Puja Hait

I will share first two steps that I follow. Step 1: Is this problem worth solving? 1.1 Problem definition and user segmentation B2B product: A business customer must have a genuine painpoint that they are willing to pay for. Some problems are not big enough problems, hence not high priorirty for the business users, these are not worth pursuing. Fine tune the problems till they hit   B>B>C: The business user/stakeholder may have rightly identified a problem but may not have the best ideas i ...Read More

Start with a Total addressable market (TAM) * share of TAM you can get in next 3-5 years *confidence level *Revenue per user per year * 3-5 years. In the RICE framework, you would divide TAM * Share of TAM (influence) * Confience/ Effort to then help prioritize. (Desc) Calculating Share of TAM you can get in next 3-5 years is a art more than science. Do a SWOT analysis for yourself, incumbents in the market, if any and emerging players. Also keep in mind that market/users may not always be ready ...Read More

I would say there is no substitute to real user data.   User research is table-stakes. But in my experience, not always representative of "actual" usage, so don't overindex on specifics. Rather validate if the problem statement is indeed important for the user segments. Because if it is, then they might be more patient with your iterations towards solving their needs. Else they are very likely to abandon very early on and never return. A good way to test is whether they are willing to pay for th ...Read More

I would consider the following factors: What are the goals at that time? How best are the goals served? e.g need a product-2 to monetize and sustain product-1, which is growing but no line of sight to monetization  Competitive value - What is the best way to build or defend moat? Is the sum going to be greater than parts? Vertical or horizontal integration? Solution offering rather than piecemeal feature offering? Execution confidence- Are we in the position to take on a second product? Can we d ...Read More

In GenAI product development- Your role as a PM essentially shifts from writing a PRD to writing Evals in addition to PRD. The Evals are your reality check on how well the model is actually performing for your intended usecases / user queries. Also the Eval metrics matter a lot. I would treat them as input metrics and engagement (e.g DAU) as output metrics. Its because if your output quality is great, users will come back so focus on making your solutions really shine and matter. Ofcourse you st ...Read More

It depends on the lifecycle of the product and goals.  0>1 product: Goal - to find product-market fit. Here its very important to think through your hypotheses, possible outcomes (Prove, Disprove, insufficient signals) and what you would do next - next set of features, V2 of the MVP and so on. Charting this out helps you then answer what you must absolutely answer to get to the next step. Once your product enables you to achieve testing of your hypothesis, ship it! This assumes that product/s ...Read More

Great question! My response to "At what point is a solution ready to be shipped?" applies here.  The aspect of launching a true MVP is harder in a large organization, when the expectations from the customers are high and I think rightly so as the stakes are maybe much higher.  In my experience, what helps calm the nerves is to play out the outcomes with the team: What is the worst case scenario?  Asking why is this not acceptable and thinking through ROI, opportunity or sunk cost on doing more, ...Read More