We are building live demo (landing page + algorithm) for viral video marketplace that give users incentives of rating and promoting branded video content (i.e. campaigns). Our current goal is to showcase potential investors and partners possibility of "custom" market analytics and present test user stories related to various levels of users engagement. We want to demonstrate how users social relevance affects performance of placed campaigns and how much of their activity contributing to platform's viral spread.
a. user sign up to our platform using multiple social network profiles. We want to calculate (approximate?) users social profile "index" based on all possible factors, like number of friends, posts, reposts, messaging, tags, native blog posts etc. Parallel to that we want to locate and invite users with highest social status profile (search) within our users reach. At this stage we are looking to set up goals, identify limitations of current social networks APIs and to outline where and how we can create better native analytics for brands. For testing we can use exiting open APIs like FB social graphs with notes on what we are looking to disrupt further with our platform (options?)
b. once user decided to use our platform, they will select test campaigns they believe would be the most successful. They will be asked to contributed some value as "bet" (putting chips on the campaign) and also to repost these campaigns throughout their social networks. We want to calculate how the campaign "travels" within their social sphere and how it contributed to spread of the campaign. (We can use something similar to [url removed, login to view] API). Factors for campaign spread contribution is not just "eyeballs" but also speed of the spread. Approximate viral cycle of the campaigns are 3 days. At this stage we want to show options and what can be possible to build - we don't need yet the full features. We want to demonstrate test on several users cases and to define main functionality that we will be building.
c. once campaign is completed, we want to demonstrate in demo mode how users "incentives" are calculated and essentially how user can manipulate future campaigns for better returns (i.e. either increasing his/her social relevance or putting higher value chips - higher bets). The most unique part of the project is building the mechanism that will allow users to get higher returns. For brands we need to demonstrate that we will provide special type of analytics superior to any other that will showcase how campaigns are performing in accordance to users social relevance (what type of users are most suitable for brand's to target for similar products etc.) Again, we are not looking to build full feature product yet, but to set up parameters, goals and our unique feature set.
This project is hybrid of coding / consulting. We need to build landing page with some build in demo mode and to explain to investors what exactly our goals are going to be.