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.

By the end of the project, students should complete the following list of activities:

• Familiarize themselves with Pifit concept.
• Compile a design flow of multiple campaigns running consecutively
• Design modelling to monitor the campaigns unfolding in real time
• Exponentially increase the flow of campaigns
• Calculate any identifiable risk or breaking points

Bonus steps would include:

• Increasing or decreasing the ad quantity formula while identifying any benefits

Final deliverables should include:

• A presentation on the finding in a shareable format.
• Feedback on the modelling stability as campaigns increase
• Which formula was most favourable

Students will connect directly with us for mentorship throughout the project. We will be able to provide answers to questions such as:

• Current product understanding
• We will provide a CPA with experience in financial modelling to assist on any challenges
• Any sort of branding or styling advice
• Input on choices, problems or anything else the students might encounter
• Regular checkpoint meetings on a bi-weekly basis