Written by
Lara Rice
Product Manager for Ascribe at Voxco
In the age of AI, analyzing open-ended survey responses is more efficient than ever. While general AI models like ChatGPT can process text, they lack the precision, structure, and market research (MR) expertise needed for accurate coding and categorization. Ascribe Coder stands out as the superior choice for researchers, offering a purpose-built solution designed specifically for open-end analysis. Here’s why:
Purpose-Built for Market Research & Survey Analysis
Unlike ChatGPT, which is a general-purpose language model, Ascribe Coder is specifically designed to process, categorize, and analyze open-ended responses. It employs a proprietary method for extracting themes, refined over decades of market research experience. This specialization ensures that responses are coded meaningfully, aligning with industry expectations.
Consistent, Reliable, and Transparent Coding
One of the major drawbacks of ChatGPT is the potential for inconsistent responses due to its generative nature. Ascribe Coder, on the other hand, provides:
- Structured and reproducible coding, with clear parameters and guardrails to keep results focused on the topic.
- Transparency, in the process ensures applied codes stay linked to the original context and meaning within responses.
- Partially coded response reporting, making it easy to review and refine results.
Customizable Codebooks
Ascribe Coder gives users complete control over the codebook or code frame. Researchers can:
- Automatically create descriptive, thematic codebooks tailored to their projects and refine as needed.
- Create code frames with hierarchical and multi-level netting for detailed categorization.
- Save and reuse codebooks for ongoing or similar projects
This level of customization is not possible with ChatGPT, which lacks structured taxonomy management.
Scalability & Efficiency with AI Flexibility
Market researchers often handle large volumes of text data. Sometimes they prefer to use AI assistance for coding, and sometimes they prefer, or are required, not to use AI. Ascribe Coder is built for scalability and flexibility. It:
- Handles large volumes of text with fully automated, fully manual, or hybrid processing to fit user or project needs.
- Offers both generative and non-generative processing modes to suit different analysis needs
In contrast, ChatGPT processes text one query at a time, making it inefficient for large-scale analysis.
Seamless Integration with Market Research Workflows
Ascribe Coder fits seamlessly into research ecosystems, offering:
- Direct integration with survey platforms for smoother data processing.
- Access to Ascribe Coder’s project management system for improved workflow visibility and efficiency.
- Access to MR deliverables when needed for further analysis and reporting.
- Built-in visualization tools, delivering instant insights.
- ASK Ascribe, a tool allowing users to ask questions of the analysis and immediately receive insights, summaries and reports.
Human Oversight of Coding for AI Accuracy & Control
AI should enhance, not replace, human expertise. Ascribe Coder embraces human oversight, enabling researchers to:
- Supervise and customize AI-generated results and make adjustments as needed.
- Use integrated power tools to oversee, refine, and ensure quality control of AI coding.
ChatGPT, in contrast, operates autonomously, making it harder to systematically validate results.
Language Agnostic
Global research often requires analysis of multilingual responses. Ascribe Coder is language agnostic, meaning:
- It can create codebooks and present results in any language, regardless of the input language.
ChatGPT struggles with structured multilingual coding and lacks built-in tools for cross-language consistency.
Exceptional Customer Training and Support
Often times researchers need help with a complex project, training a new team member, or exporting results in a new format. Ascribe’s Customer Training and Support teams have worked for 20+ years in the business and are there to help when needed, ensuring customers receive the results they need from their data to deliver their business objectives. This makes Ascribe a true research companion, far beyond what ChatGPT can offer.
Conclusion
While ChatGPT is a powerful AI model, it was never designed for market research and survey coding. Ascribe Coder delivers structured, transparent, scalable, and customizable text analysis tailored to researchers’ needs. Its proprietary AI, seamless integrations and interactive tools all with human oversight, make it the superior choice for analyzing open-ended responses.
For researchers who demand accuracy, efficiency, and control, Ascribe Coder is the clear winner.