Quantitative Research — Everything We Measure Becomes a Decision
With statistically significant, demonstrably representative numerical data, we deliver clear answers to "how much?", "at what rate?", and "by what margin?"
Overview
Quantitative research comes in when decisions need to be supported with measurable data. What is your brand's awareness in percentage terms? How has your customer satisfaction shifted in the past six months? Is a campaign's effect on awareness statistically significant? Clear answers to these kinds of questions are only possible through properly designed quantitative research.
At Arvensus, quantitative research is fielded across all 81 provinces using CATI, CAWI, CAPI, and face-to-face (F2F) methods. From sample design and question calibration to data cleaning and advanced analysis, we hold to scientific standards at every stage. When interpreting numerical results, we report not only "what happened" but also "what it means."
Techniques
The techniques we use most often within this methodological framework.
- 01
CATI (Computer-Assisted Telephone Interviewing)
Our standard method for quantitative projects that need fast reach across a wide geography. Our trained telephone team works on an interview flow with quality control applied at every stage.
- 02
CAWI (Online Surveys)
For digitally reachable audiences and longer surveys. Fielded through our panel partners and the client's own database; runs on responsive, mobile-first designs.
- 03
CAPI (Tablet-Assisted Face-to-Face Interviewing)
Tablet-assisted face-to-face interviews conducted in the home, on the street, or at the point of sale. Preferred for both rich data capture and geographic representativeness.
- 04
Face-to-Face (F2F) Interviews
The classic face-to-face interview, preferred for sensitive topics, deep scales, and technical products. Our field team is trained to ESOMAR standards.
- 05
Conjoint Analysis
An advanced technique that models consumer trade-off decisions. Reveals the optimal product configuration on the price–feature balance, market-share simulations, and elasticities.
- 06
Segmentation and Clustering
Statistical models that divide the consumer base into segments based on behavior, attitude, need, or value. Forms the foundation for strategy, product, and communication decisions.
- 07
Regression and Driver Analysis
Reveals which factors drive outcome variables such as satisfaction, loyalty, or preference. Used to forecast which investment will produce which effect.
- 08
Van Westendorp / Gabor-Granger Pricing
Proven techniques for measuring perceived price thresholds and price sensitivity. A core input for launch and price-optimization decisions.
- 09
MaxDiff Analysis
For prioritizing among many features or messages. Provides a statistically reliable answer to "which message/feature matters most?"
What does this methodology deliver?
- Statistically significant, high-evidence results — confidently presented to boards, investors, and regulators.
- Large samples enable segment and geography comparisons — "Türkiye-wide," "Istanbul vs Anatolia," "18-34 vs 35+" cuts are possible.
- Trend tracking is feasible — applying the same instrument over time lets you read change in numbers.
- Evidence-based investment decisions — which message, product, or price level delivers the highest return can be modeled.
- Action-oriented analysis — numbers move beyond charts to answer "what should we do?"