

Ask HN: Need feedback on my Professional Quantification website, Predikt.co - amogh10

Hello hackers, I am looking for feedback on Predikt.co (Quantifies your Linkedin and Facebook profiles). 80+ users have already registered and we are in a beta mode. What do you think of this idea? Here is a sample profile if you dont want to log in (http:&#x2F;&#x2F;predikt.co&#x2F;users&#x2F;view&#x2F;6427DX551) or view trending users www.predikt.co
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dsutoyo
I think the idea has potential. I am curious what kind of insights and
analytics you will be providing.

It would be good to start with a specific audience (e.g. programmers) and use
GitHub activity to factor in their professional experience as an example. I
can see this being useful for recruiters to screen developer linkedin
profiles.

The name predikt implies you plan on predicting something, but I am unclear
what you are predicting. Potential salary range? How likely to leave current
job? etc.

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amogh10
Hi, thanks for the comment. There is some ongoing development on predicting
couple of main things: 1) Would a particular person be potentially a good
candidate for certain role. This is done by using similar other profiles as a
training set and use those factors to predict early on if someone would be a
fit. e.g. People who have studied in a university of reputation X, have Y yrs
of experience and have Z skills go on and achieve position 'A'. These factors
would be used to predict the users who share the traits and would likely land
in a similar position. 2) Predikt the probability of job hopping, likelyhood
of someone being a passive job seeker, potential salary ranges the candidate
falls into.

Right now, Linkedin and facebook integration are functional, certainly it
would be more useful to add all possible networks. Github, Stackoverflow would
be next. Some recruiters have approached and would like to use this for
screening their applicants.

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dsutoyo
Exciting! Thanks for the additional info, I definitely have a better picture
now.

I think the recruiting industry can definitely use more help from technology.

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amogh10
Thanks. Here is the brochure for recruiting solutions, it has some more
details: [http://bit.ly/predrecsol2](http://bit.ly/predrecsol2)

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amogh10
Add comment for clickable links: Linkedin or Facebook login:
[http://predikt.co/](http://predikt.co/) Sample profile:
[http://predikt.co/users/view/6427DX551](http://predikt.co/users/view/6427DX551)
Trending users: [http://predikt.co/users](http://predikt.co/users)

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bruceb
Neat idea. I have to ask how FB comes into it. As most educational and work
info is going to be on Linkedin?

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amogh10
Thanks bruce. Yes, Linkedin is for sure the professional destination. Users
are slightly hesitant to give out linkedin data, Facebook has a 5x larger
userbase and people tend to fill minimal data such as job title and education,
so the idea is to build and use a professional graph so as to interpret
relevant information to the data and quantify it. There is some useful info
such as interests, likes, groups etc which give vital information too. The
plan is to integrate all possible social sites and aggregate the professional
data out of it.

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parthoghosh86
This idea really looks neat...

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amogh10
thanks :)

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davidsmith8900
\- Clickable Link ~> [http://predikt.co/](http://predikt.co/)

Personally I like the idea. I have never heard of it before. Something like a
Credit Score for profiles.

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amogh10
Special thanks for mentioning Credit Score. The algorithm we are building is
pretty much like a Credit Score algo. Not just because we show a score for
users, but because we use factors learned and deduced from similar other
profiles and use it to quantitatively predict the likelihood of a fit (risk in
case of a credit score). It would be ideal to use larger datasets for
training, however its still in beta and the algorithm is being updated
continuously. Thanks for the clickable link too :)

