**Calculate the Desirability Score:**
Use the responses from the attached CSV to calculate the Desirability score using the following formulas:
- **Impressions Score** = (count of positive impressions selected in **"[Column with impression selections]"**) divided by (count of all impressions selected in **"[Column with impression selections]"**)
- **Likelihood Score** = (sum of all Likert ratings in **"[Column with likelihood ratings]"**) divided by (number of responses) ÷ 5
- **Desirability Score** = average of the Impressions Score and Likelihood Score
Likert Ratings for Likelihood are coded as:
- Very Likely = 5
- Likely = 4
- Neutral = 3
- Unlikely = 2
- Very Unlikely = 1
After calculating the Desirability score, report where it lands on the following scale:
- **Very Good** = above 90%
- **Good** = 70–89%
- **Average** = 50–69%
- **Poor** = 30–49%
- **Very Poor** = 0–29%
Next, analyze the responses in the column **"[Column with qualitative explanations]"** in the CSV to identify common themes and provide clear, actionable suggestions for how the Desirability score could be improved.
📊 Metric Calculations
Impressions Score = 88.8%
(Most impressions selected were positive ones: Innovative, Joyful, Helpful, Simple)
Likelihood Score = 81.2%
(Most participants leaned toward Likely or Very Likely to use the product)
Desirability Score = 85.0%
Scale Placement: ✅ Good (70–89%)
💬 Common Themes in Explanations (Section 3)
From participant explanations, the most frequent themes and words included:
Event-related context (mentions of “event”) → suggests users see it as tied to event use cases
Helpful / Help (12+ mentions) → seen as practically useful
Easy / Simple (9 mentions each) → participants value clarity and ease of use
Innovative (6 mentions) → some recognized novelty or uniqueness
Outfit / Page references (smaller cluster) → suggests visual or shopping-related expectations
🔧 Suggestions to Improve Desirability
Emphasize Ease and Clarity
Highlight “easy” and “simple” aspects more explicitly in messaging and onboarding.
Reduce any complexity that could cause hesitation.
Strengthen Perceived Usefulness
Lean into “helpful” scenarios in product copy and walkthroughs.
Tie features more directly to real-world use cases like events or planning.
Differentiate with Innovation
Users notice innovation, but mentions were fewer than “helpful” or “simple.”
Showcase unique elements more clearly to stand out from alternatives.
Address Uncertainty
A few responses hinted at vagueness (“seems,” “something”)—reduce ambiguity with concrete examples of what users can achieve.
✅ Overall, the product is already perceived as helpful, simple, and likely to be used, but to move the score from Good → Very Good, focus on sharpening clarity, showcasing innovation, and reducing uncertainty in how the product is presented.