Case Study - Tailoring Lottery Campaigns to Swiss Values through MaxDiff
Case Study - Tailoring Lottery Campaigns to Swiss Values through MaxDiff
The challenge
A lottery marketing team needed to identify the true motivations that drive participation across age groups in Switzerland.
The solution
A MaxDiff study measured 20 motivations among players and compared younger adults (18-44) with seniors (65+) to inform segmented communication.
Study impact: +13% ticket sales
Ranking of Lottery Motivations
Bubble Chart - Perception Map
ⓘ Understanding this chartThis chart shows how incentives relate to each other in consumers' minds. Bubble size represents overall preference. Items close together are perceived as similar and may substitute each other. Items further apart tend to be complementary.
Bubbles combine preference strength (size) and strategic positioning (x/y) to identify themes that are both high-impact and differentiating.
ⓘ How to read this chartThis chart identifies the optimal combination of incentives. The first item is the most preferred individually. Each additional item is selected because it adds the highest incremental preference when combined with the previous ones. Bars show the incremental contribution of each item, while the line represents the cumulative preference generated by the mix.
Recommended mix: financial security, travel, family joy, and loved-ones support to maximize campaign resonance across generations.
ℹ️About the real study behind this case
This case study was derived from a real study conducted by MaxDiffPro. It has been anonymized for confidentiality: the tested options and results shown here do not correspond exactly to reality. The actual study had the following characteristics:
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Country
🎰
Items tested
20
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Respondents
~150
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Timeline
4–5 days
The timeline depends on the complexity of the study and the target audience.
Run a Similar Study for Your Product
MaxDiff helps teams identify which messages, features, or ideas truly resonate with customers.
Typical study: 15–25 items tested · 150–300 respondents · Results in 3–5 days
