A friend is emigrating to Singapore next month. We decided to buy tickets online and tried out many options like travelocity, yapta, ixigo, cleartrip, fly.com and many more. While we could find the cheapest fares at ixigo, the process still took around 1 hour of insane clicking here and there.

Clearly, the fare discovery problems still remains unsolved at large. The existing online fare discovery products have managed to reduce the no of sites to probe for getting best fares, but the growth of such products has been non-linear, as a function of time. The problem is solved at their perspective, but for the enduser, abundance of such products has kept the problem at the same place.

The point will be more apt with the following graphic. Here A’s are the airlines, FD’s are the Fare Discoverers, and Cloud represents you and me.

This image shows the structure of fare discovery when the first few companies started to appear on the scene. Users had to browse through A1,A2….A5. Then they had to search FD1, FD2. Net result? Time reduced. Following graphic depicts the scene now.

Clearly, the companies like yapta, ixigo consider the problem solved, but for someone who is in the cloud, it has become more problematic. The key reason being, Fare Discoverers(FD’s) not only aggregate the data from the Airline(A’s), but also provide their own discounts etc (the standard i-buy-in-bulk-and-retail approach). This has lead to increase in price sources all together. One might argue that one size fits all approach never works out in such cases, but to me, the bottom line is the solution to the problem, which is far from reality as of now.