Advanced Data Analysis and Empirical Research Methodologies - PIFit

Pifit (Paying It Forward) is a patent-pending app focused on delivering digital advertising to users in a new interactive manner. Designed as a Not For Profit, we have created a complete wall garden platform. Utilizing the profits from advertising campaigns creates a monetary value, an Instant Cash Discount (ICD) for our users. Ads are delivered to users’ devices upon their request by scanning the Pifit logo at a merchant store. Each ad is framed with a $$VALUE amount for the ICD which users can apply to their immediate purchase at the merchant store. One can think of the ICD as compliments of the advertiser to the user.   Campaigns are run on a cross-platform, meaning the merchant location where the ad appears is not related to the actual advertiser. PIFit is essentially a B2B2C APP that confirms the viewing of digital content.     Our Live Dashboard completely tracks every aspect of each ad campaign and user’s actions. We are seeking to micro-analyze the process by populating it with individualized ad campaigns, mixed campaigns representing more than one advertiser and then assessing that data. The objective is to find any ceiling capacity or challenges in the system.   More specifically (1) see how many campaigns can be run consecutively and simultaneously - is there a ceiling? (2) what is the best modelling to use to monitor the campaigns in real time What's involved: Conduct background research on existing or comparable models. Identify key data areas of the campaign from inception to implementation. Forecast modelling based on a spread of 20% $3 30% $2 50% $1 Using assumption and risk models calculate if there is a breaking point.

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