For any product or brand typed, CEP Finder runs a five-stage analysis process. Because each stage is seperated, the results go far beyond simple keyword lists delivering deep, context-driven insights.
1.Background research
2.Extraction of product anchors and categories
3.Deep-dive into consumer contexts
4.CEP extraction and Nano Intent generation
5.KBF (Key Buying Factor) extraction
Since each step builds on the output of the previous result, we recommend waiting until the full analysis is complete without interruption to receive the most comprehensive and accurate report.
If the initial analysis doesn’t surface enough CEPs to fully capture your target insights, click the “+Expand CEP ” card at the end of the results grid to expand the scope of analysis.
With a single click, the AI picks up where it left off retaining the full context of the existing analysis and generating additional CEPs on top of it. All previously identified CEPs are preserved, allowing you to expand your analysis without losing any of the original context.
Contextual Search Insights are the detailed analysis displayed when you click on a CEP card in the results view.
It consists of three components:
- Nano intent and Key Buying Factors
A clear summary of what consumers are actually looking for within the selected CEP, and the criteria they use when choosing a product. - Related Keywords & SERP History
Related keyword list consists of keywords for which AI Overview (AIO) responses have been provided in contexts similar to the selected CEP.Clicking a keyword lets you view the corresponding Google Search results page (SERP), including any AI Overview. Previously collected data for the same keyword can be reviewed chronologically under SERP History. - AI Search Query Examples
Based on the CEP and KBF, the tool automatically generates example prompts that consumers are likely to ask AI search engines.
Type the name of the product, brand, or item you want to analyze.
CEP Finder is an AI-powered feature that deeply investigates and analyzes the underlying contexts and motivations behind when and why consumers recall and consider a specific product or category. Rather than simply listing what users are searching for, it delivers a comprehensive view that includes consumers’ real pain points, commonly used search keywords, and even example prompts that consumers are likely to ask AI.
Analysis results are organized around three core concepts:
- CEP (Category Entry Point)
The specific situation, context, or trigger that leads a consumer to think of or feel the need for a particular product or category.
Example: Not just “sneakers” as a category, but a concrete, real-life moment such as wanting waterproof, comfortable sneakers for a rainy-season commute represents a CEP. - Nano Intent
The specific goal or detail intent that varies from person to person, even within the same CEP situation. - KBF (Key Buying Factor)
The specific product attributes or conditions that become the deciding factor when a consumer narrows down their options and makes a final purchase decision within a given situation.
