Profiling methods for buyer identification (such as ICP or persona)

BACKGROUND

Identification of potential buyers (e.g.: Ideal Customer Profile (ICP) or Personas) in social networks, i.e. establishing potential buyer patterns based on expert knowledge and on the intelligent analysis of data available in social networks.

Problem

Identifying potential customers is a complex and essential task in marketing and sales. Existing tools in the market allow a certain degree of targeting but they do not categorize them considering metadata such as activities and tastes.

Benefit

Profiling social network users into different types of buyers according to their interests, allows marketers to generate targeted advertising to customer groups and increase sales revenue with more cost-effective campaigns.

METHODOLOGY & results

Architecture: Could architecture based on micro-services.

Developing language: Python.

ML techniques: NLP techniques and fuzzy logic.

Results: Module that profiles types of buyers through metadata extracted from social networks.

This project was carried out before AI Shepherds’ foundation by its team members.
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