back to the async book club 📚 To pivot or not to pivot? That is the question 🤔 The Lean Startup stresses that the only way a startup can truly know when to pivot is by having its metrics and experiments set up correctly. Remember we talked about the 3 As of metrics (actionable, auditable, accessible), and the importance of using cohort-based data rather than vanity metrics to evaluate performance? Not discounting that pivoting can be a difficult and often emotional decision, The Lean Startup recommends implementing it into your process by having a regular ‘pivot or persevere’ meeting with the metrics leading the discussion. If you are considering a pivot, rest assured that it’s a normal part of the startup lifecycle, and the book says that businesses should continue to pivot even after initial success - so always be evaluating the metrics and questioning the strategy! See ya next time 😎

Embracing failure is actually the key to success. Success isn't about avoiding mistakes. It's about what you DO with them. This mindset shift was a complete game changer for me as it allows you to to take more calculated risks and to view 'failures' as essential feedback for growth. Setbacks in hindsight end up just being stepping stones.

🚀 Embracing the Build-Measure-Learn Feedback Loop for Start-Up Success In the fast-paced world of startups, the Lean Startup methodology, developed by Eric Ries, offers a transformative approach: the Build-Measure-Learn feedback loop. This powerful strategy encourages rapid prototyping, targeted observing, and swift learning. Here’s how it works: Build a minimum viable product (MVP) to test your hypotheses. Keep it simple, focusing on core functionalities that reflect your business assumptions. Measure the product’s performance using real-world data. Identify key metrics that reflect customer behavior and product engagement. Learn from the data. Decide whether to pivot and alter your hypotheses or persevere with your current strategy. This iterative process minimizes development cycles, enhances flexibility, and ensures that you’re building products people actually want. Whether you’re launching a new feature or starting from scratch, integrating the Build-Measure-Learn loop can significantly de-risk your venture and speed up your path to a product that truly resonates with users. #LeanStartup #Innovation #Entrepreneurship #ProductDevelopment #StartupLife #DataAlchemy Feel free to share your experiences or thoughts on applying this method in your projects! 🔄

HOT TAKE: A/B testing at startups is overrated. Meaningful product A/B tests usually require > 20k visitors or email openers to be conclusive, and they usually impact metrics by less than 1-5% even when they are conclusive. You probably have much more "macro" things you could be focusing on. Often, a focus group of 3 beta testers can tell you more than the fancy A/B test would have told you, with better actionable follow-ups. Concentrate on the BIG stuff for now, and iterate based on actual human interactions. You'll have plenty of time to "optimize" with data when you get huge . . . . #startups #analytics #productmanagement #entrepreneurship

How data-driven are startups, really? Surprisingly, many startups are not data-driven AT ALL. The thing is, early on, there is rarely enough data to make decisions based on that data. In fact, if you make decisions on that data (n of 1), you could go in the wrong direction. This is what leads startups to keep building features for one customer, then the next customer, then the next customer, before realizing they don't have a cohesive product. So you do have to make educated guesses based on gut when the data isn't there. However, this muscle of making quick decisions can also lead you astray once the data DOES come in. And you're so used to making gut decisions that you reason away what the data says. On the flip side, the ABSENCE of data is also telling. If you're one, two years in and you still don't have enough data, that is also a data point. But again, it's easy to ignore this and continue proceeding to make educated guesses. All this is to say that all founders need to suspend disbelief, but if you suspend disbelief for too long, you risk not being data driven when you actually CAN be data driven. #productmanagement #startups #startupbuilding

Do you really know what MVP is? Most people misunderstand MVP. MVP is not only the acronym of Minimum Viable Product, but also 'Maximum Validated (learnable) Product'. You have to focus on “Maximum”, not minimum. Yes. Maximum. Eric Ries (who wrote Lean Startup) defines MVP as “A version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort.” The most important part is not “the least effort”, but “the maximum amount of validated learning”. Most of builders focus on the former, but you have to focus on the latter. Think and focus on “How to learn more”, not “How to work less”. [Lean Startup Series #1]