Fork Project

Fork project is a new extension for Pinterest. Pinterest is one of the biggest food database. This giant social media has access to thousands food boards, however their data is more quantitative . What if this social media wants to be the pioneer of food trends forecasters?

With Fork project, Pinterest has access to qualitative data. Users can find their pinned foods nearby and taste them. These foods are served by professional chefs in Fork food truck. then people can share more data about the real food in Fork app.

At the end the data are analyzed and published by Fork project; therefore, different parts of food industry (retails stores, restaurant, big corporates, etc.) can have access to the website and track trends locally, nationally and globally. 

Studio II (Brand Extension) in College for Creative Studies (CCS) | Jan-Apr 2014 | Detroit, US  




Brand Study



Pinterest Content Analysis

To find an opportunity and new market for Pinterest, we need to understand the current market and users behaviors. So three studies were done in different levels:

  • Number of Users (Pinners)
  • Data Size (Pins)
  • Users Purchasing Behaviors 


Number of Users (Pinners)

Pinners Behaviors


Data Size (Pins)



Users Demographic Information & Online Behaviors

purchasing behaviors


Study Results




Pinterest has a good business opportunity in food industry due to its vast data and high potential for food trend forecasting.


Trends Forecasting

Trend forecasting is a complicated but useful way to look at past data, determine possible trends and use them to extrapolate what could happen in the future.   


What Are The Benefits of Food Trends?



How Food Trends Can Be Forecasted?

Data is the only powerful key in this process and experts use it in two different levels:


Quantitative Data: They are tangible and concrete numbers that present different patterns based on time. Food trend forecasters collect online data or use different surveys to find quantitative data.  

Qualitative Data: They are intangible facts about users' behaviors that present deepest layers of forecasting. Mostly these kinds of data need more accurate analysis. Food trend forecasters use food festivals, food exhibitions, food competitions, etc. to collect qualitative data.   


Competitors Positioning Matrix

Competitors bench marking

Nestle Professional : Uses their own brands feedbacks and their partners.

McCromick : Uses their brands feedbacks and also online data from an app called FlavorPrint.

Kraft : Uses their users feedbacks and also different field study to predict food trends.

Bellwether : Uses different food festivals and exhibitions to collect most qualitative data among other competitors.

IBM : IBM is the most innovative company in this competition. IBM Cognitive Food is a food truck that serves foods based on peoples' tweets. However Cognitive Food doesn't have access to specific food data source. Also IBM doesn't have publish an official food trends report yet.  

National Restaurant Association : They just collect data from restaurants around the country and compare them to predict the future.   


Brand Extension Proposal


What Are The Fork Project Components?



How Does Fork Project Work?

System Structure


Fork Project Uniqueness #1 


Fork Project Uniqueness #2 



Revenue Models 

Two different revenue models were designed for Fork Project: