Glad you brought this up Adam Price. You got the formula right.
I would go a step further to add,
- Business can lose money within a city if they are catering to less dense areas (density in terms of number of orders per delivery person). It is essential to add more areas within a city it is best to take ‘demographic segmentation’ approach
- The same approach must be taken while expanding to other cities — data first approach throughs up some really interesting suprises
I have been working a on-demand home service startup here in India, team recently started re-allocating delivery resources to high density territories while simultaneously shutting down service in areas where order density was low. Second step, currently under execution, is to map demographics and income distribution of dense areas — this learning will be mapped on national data to identify next set of markets.
As a side note, certain segments like beauty, fitness, wellness with on-demand business models (where in user is consuming services outside home and at an establishment) the formula to success would be different. Here, it is essential to focus on optimising customer acquisition cost. You don’t want a condition where
(a) Business service provider gets from your app/site is too small and hence she doesn’t give too much importance to your app/site
(b) Customers don’t have sufficient options — demand & supply needs to be balanced [ at neighbourhood level ; not city level ]
What do you think?