SAN FRANCISCO--(BUSINESS WIRE)--Qordoba, the only platform enabling product development teams to manage the words in their applications, today announced a revolutionary new capability for scoring emotional tone in product and marketing content. Qordoba's patent-pending technology actually measures the emotional content of product and marketing copy to improve the user experience.
Qordoba's content scoring is based on Affect Detection, a computer science discipline that applies artificial intelligence and machine learning to understand the primary emotion conveyed by written text. The Qordoba platform utilizes natural language processing techniques to identify the emotion associated with a specific combination of words, allowing developers and product teams to create more effective user interfaces (UI).
Copy forms the foundation of brand experience, alongside design. How users perceive an app – for example, as bold, quirky, professional, or cute – depends primarily on the copy. However, the UX industry has largely overlooked words. There are now hundreds of tools on the market for user experience management and design, ranging from design and usability feedback to event tracking and user analytics. However, the UX industry has largely overlooked words.
Only 28% of companies believe "our user experience is very good."1 The data2 shows that the words in applications have the most impact on user engagement, with 4x conversion differential on improving text. Yet companies report only 8% of iterations are spent on optimizing copy, with most companies agreeing that "it's not easy for us to optimize all the elements in our user experience."
According to Qordoba co-founder May Habib, "For many companies today, managing written copy in their applications is a mess. Final copy is developed in Google Docs or Sketch, copied into source code by engineers, who end up writing more copy on their own, and the final product lives across dozens sometimes hundreds of files. Copy is created by dozens, and in the enterprise, hundreds, of different authors, with no automated system to see if people are adhering to a company's brand voice or style. Some text is hard-coded into source code, where it becomes difficult to find and risky to update."
Content quality is also an issue. From simple issues such as spelling and grammar errors, to complex issues such as inappropriate emotional tone or divergence from official brand voice, managing the text part of an interface can be a minefield. Qordoba offers a managed interface layer, where product content is managed and measured in a central repository to improve the user experience and accelerate time to market. Different apps running on multiple channels stay consistent with new versions of interfaces across multiple sprints.
Habib added, "Interfaces matter. People can already customize and personalize content in CRM and email. Qordoba enables customization in software interfaces, apps and products. Our plan is to have a permanent spot in the tech stack used to manage all the text everywhere. GitHub is used to manage code — Jenkins is used to manage build and deployment — Qordoba is used to manage all of the words in the user experience."
The Qordoba Strings Intelligence Platform enables product teams to create compelling user experiences by managing all of the words in their products. Qordoba is the only machine-learning based solution which extracts text from strings in source code and makes every application's words accessible and measurable across platforms, teams, channels, and technologies. Companies like Postmates, VISA and Marriott use Qordoba to rapidly optimize and release new copy across product, marketing and customer support. Qordoba's platform integrates with over 100 development and marketing technologies, seamlessly fitting into developers' stacks and enabling agile strings management.
Qordoba manages over 2 billion words every day for customers including the NBA, GitHub, Sephora, and Conde Nast. Based in San Francisco, Qordoba is backed by Upfront Ventures and Rincon Venture Partners.