Data-Driven Product Naming for AI Products

Client confidentiality prevents sharing specific artifacts and impact metrics, but the following overview provides a representative look at my process and the results achieved. Please reach out for a verbal walk-through if you’d like to learn more.

The Challenge

With AI products flooding the marketplace, naming conventions have become cluttered and inconsistent, creating confusion and eroding trust. The recruitment platform’s AI products were part of a larger platform, and they needed clear, consistent, and audience-resonant naming guidelines.

The goal was to create a naming framework that worked across job seeker and employer audiences, reinforced brand trust, and aligned with the company’s strategic vision.

Approach

Assessed product name options using metrics like:

Results were analyzed to uncover patterns in how AI experience, product clarity, and brand alignment influenced preferences. The findings were synthesized into actionable insights supported by CX research expertise and in-house linguistics knowledge.

Output

A comprehensive, data-backed set of AI product naming guidelines covering:

  • How to balance clarity and innovation in product names
  • When and how to reference AI without alienating users
  • Strategies for consistency across audiences and products
  • Guidance to avoid implying AI replaces humans

Impact

  • Turned a traditionally subjective process into a scalable, objective naming strategy.
  • Provided actionable guidance still in use by client teams months later in product naming and go-to-market planning.
  • Strengthened brand alignment and customer trust across diverse audiences.
  • Positioned the client’s AI products as credible, consistent, and contextually relevant in a competitive landscape.

Photo by Element5 Digital: https://www.pexels.com/photo/gray-steel-file-cabinet-1370294/

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