Generating Appealing Brand Names
This work addresses the need for effective brand naming in marketing and business, though it appears incremental as it builds on existing computational methods with specific improvements.
The paper tackles the problem of generating appealing brand names for products or companies based on descriptions, using quantitative scores for readability, pronounceability, memorability, and uniqueness to rank names. Experimental results show that the names generated by their approach are more appealing than those from prior methods and human-generated ones.
Providing appealing brand names to newly launched products, newly formed companies or for renaming existing companies is highly important as it can play a crucial role in deciding its success or failure. In this work, we propose a computational method to generate appealing brand names based on the description of such entities. We use quantitative scores for readability, pronounceability, memorability and uniqueness of the generated names to rank order them. A set of diverse appealing names is recommended to the user for the brand naming task. Experimental results show that the names generated by our approach are more appealing than names which prior approaches and recruited humans could come up.