In startup land, that’s pretty much one of the key aspects of customer development. Figure out the market or business model first – experiment and iterate to identify a replicable, scalable revenue model before stepping on the pedal. Chances are quite good that a product is world changing only in the entrepreneur’s head. It doesn’t matter if it was agriculture a hundred years ago or high technology startups today, some basic concepts remain the same.

Of course, the customer development methodology is a lot more than the one analogy I described above. I heard Steve Blank’s first class was standing room only last week! But, it’s possible to find lots of resources on the web. Here’s a good video series – part1, part2.

As part of the IOLab course, we worked on a bunch of mini-projects related to themes like the semantic web, controlled vocabularies, distributed classification etc. We spent around 15-20 hours on each project. The Flickr Tagr, which Ljuba and I worked on, was one of the projects that was in a complete enough form. Here’s how we described it:

Flickr Tagr visualizes photographs based on social classifications (i.e. tags). It allows users to search for photographs tagged with particular words while showing them additional tags related to the ones selected so far. The goal is to allow a user to quickly visualize the photos available for an arbitrarily selected intersection of tags, while exposing them to other tags they might find interesting. Users can also click on a photograph to see a larger version in a custom-built light box.

We thought the faceted search interface to Flickr was fun to play around with!

PowerMeter, Microsoft’s Hohm, WattVision, a YCombinator backed startup and others pull in data from smart meters and visualize it for end users. Studies have shown that providing data can help change behaviour, so the main aim is to reduce electricity consumption. The big guys like Microsoft and Google don’t charge for the service, but the startups have a revenue model based around the value add of providing access to the data and sales of hardware that prevents having to go through the utility. But, I think there is a third possibility that is around the corner, waiting for large scale deployments of smart meters.

When we were discussing information leakage in the privacy and security course I took in the Fall, I remember Doug mentioning that it is possible to study the electricity consumption pattern and determine which applicances / sources drew power based on the wattage consumed, duration it was on etc. Given a large enough corpus of data (with signals based on actual consumption, geography, number of residents) it should be possible to do it quite accurately. That should make temporal targeting of ads very feasible. If you open the fridge to get a bite to eat at an odd hour and load a web page when you get back to the seat, it should be possible to display a dieting ad. A shampoo ad after getting out of the shower? Of course, there are privacy implications, but this is a world where people are willing to share their credit card transaction details, so there should be takers for it if you promise a reduction in the power bill. Behavioural data is already being used for targeting ads online. This just uses meat space behavioural data. Creepy? Sure, but so was Gmail for about 1 month when it launched. The argument that only machines look at the data was good enough then and should be good enough in this case too.

What most people don’t know is that Narayana Hrudayalaya is very similar to Aravind Eye Care, which pioneered the high quality, low cost care through scale model. I wrote the final paper for the “Market based mechanisms for poverty alleviation” course I took this semester on Aravind and was amazed at the scale of their achievement. I was always aware of Narayana Hrudayalaya (I went past the hospital on my way to work for a year!), but not of the model which made them so successful.

There is an opportunity for a Aravind Eye Care or Narayana Hrudayalaya in every area of healthcare – we just need the people with the tenacity of Dr. G. Venkataswamy or Dr. Devi Shetty to make it possible. This is an area of innovation where India has all the right advantages – large patient population, skilled doctors, low cost manpower and access to the best medical technology. There was a time when people in India had to go to developed countries to get the best medical care. I’m happy to see that trend being reversed over time.

I’ve wondered how hubs, in both protocols, handle updates when there are lots of subscribers (in the millions). The obvious answer is a job queue, and that’s what one of the PuSH implementations of the hub does (backed by RabbitMQ). I asked Joseph Scott, the Wordpress developer who implemented the feature what they do for WP.com, and I believe it’s something similar. The Wordpress plugin at this point just sequentially pings all subscribers. That should be sufficient for the vast majority of users. The interesting problem is how real time it would be when a hub has to update 10 million subscribers? Also, what is acceptable as real time? 1 second, 10 seconds, 1 minute? Interesting thought experiment, but I think that’s a problem to be solved when we get to it.

The best part of the day was that I finally met Doug Kaye in person at the meetup. He’s the father of podcasting if you’re not aware.