MARKETING

Concept Test Analysis

Go beyond average scores to the emotional drivers behind concept preference.

Choosing the right product concept, packaging, advertisement, or innovation requires more than simply comparing average survey scores. Steeped AI transforms concept testing research into statistically validated business intelligence by combining survey results with open-ended feedback, demographic data, behavioral segments, and qualitative responses.

Automatically identify the concepts that resonate most with different audiences, uncover the emotional drivers behind preferences, quantify purchase motivations, and discover hidden market segments that traditional reporting overlooks. Researchers can rapidly generate research-grade reports backed by statistical significance, predictive metrics, and exact citations to support confident product launch decisions.

1.winning_concept

● High Insight Urgency

AI Score Highlight: This concept has findings in the upper ranges of relevance score.

Finding Highlight: 57% of "Gen Z" chose "concept B"

Highlight Reason: Concept B wins decisively among younger, urban buyers, driven by its sustainability claim, a segment traditional average scores hid.

More Value Findings:

• 57% of "Gen Z" segment chose "concept B"

• 42% of "sustainability" driver = "top-2 box"

• 19% of "price-first" buyers chose "concept A"

AI Topic Mapping

Use Steeped AI's AI topic mapping to turn open-ended concept feedback into measurable concepts like emotional appeal, purchase motivation, and concept confusion. Quantify the drivers behind a preference by segment, so you understand why a concept wins, not just that it scored higher.

Statistical Significance Testing

Steeped AI's automated significance testing confirms that a winning concept truly beats the alternatives rather than leading by chance. A university-grade, 3-part framework keeps every launch recommendation defensible, so you greenlight a concept on evidence, not a narrow average.

Data Preparation

Use Steeped AI's data preparation to combine survey exports, open-end coding, and demographic files into one clean dataset. When concept labels and scales differ across waves and vendors, Steeped AI reconciles them first, so cross-concept comparisons compare like with like.

Merged survey exports with the open-end coding file

Labels "A", "Concept A" and "conceptA" were unified

Rescaled a 1-7 preference field onto the 0-100 scale

Removed column "panel_raw" because 82% were blank

Duplicate respondents across waves were merged

generating new dataset

NEW DATA

Customer Journey Mapping

Apply Steeped AI's journey mapping to trace how a concept moves someone from first exposure to preference to stated intent. See which element converts interest into intent, so packaging and messaging emphasize the moment that actually drives purchase.

The insights are already in your data.

Ask your data anything. Get real findings ranked by impact, with AI reports your team can present and share on the spot.