feedback pt 3

 This question seemed to bring about the strongest response. Of the twelve people questioned, each and every one of them agreed that it is definately a major issue to locate a club that they have never been to before. The difficulty of finding a nightclub definately impacts on the decision making process, and having the iClubber interconnected with the Google mapping application would definately make decisions easier and would essentially influence which nightclub to “hit up”.

feedback pt 2

There were a number of different answers for this question, however i have managed to draw some useful ideas from these answers. As a whole, there are two simple factors which should contribute to grading the “status” of a particular nightclub. Firstly, it must be taken to consideration the ratio of males to females. Secondly, the estimated line up time as well as a probability of successfully getting in should contribute to grading a nightclub.

feedback pt 1

Overall, regular clubbers take a number of factors into consideration when picking and choosing which nightclubs to “hit up”. A number of people have said that it is not only the size of the ques, but also the type of people that go, the price of entry and also the price of drinks. One person said that they base their decision on whether any clubs have any promo offers such as two dinks for the price of one.

Prototypes: Gathering User Requirments

When constructing my protoype there were are number of issues that i needed to take into consideration. Firstly, it was important to find out what specific information people require when deciding which nightclub they will go to. Secondly, what factors should contribute to grading the status of a particular night club. Also to find out if there are ever any difficulties experienced in finding particular nightclubs, and whether or not a built in mapping feature integraded with the iClubber application would have an impact on the choice of a particular nightclub.

Taking all of the above issues into consideration, i devised a simple questionaire to extract information from people that fell within my targeted user group: people between the ages of 18 and 30 who enjoyed going out to nightclubs.

Q1. What information do you take into consideration when deciding which nightclub to? Eg the size of the que.

Q2. In your opinion, what factors should contribute to grading the “status” of a particular nightclub?

Q3. Do you ever have problems in finding nightclubs that you have never been to before, and would you find nightclub mapping within the iClubber useful?

interesting iPhone article: iPhone hacking in Australia

browsing the web the other day i came across an interesting article regarding iPhone usage in Australia…. check it out its cool… http://www.smh.com.au/news/technology/code-crack-opens-the-iphone-floodgates/2007/09/04/1188783213914.html

post presentation

farkk ive been pretty busy moving houses but ive finally got a chance to add another blog. i really need to get into the habbit of doing this more often now… it felt good to get that presenttion out of the way…i think it went fairly well. im not sure what to think about no questions being asked though…does that mean that i explained my applicaation well? or does it mean that nobody understood my idea? anyways im going to bed now…goodnight

introducing: the iClubber

trying to think of other ideas was too hard, so ive decided to stick with my first (and only) idea.  ive decided to name my application –  iClubber. as i mentioned in my previous blog, the purpose of this application is to display the entry status of a city’s nightclubs, whether red, orange or green, while also integrating with the google mapping feature for directions and the quickest path to get there…

tonight i will be putting together my slides and preparing for friday.

in the mean time…

you stay classy san diego

first proper idea

well its taken me long enough but i finally have an idea worth writing something about…im thinking an application that will allow night clubbers to be able to distinguish which clubs they can get into and which they cant. sort of like traffic lights being displayed next to the club names on the application as a guide.

a green light would mean that the probability of getting in is high: 75-100%

an orange light would mean that the probability of getting in is moderate: 50-75%

a red light would define a “no go zone”, and that the probability of getting in would be unlikely: less than 50%

this application would work with the google mapping application, and users would be able to scroll and check the status of the clubs closest to them.

Dancing Midget!

i have had no good ideas yet….ive just been looking up cool videos on YouTube…check out this dancing midget!!