Develop a Big Data Strategy, Architecture and Roadmap for a Direct-to-Consumer Mass Personalization Platform in the Consumer Goods Sector

Project Description

TASK

Create the list of potential data sources and conduct feasibility assessment of these data sources to determine if and how data science can be applied (separately and together) to grow revenue and reduce costs for retailers and consumer goods manufacturers.

 

 

COMPANY OVERVIEW

INS builds a scalable blockchain-based Direct-to-Consumer mass personalization platform for the consumer sector (FMCG, CPG, groceries). There are 3 involved parties: manufacturers, retailers, and consumers. Consumer goods manufacturer and retailers will be able to provide personalised offers directly to consumers (discounts, promotions, etc.) via mobile app based on consumer personal data (gathered online), consumer purchase history (gathered offline via POS on checkout), and other data sources (from manufacturers, retailers, etc).

 

 

PROBLEMS TO SOLVE

•          What data should be gathered?

•          How to use these data to increase sales in retail stores?

•          How to use these data to increase sales for selected consumer goods manufacturers?

•          How to align interests of consumer goods manufacturers and retailers?

•          How to make personalised offers (discounts, rewards, etc.) for consumers with best-in-class personalisation and success rate (customers view offers via a mobile app and purchase promoted items in offline stores)

 

 

WHO WE NEED

•          Data scientist with 3+ years of experience in building mass market products

•          Deep understanding of the retail sector

•          Deep understanding of the consumer goods sector

•          Out-of-the-box and creative mindset

 

 

DATA SOURCES TO BE USED

•          Consumer personal data

•          Consumer social networks data

•          Data from a consumer goods manufacturer

•          Data from a retail store

•          Any other data sources that can be useful (weather forecast, holidays schedule, traffic situation, location-specific data, ect)

 

 

TECHNOLOGY

•          Ruby on Rails

•          Hadoop

•          Any other relevant technologies (we're open to the most advanced and cutting-edge solutions; we haven't started the development yet)

 

 

DELIVERABLE

Advisory service on developing a big data strategy, architecture and roadmap.