Save Thousands on User Testing with AI-Powered UX Analysis

User testing is invaluable for understanding how real people interact with your product, uncovering unexpected mental models, and measuring success metrics. But it's also expensive and time-consuming. A single round of professional user testing typically costs between $3,000 and $10,000, requires weeks of scheduling and recruiting, and often reveals issues that expert heuristic analysis would have caught immediately.

The Problem with Testing Too Early

Here's the problem: if you run user testing on a flow with obvious usability issues—unclear button labels, missing error states, confusing navigation—you'll spend thousands of dollars watching users struggle with problems you could have fixed beforehand. Your testing sessions become diagnostic rather than validating, and you waste your budget on issues that didn't require real users to identify.

The Two-Phase Approach

Phase 1: Rapid Heuristic Analysis with Krux AI

First, use Krux AI to conduct rapid heuristic analysis:

• Upload your flow
• Get detailed feedback on usability issues, missing states, unclear copy, and flow logic problems
• Fix the obvious issues that Krux identifies
• Cost: Under $50, takes minutes instead of weeks
• Result: Eliminate 60-80% of usability problems before you ever recruit a single test participant

Phase 2: Strategic User Testing

Then, with a polished flow that has passed heuristic validation, invest your user testing budget strategically. Use real users to answer questions AI cannot:

• How do people perceive the value of this feature?
• Which variation leads to better task completion?
• Where do users get emotionally frustrated versus merely confused?
• What mental models do they bring that we hadn't considered?

This is where user testing truly shines, and now you're not wasting sessions on issues you should have caught earlier.

Teams that adopt this approach report saving 60-80% on total testing costs while actually improving their product quality. You run more iteration cycles with the same budget, catch issues earlier when they're cheaper to fix, and make better use of user testing by focusing it on strategic validation rather than basic usability diagnosis.