Tevfik Aloglu

In today's oversaturated markets, product-led growth (#PLG) has emerged as a game-changing strategy for companies looking to stand out and scale efficiently. But what makes PLG different, and why is it so crucial? User-Centric Approach: PLG puts the product experience at the forefront, allowing users to derive value before they pay. This approach builds trust and loyalty in crowded markets where traditional marketing noise is overwhelming. Reduced Customer Acquisition Costs: By leveraging the product itself as a primary growth driver, companies can significantly lower their CAC, a critical factor in saturated markets with fierce competition. Viral Growth Potential: PLG strategies often incorporate viral loops and network effects, enabling exponential growth - a powerful advantage in crowded spaces. Data-Driven Optimization: PLG relies heavily on user behavior data, allowing companies to continually refine their product and growth strategies based on actual usage patterns. Scalability: As Elena Verna notes, PLG allows companies to scale more efficiently by automating parts of the customer journey that traditionally required human intervention. Flexibility in Go-to-Market: Leah Tharin emphasizes that PLG isn't a one-size-fits-all solution. It can be combined with other strategies like sales-led or marketing-led approaches for a hybrid model tailored to specific market segments. Focus on User Success: PLG aligns company success with user success, creating a virtuous cycle of value creation and capture. In oversaturated markets, PLG offers a way to differentiate through superior user experience and efficient growth mechanics. It's not just about acquiring users; it's about creating passionate advocates who drive organic growth. Are you leveraging PLG in your growth strategy? How has it impacted your ability to compete in crowded markets? If you're aware of any relevant Senior Product Manager or Product Lead opportunities aligned with my expertise, I'd greatly appreciate you connecting or referring them to me as I continue my pursuit of the next role where I can drive significant impact. #OpenToWork #OpenToNetwork #ProductManagement #ProductManager #ProductLedGrowth #PLG #ProductStrategy

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Finally some real innovation in LLMs that is not about spitting out the next token better. OpenAI o1 series models actually "think" before they respond, very much like a human's internal reasoning before answering a hard question. We already started benchmarking the o1 model today and we are excited to bring this superhuman intelligence into solving complex problems in manufacturing with Aibuild. Congratulations to OpenAI, and all pioneers who dare to build something new. https://ai-build.com/ai/ https://lnkd.in/eKT_XGV6

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Day 3 of building Fibr AI in public How do we decide what to build? 🛠 We don't build anything unless we feel it's necessary and users are asking for it. 🛠𝗜𝗻𝘀𝗶𝗴𝗵𝘁-𝗱𝗿𝗶𝘃𝗲𝗻 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵: Our approach is insight-driven. We learned that companies spend between $30,000 and $100,000 on platforms like VWO and Optimizely for experimentation but often run only 2-3 campaigns a month. This leads to a significant amount of money going to waste. So, what is the missing link? The marketing department wants to be smart and experiment, but initiation and hypothesis building are the blockers. We addressed this by introducing ad-to-landing page personalization. 🛠𝗦𝗲𝗹𝗹 𝗯𝗲𝗳𝗼𝗿𝗲 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴: This is an area where we’re still improving, but we're working hard to get there. Every team member is expected to actively sell. Create an interaction file for the feature you think is really important and show it to 10 prospective clients before your bias takes over.Also, we view AI as a technology enabler rather than the core of our thinking when crafting new features. We made the mistake earlier this year of overemphasizing AI, only to realize after 4-5 months that marketers don’t care about half-baked AI output; they only care about solid, impactful results. 🛠𝗔𝘀 𝗮 𝗰𝗼𝗺𝗽𝗮𝗻𝘆, 𝘄𝗲'𝗿𝗲 𝗴𝗼𝗶𝗻𝗴 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗮 𝗺𝗶𝗻𝗱𝘀𝗲𝘁 𝘀𝗵𝗶𝗳𝘁 where everyone is a marketer and salesperson first, and a builder second. We celebrate when our team pushes back on building new things without proper validation, and this has been incredibly positive so far.Tomorrow, I will share more on what we have built so far and what’s coming next. On a daily basis, I will share small snippets of how some features work and discuss the mistakes and learnings from building them. 𝗦𝘁𝗮𝘁𝘂𝘀 𝘂𝗽𝗱𝗮𝘁𝗲 𝗼𝗻 𝗮𝗰𝘁𝗶𝘃𝗲 𝗰𝗹𝗶𝗲𝗻𝘁𝘀: 3/20 (target). One client is finally going live this week! 🎉 P.S: We have built a fantastic feature that can curate your brand guidelines with just one click. From there, it further refines the content output to match your brand’s tone precisely. You can check out the Brand Guidelines feature in action in the video here! #buildinpublic #buildinginpublic #experimentation #startupjourney #personalization #ai #marketing #mindsetshift #buildwithpurpose

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In the age of AI, is every product a data product? And if it is, how should your product strategy change? 🤔 Earl Lee (ex-PM at FiscalNote, Co-founder & CEO HeadsUp, and now at Hightouch) and I talked a bunch about "data products" in the latest Product Lunchbox episode. Earl has a ton of experience working at different types of data companies: ⛽️ Data "fillers" (companies that provide 2nd/3rd party data) 🔮 Data "manipulators" (companies that unlock more value from your existing 1st party data) In our short ~10 min episode we cover A LOT including: ➡️ Defining data products (is everything a data product?) ➡️ Do UIs matter at data products? ➡️ What are the main challenges building data products? ➡️ Should PMs specialize to data PMs? ➡️ Are business models for data products changing with LLMs? If you're a PM and interested in data or data products, then please check out the write-up and full recording in the comments below. New bitesized "Lunchbox" episode will drop each week, with a single focus, tactical advice, from current operators, so follow me (Pulkit 🔔) for short updates in your feed.

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As the cost of building software aided by AI approaches it’s asymptomatic minimum, B2B SaaS is already changing fast and we need to strap for the headwind as this is way bigger than post ZIRP tightening. Klarna replaced their salesforce and workday stack with internally built AI tools. OpenAI’s new o1 model is testing great on reasoning and code generation and writing much more complete software with just a few prompts Cursor is now already embedded in software development workflows and will massively improve the productivity of engineers AI agents will be able to communicate with each other, exchange data and resolve dependencies Net of all this is that the marginal cost of building a software is diminishing. That means more copy cat companies and no differentiation. Differentiation gets copied away really fast. The 2nd order effect of that is a total commoditization of software and SaaS, with every category becoming almost instantly crowded. Combined with AI driven content explosion, even content will not be enough to stand out. At least not with average cookie cutter content. So net net / undifferentiated softwsre and undifferentiated content — means much more intense attention wars. Getting attention of buyers and users won’t be easy as Kieran Flanagan mentions in his post as well. SaaS economics leading to new attention economics where the competitive currency changes from features and product capabilities to grabbing and retaining attention. SaaS was valued for high gross margins compared to traditional businesses. What investors have realized is that the competition bleeds away that advantage and necessitated perpetual investment in product roadmap and customer retention - just to protect the initial ARR, leading to poor downstream metrics like operating margins, ebitda and fcf. This means SaaS has to get internally more efficient. And Klarna is showing us how. So the companies that survive this commoditization phase will be the ones that can A) deploy AI internally to boost operating margins and B) command attention to fuel the top line. We are headed into very interesting times.

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