Our Business Model
While our main priority is getting to a critical mass of users, it's important to make sure we're building the groundwork for a viable future business.
It is important to get feedback, not only to understand how people are reacting to the business, but also to make sure we're not missing any unseen challenges. We have a lot of recruiters, entrepreneurs, and experienced investors reading and kicking the tires now is important.
First, there is the established model of aggregating communities around goal oriented activity. That has been established as a viable means of revenue generation through advertising and lead generation. TheKnot.com did $95 million of revenue in the 12 months ended 9/30/07, 50% of which was advertising.
From a content perspective, aggregating an audience around discovering and planning a career has similar potential. Certainly a lot more people need help each year than plan a wedding. Even now, with just our informational site up, we've already seen targeted ads for continuing education, professional career coaching, and industry conferences for starting businesses. In addition, it would seem appropriate to have targeted job classifieds down the line as well.
Monster saw enough value in the potential for career focused audience aggregation that they bought Affinity Labs for over $60 million after just a year or so in business.
They focus on a handful of career verticals. Here's he quote from the press release:
networking. Employers will also benefit by having efficient access to a targeted pool of job candidates in desirable career fields."
This sounds pretty similar to what we have the potential to provide.
Aside from the ads, I actually think the real key to our business potential will be in our database of users.
The basic concept of Path 101 is that users provide data about themselves so that we can compare them to others and show them possible career paths. While our database is sure to be full of valuable insights into careers, it's not the database itself, but the application of the database that drives value. Because we have relevant information to show candidates, they're willing to share more with us about who they are and what they want.
Our business goal is to know more about potential candidates than any other candidate search site. Not only can we provide a better service to users that way, but that makes candidate searching for recruiting purposes that much more targeted--better for both sides.
Candidate search is a significant component of all the major job boards and it's a bulk of LinkedIn's revenues, which is estimated to be $100 million next year. Are we competitive with them? I don't think so. LinkedIn is built on trust, networks, permissions. We're coming at things from a slightly different approach. I actually think that the kind of inherent trust built into the LinkedIn network could help power other sites, just as I hope LinkedIn will open up to allow sites like ours that maintain a really deep information relationship with our candidates to help power their offering.
Both of our respective businesses are tremendous improvements over current methods of resume searching and downloading--even though those businesses are driving significant revenues for the mass-market job boards. Companies don't want a firehose of untargeted resumes--they want the right candidates. Companies like us and LinkedIn using net-native approaches to improving candidate search have a tremendous market opportunity.
Such value creation in this industry stems from two basic questions:
"How much is a good hire worth to you if you are an employer?"
"How much is the right job worth to you if you are in the working world?"
That's why employment related services have consistently been one of the best revenue generating online businesses out there and why there's still so much value out there to be gained from matching the right people to the right positions. The market is begging for disruptive approaches to the Jobs 1.0 model of calling big job boards and newspapers on the phone to post a job for $450.
I would easily, however, pay a company $450 for 50 candidates that all score very highly on their interest/ability to be self directed, whose friends say they'd be the most easy to work with, and, in our case, whose resume pops up uncommonly appearing words like SVD (Singular Value Decomposition) and not SVD (Society of the Divine Word)--which our textual algorithms would be able to differentiate between because of the other statistics related terms that also appear on other quantitatively inclined programmer resumes.
Anyway... thanks for reading down this far and allowing some clarification on our business vision. We're very interested in hearing your feedback.