DealMaadi…proof of concept for community ranking based aggregators

DealMaadi is an experimental webapp that has created by Rajiv, a Bangalore based software engineer. It adopts a user contributed approach to sharing & finding the best shopping deals on the web. The site uses the popular Digg style voting widget to rank various deals and push the best ones to the top of the homepage. You are likely to find all kinds of deals- discounts, offers, clearance sales, buy X get Y free etc. This is a part time venture for Rajiv and his future plans with the site will depend on the response he gets. Monetization in any, will be through contextual ads and sponsored deals. Not withstanding its experimental nature, I find the site’s basic layout and design very effective and without any frills. The moment you land there, you know what the site is about. There is a very neat categorization structure for the deals and you can browse by the popular or the latest ones. I can’t add much here except wish Rajiv for his venture. Oh yes, just in case you get confused (like I was), the word ‘Maadi’ is not a mis-spelt version of ‘mandi’. Maadi (as the FAQ section explains) is a hackneyed slang used by non-localities in Karnataka originally meaning ‘do’.

The internet as a filter and relevance of Search V/s Ranking:

One of the reasons that prompted me to write about this webapp (in spite of its experimental nature) is the dichotomy between traditional search and ranking systems, in the context of aggregated websites. The internet is a great medium because it is free (largely) and it is a huge repository. This factor by itself, is incidentally, one of its biggest problems as well. Because it is so big and because creating content is so easy due to low entry barriers, you will always be confronted with a fundamental problem – How do I locate good content amongst the mountain of sub standard content? How do I get the best content without having to waste much time searching for it? That’s where community based ranking systems come in. That’s also why DIGG IS SUCH A POWERFUL IDEA. Its community based ranking methodology filters the aggregated content and ensures that the best floats to the top. I think the Digg idea, while best known for tech oriented news, can be applied to anything that is user generated or user aggregated. And in this regard, I find DealMaadi quite relevant. I’m not sure if this (DealMaadi) is an original idea but at a conceptual level, it has tremendous promise.

Let me submit proof about the applicability of the Digg voting methodology to other fields as well. I wrote this post last night, planning to put it out today in the afternoon. Just as I was about to do so, I got the daily RSS email feed from TechCrunch into my mail. The lead story on TechCrunch is about a resume aggregator website called TalentSpring, that is using the Digg style voting to isolate the best resumes, to be considered by prospective employers.

Off course whether Talent Spring (or DealMaadi) is a commercial success is going to be influenced by a lot of other factors, but the core idea is indeed very powerful