techTribe, the career networking site (profiled earlier on Webyantra) has launched a referral recruitment service called frontFoot. This is claimed to be a patent pending concept and the first one of its kind in the world; it is based on the rationale that the best way to recruit non entry-level employees is through employee referrals & professional networks. The way it works is simple- companies can post for middle mgmt openings (read high-paying jobs, minimum 8-10 lacs CTC) on techTribe; users can refer (frontFoot) other tribers as candidates for the jobs; if the company hires the candidate you referred, you make 10K. To control referral spam & filter down the resumes based on relevancy, there is a system which tracks and surfaces the referrer’s cumulative ranking; thus if you randomly refer candidates and they do not end up getting hired, your ranking nosedives, which does you more harm than good.

I like the concept for the following reasons:

Firstly, it addresses a REAL PROBLEM that afflicts recruitments in India; the lack of quality manpower and how to search for good candidates in an ocean of mediocrity. In fact, just a couple of weeks back, I wrote this post about online job boards and how they can be useful in addressing the quality dimension in recruitment, that none of the Indian jobsites seems bothered to address. I see frontFoot as a vindication of my stance.

Secondly, for all those who are looking for answers about how to monetize social networks, there is something to learn here. frontFoot is an innovative way by which the site can become useful to recruiters as well as to job seekers, while rewarding its genuine users monetarily.

Finally, the timing of frontFoot’s launch hits me real hard in the face. Let me explain how- two weeks back, I was invited to participate in an online discussion about emerging trends in India in the fields of social media, user generated content & social networking. The discussion was published on Blogworks.in, a social media strategy blog. The discussion panel included Prerna Gupta of Yaari.com & Alok Mittal of Canaan Partners/Venturewoods. And let me quote Alok from the talk’s transcripts- “…I would expect to see the first career social network to start gaining momentum in next 12-18 months……I think it’ll be a mix of LinkedIn and Jobster (passive and active hiring network); I think it will be more intrusive that either of those (Indians want good jobs real bad); and I think it will be some mix of consumer ownership between the companies and the SN provider (rather than pure media model of LinkedIn)….I still do not think it will get to ‘senior level hiring’ in the short term, more likely to be junior-mid levels…..”

That was two weeks back. Alok’s guess was absolutely correct, though it happened 12-18 months sooner than he predicted.

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