Recommending Influencers to Merchants using Matching Game Algorithm

TL;DR

This paper explores using the Gale-Shapley matching algorithm to pair influencers with merchants, demonstrating its effectiveness in aligning interests and achieving corporate goals in influencer marketing.

Contribution

It introduces a novel application of the Gale-Shapley algorithm to influencer-merchant matching, translating performance metrics into effective pairings.

Findings

The matching algorithm successfully pairs influencers with merchants based on specified criteria.

The approach aligns influencer campaigns with merchant objectives effectively.

Experimental results validate the algorithm's applicability in real-world marketing scenarios.

Abstract

The goal of this work was to apply the ``Gale-Shapley'' algorithm to a real-world problem. We analyzed the pairing of influencers with merchants, and after a detailed specification of the variables involved, we conducted experiments to observe the validity of the approach. We conducted an analysis of the problem of aligning the interests of merchants to have digital influencers promote their products and services. We propose applying the matching algorithm approach to address this issue. We demonstrate that it is possible to apply the algorithm and still achieve corporate objectives by translating performance indicators into the desired ranking of influencers and product campaigns to be advertised by merchants.