Social Media Ready Caption Generation for Brands

TL;DR

This paper introduces a novel pipeline that generates engaging social media captions aligned with brand personalities by combining image captioning and personality-specific text generation, enhancing brand marketing strategies.

Contribution

It presents a new multimodal captioning pipeline tailored for brands, integrating image understanding with personality-driven text generation, which is not addressed by existing models.

Findings

Effective in generating brand-aligned captions

Outperforms baselines qualitatively and quantitatively

Allows customization with hashtags and handles

Abstract

Social media advertisements are key for brand marketing, aiming to attract consumers with captivating captions and pictures or logos. While previous research has focused on generating captions for general images, incorporating brand personalities into social media captioning remains unexplored. Brand personalities are shown to be affecting consumers' behaviours and social interactions and thus are proven to be a key aspect of marketing strategies. Current open-source multimodal LLMs are not directly suited for this task. Hence, we propose a pipeline solution to assist brands in creating engaging social media captions that align with the image and the brand personalities. Our architecture is based on two parts: a the first part contains an image captioning model that takes in an image that the brand wants to post online and gives a plain English caption; b the second part takes in the generated caption along with the target brand personality and outputs a catchy personality-aligned social media caption. Along with brand personality, our system also gives users the flexibility to provide hashtags, Instagram handles, URLs, and named entities they want the caption to contain, making the captions more semantically related to the social media handles. Comparative evaluations against various baselines demonstrate the effectiveness of our approach, both qualitatively and quantitatively.