Mahalo is amazingly both validation of the Cogmap approach and an example of a Web 1.0 model that I fear is doomed to fail. Mahalo is based on the concept that there is a difference between content and automated content in ability to identify what is valuable to a consumer.
Theoretically, the benefit of automated services is their ability to serve a broader range of demand. In Mahalo’s case, Google answers every query but Mahalo only answers 10,000. Zoominfo has millions of companies, Cogmap has thousands.
In my post on Cogmap data quality versus sites like Zoominfo, I made the case that the Mahalo/Cogmap approach probably works pretty well.
Having said that, I have to say that I am not loving the Mahalo approach. It seems to me like you have a few problems:
- Mahalo seems to have all of the Web 1.0 problems I have documented in my previous post on Web 1.0 versus Web 2.0 business models. Jason pays all of these editors to produce all of this content and it sounds so expensive. For every editor that he does not pay, his service adds that much less value, for every editor he pays, he incurs costs. Costs increase as value is created. Mahalo benefits from being able to rely on automated services to determine where the most value can be derived by human editors, so maybe there is some point on the curve (where the most popular search query generates a lot of value but the least valuable query costs more than the value they create) where they can generate the most value with just a few editors have a sustainable model, I don’t know.
- Why not Wikipedia? Mahalo loves to point to Wikipedia and, if you think about it, it costs Wikipedia less to generate its data then it cost Mahalo. Wikipedia relies on user-generated content whereas Mahalo is driven by an editor. It seems like Wikipedia is Mahalo 2.0.