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Growth: What I learned from building growth engines for Marketplaces — An interplay of engines (Part II)
Marketplace efficiency is all about understanding the ‘User Intent’. No wonder best growth teams spend a considerable amount of time to understand their users and their intent. The better we understand the intent, the better will be the product that can serve the users.
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Data Science: Framing the business problems as machine-learning problems (Part I)
Solving the right problem is more important than solving a problem right away
Data Science: Framing the business problems as machine-learning problems (Part II)
The real value of data science is rarely in snapshot but in motion
Data Science: How to increase the adoption of data science models in your company
However, as I started interfacing with the team members of the data science team, one thing that came up repeatedly was that despite shipping some ‘good’ machine learning models, the adoption of those models among business stakeholder teams was almost zero. As per the team, there was just no enthusiasm for any machine learning models. In the last year alone, the team developed a propensity model, booking projection curve, demand forecasting, etc.
Data Science: Framing the business problems as machine-learning problems (Part III)
The real value of data science is rarely in snapshot but in motion
Growth: Self-Serve Sales Model (Part II) - How to use product qualified lead to enable growth
The self-serve model has its own risk. So before thinking of implementing that, it is important to evaluate the risk and its mitigation strategy.
