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Mixed Methods Research

Get the “why” and the “how many”—so you can decide with confidence. Mixed methods research blends qualitative depth (interviews, observation) with quantitative certainty (surveys, modeling). It’s the fastest way to move from learning to proof to action. We combine human insight with data science to reduce risk and sharpen strategy.

Meeting

What it's best for

Mixed methods combines qualitative insight and quantitative evidence so you can answer both “why” and “how many.”It’s ideal when decisions require speed, clarity, and confidence across stakeholders.

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What it’s best for

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  • Understanding customer motivations (qual) and proving how widespread they are (quant)

  • Building and validating segments and targeting strategies

  • Testing concepts/messages deeply, then quantifying what will win in market

  • Diagnosing performance issues (what’s happening + why it’s happening)

  • Turning exploration into decision-ready recommendations backed by evidence

 

Typical outputs

 

  • A unified story: themes + numbers + what to do next

  • Segments with both human insight and statistical proof

  • Clear visuals (charts + themes) and practical recommendations

 

When you should choose mixed methods research? 

Choose mixed methods when the decision is high-stakes, the market is complex, or you need stakeholder buy-in using both stories and stats.

What Ascendancy does differently

Ascendancy specializes in mixed methods research that connects real customer stories to decision-grade data. We design studies where qualitative insight shapes the right questions, then quantitative results prove what’s true at scale. With our data science-led approach, we uncover segments, drivers, and scenarios—then turn them into an action plan for positioning, pricing, product, and go-to-market.

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  • We design studies where qual and quant work together, not as separate reports

  • We translate customer language into measurable variables and tested hypotheses

  • We use analytics to reveal drivers, segments, and scenarios—then connect them to strategy

  • We deliver an action roadmap (who to target, what to say, what to offer, where to focus)

 

​Great fit for

 

  • New product launches and rebrands

  • Competitive categories with switching and price pressure

  • Multi-island or diaspora expansion (different contexts, same brand)

Image by Olav Ahrens Røtne
Image by Sean Pollock

Top 10 types of quantitative research marketers use

  1. Exploratory Sequential (Qual → Quant)
    Explore motivations with interviews/groups, then validate at scale with a survey.

  2. Explanatory Sequential (Quant → Qual)
    Start with a survey to spot patterns, then use interviews to explain why they occurred.

  3. Concurrent Triangulation (Qual + Quant at the same time)
    Run both simultaneously to cross-validate and strengthen confidence in findings.

  4. Segmentation Build + Validate
    Qual to define needs and language; quant to statistically build segments and size them.

  5. Concept Development + Concept Test
    Co-create/refine concepts qualitatively, then quantify appeal, uniqueness, and purchase intent.

  6. Message Framework + Message Testing
    Develop messaging from real customer language, then test which claims and tones convert best.

  7. Customer Journey Mapping + Journey Quantification
    Map the journey qualitatively, then quantify drop-off points, drivers, and moments that matter.

  8. Pricing Discovery + Pricing Measurement
    Qual to understand value perceptions and price barriers; quant to measure willingness-to-pay ranges.

  9. Shopper Observation + Shopper Survey
    Observe behavior in-store/online, then quantify frequency, triggers, and channel preferences.

  10. Innovation Funnel Research
    Qual to generate ideas and uncover needs, then quant to score/prioritize what to build and launch.

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