Svarstester

Svarstester is a term used in Norwegian and Swedish IT contexts to describe the practice and role of testing the answers provided by an information system, such as a chatbot, virtual assistant, or a knowledge-base-driven customer service tool. The aim is to verify that the system’s responses are accurate, relevant, complete, consistent, and appropriately toned for the user.

The work may be performed by QA engineers, content specialists, or user experience researchers and can involve both manual and automated methods. Test sets typically include user questions and expected or acceptable answers, structured conversational scenarios, and negative tests that probe ambiguous or adversarial inputs. Multilingual and multi-domain cases are common in environments serving diverse user bases.

Key metrics used in svarstester include correctness, relevance, completeness, and consistency of responses, as well as deflection rate, which measures how often the system resolves inquiries without escalation, and user satisfaction, often gathered from surveys or simulated feedback. Automated tests may exercise natural language understanding components, intent recognition, and knowledge-base lookups, while manual reviews assess clarity, tone, and usefulness of the replies.

Workflow generally follows mapping requirements to expected outputs, maintaining and executing test scripts, logging defects, and iterating on data, prompts, and system behavior. Integrated into release cycles, svarstester supports continual improvement of conversational interfaces and knowledge management.

Challenges include language ambiguity, context carryover across turns, evolving knowledge bases, multilingual support, and the subjectivity of perceived helpfulness. See also: software testing, chatbot testing, natural language understanding evaluation, and conversation design.