<p>Now that the standout virtual-character concepts have been refined through qualitative feedback, Phoebe and Maikel jump into the <em>numbers phase</em>—where data, not gut feeling, decides which designs go live.</p><p><strong>Key take-aways</strong></p><p><strong>- From shortlist to scorecard</strong> – Why you first narrow to a small set of high-potential designs, then pit them head-to-head in structured tests rather than betting the budget on a boardroom favorite.</p><p><strong>- Quant 101 for character design</strong> – Crafting perception surveys in tools like Qualtrics, defining traits (trust, energy, professionalism) in testable language, and keeping sessions under 20 minutes so attention—and data quality—stay high.</p><p><strong>- Participants that matter</strong> – Sourcing 100-300 respondents <em>who match the target market</em>, building demographic diversity, and spotting red-flag responses (five-minute completions, straight-line scores) before they skew results.</p><p><strong>- Hybrid methods</strong> – Using “think-aloud” moderated surveys with a sub-sample to capture the <em>why</em> behind the sliders, linking qualitative nuance to quantitative scale.</p><p><strong>- Pilot before you plunge</strong> – Quick internal dry-runs expose confusing wording, broken sliders, or survey fatigue <em>before</em> hundreds of users see it.</p><p><strong>- Making the data talk</strong> – Cleaning noisy responses, running correlation and subgroup analysis (e.g., slower speech → higher trust among 60-plus drivers), and translating findings into concrete visual, vocal, or personality tweaks.</p><p><strong>- Knowledge that compounds</strong> – Each quantified insight becomes part of a growing, cross-project playbook that lets future teams start smarter and align faster.</p><p><br></p><p>If Episode 3 covered <em>inspiration</em> and Episode 4 covered <em>refinement</em>, Episode 5 shows how to turn user perception into hard evidence—so the AI character that finally ships is the one your audience actually wants.</p>
