BlackCloud

It is not about being lazy or shady. It is about encouraging accurate information from real Facebook accounts based on the information users already have compiled. The site helps you meet new people based on that information and gives you the opportunity to eventually become Facebook friends. You need a Facebook account attached to become Facebook friends.

Right now it is based on common interests and location. In the future it will likely look for other data that similar connections can be made on.

Airtime recently launched and they are following the same model as it turns out due to their close alignment with the Facebook community and the data it provides.

There are plenty of "meet new people" sites out there where you enter whatever you want about yourself. This is a different angle on that which provides functionality leveraging Facebook which Facebook itself is not going to provide.

Thanks for the feedback.

I do have some ideas around guiding the user through the initial experience outside of the initial overlay and get the immediately involved with interacting with others. I think opening up the lines of communication between the users immediately is key.

With regards to the Facebook login I understand your point, hell I've said it myself about other sites, but in this case the entire experience is based on the data from your Facebook profile. It encourages honesty about who you really are and makes it so it is not another profile for you to manage. Without the ability to use the Facebook data you wouldn't be able to have much of an experience. I understand that a percentage will walk away from the site due to that but I'm going to have to focus on the millions of people who do use their Facebook account on a regular basis to login to a third party site.

It depends on the specifics and complexity of what I'm trying to track. For simple things Google Analytics works pretty well. You can just do some simple searching or reports to show you the averages of user usage.

For more complex situations (often within the application itself) I've actually built some APIs which allow me to store generalized data about any page interactions and relate it back to a particular page load instance. Once I have this data I can slice and dice it to figure out exactly what users in general are doing and also allows me to drill in and follow a particular page load and what that user did specifically. I can be as complex as simulating sitting behind the user and watching them use the app. It's surprising what you sometimes learn about how a particular user or group navigates a page and how different it is from what you initially expected when you designed the app.

I have found A/B/n testing to be very helpful. The more you can track about the users interaction with the page before a successful or failed conversion the better. You can use this info the determine where along the line users are falling off the path you want them to be on. After a few days to a week (depending on traffic) take a look at the results of the A/B tests and eliminate what isn't working. Apply the lessons learned from the in page analysis to build a new B test and repeat. I've found that over the course of a month or so following this method I can double and sometimes triple my conversion rates. Sometimes the smallest details that you wouldn't have predicted make all the difference.