What is a Quantitative Study?

Overview

A Quantitative Study helps you collect structured feedback through surveys using predefined question formats. It’s ideal for validating concepts, measuring consumer preferences and generating data-backed insights at scale.

Whether you're testing product ideas, brand messages, advertisements or packaging designs, Quantitative Studies are built for fast setup and robust analysis making them your go-to for confident, data-driven decision-making.

Key Features You Can Use

1. Survey Building & Customization

Block-based setup: Build surveys using predefined question types like multiple choice, dropdown, rating scales and more.
Logic flows: Guide participants based on their responses using skip logic and branching conditions.
Piping: Automatically insert a participant’s previous answer into follow-up questions for a more personalized experience.
Bulk import of choices: Instantly paste long lists of answer options directly into question blocks.

2. Localization & Accessibility

Localization: Translate system UI (like buttons ) into your preferred language.
Accessibility-ready design: Optimized for all users, across devices and accessibility needs.

3. Media Support

Rich media embedding: Add images or videos to provide context or enhance clarity (e.g., show a new product or ad).

4. Advanced Setup Controls

Randomization & rotation: Shuffle question blocks or answer choices to minimize response bias.
Previews & testing: Preview the entire survey before going live to ensure logic and flow work as expected.
Auto-save: Your progress is saved automatically as you build.

5. Technology & Performance

Lightweight delivery: Surveys load quickly across devices and locations.
Cross-device compatibility: Works smoothly on mobile, desktop and all major browsers.
Secure data collection: Designed with compliance and privacy standards in mind.

When to Use a Quantitative Study

Use a Quantitative Study when you need:

Clear, measurable feedback from a large sample
Comparative data across product concepts, marketing messages or packaging designs
Statistical confidence to support consumer, brand or campaign decisions

Best Practices

Define your research objective clearly: Understand what you want to learn - awareness, preference, purchase intent, etc.
Use structured question formats: Include MCQs, rating scales and ranking questions to ensure standardized, comparable data.
Keep the survey concise: Respect the respondent’s time by keeping it focused and under 10 minutes where possible.
Ensure sample quality: Use screening to reach your target demographics accurately.
Randomize answer options: Avoid bias by rotating brand names or choices where relevant.
Test before launch: Always preview the full flow to catch errors or unclear wording.
Use clear and neutral language: Avoid leading questions that might influence answers.

Common Use Cases

Concept testing: Measure consumer appeal, uniqueness and purchase intent for new product or campaign ideas.
Brand tracking: Monitor brand awareness, perception and loyalty over time.
Ad testing: Evaluate effectiveness of ad creatives, taglines or storyboards before launching.
Pricing research: Understand how consumers respond to different price points to find the most acceptable and profitable range.
Usage & attitude studies: Understand consumer habits, preferences and needs within a category.
Customer satisfaction: Collect structured feedback from users of your product or service.