1. Study snapshot
Study name: momentum3
Core question: Would you buy this energy drink?
Primary method: Price Sensitivity assessment
Secondary read: Key Driver Analysis

2. Study parameters
Question card features
| Category | Features |
| --- | --- |
| image | Fixed reference image |
| title | Fixed reference title |
| price | 1.99; 2.49; 2.99; 3.49; 3.99; 4.49; 4.99 |
| description | Fixed reference description |

User features
| Category | Features |
| --- | --- |
| Age Years (width 10, start 18) | 18-27; 28-37; 38-47 |
| Gender | Male; Female |
| Energy Drink Consumption Frequency | Daily; Weekly; Monthly; Rarely |
| Primary Purchase Channel | Supermarket; Convenience store; Online; Gym |

3. How this study is used
Goal: The researcher uses this study to explore price sensitivity for an energy drink while holding other question card features constant. The output supports pricing strategy by identifying the revenue-maximizing price point within the tested range.
Typical launcher: Product team exploring energy drink pricing.
Industry or company context: Beverages / product development
Research stage: Early explanatory study
Why run this study now: The researcher uses this study to explore price sensitivity for an energy drink while holding other question card features constant. The output supports pricing strategy by identifying the revenue-maximizing price point within the tested range.
What the team gets: A clearer read on the tested decision and the audience patterns behind it.
Why this matters: It reduces uncertainty around the exact decision being tested before the team spends more on execution or a larger follow-up study.
Larger plan: The strongest next move is to add consumption frequency or brand familiarity measures if the next study needs to distinguish trial vs habitual buyers at different price levels.

4. Results summary
- Participants: 334
- Yes rate: 56.59% (189 yes / 145 no)
- Model used: Ridge Regression (70.1% accuracy)
- optimal price: $3.6 (this value represents the tested price that maximized revenue per product view in this study, not necessarily long-run market revenue)
- Strongest positive signals: price = 2.49, price = 3.49, price = 2.99
- Strongest negative signals: price = 4.49, price = 3.99

5. Value for the launcher
In this study, Yes responses to "Would you buy this energy drink?" were more common among respondents with price = 2.49, price = 3.49, and price = 2.99, while No responses were more common among respondents with price = 4.49 and price = 3.99. The optimal price is about $3.6, representing the tested price that maximized revenue per product view in this study, not necessarily long-run market revenue. This gives the team a grounded starting point for follow-up tests with the segments and card features that showed stronger or weaker Yes rates here. The next study could test that by adding consumption frequency or brand familiarity measures if the next study needs to distinguish trial vs habitual buyers at different price levels and checking whether similar Yes-rate patterns persist when another factor varies.

6. What to do next
- Use now: Use $3.6 as the current price anchor suggested by this study, while validating its effect on Yes rates in broader tests.
- Next test: Add consumption frequency or brand familiarity measures if the next study needs to distinguish trial vs habitual buyers at different price levels.
- Do not over-read: These insights apply to this study's design, sample, and question framing. The optimal price of $3.6 reflects the tested setup here, not guaranteed long-run market performance.
