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- Original Research Signals
Original Research Signals
Detects phrases like 'our research', 'we found', 'survey of', and custom charts. Original research gets cited far more than derivative content.
Why It Matters for AI Visibility
How We Score It
How to Improve
- 1
Use first-person research language
Write "we analyzed 1,000 websites" instead of "an analysis of websites shows." The analyzer specifically detects phrases like "we found," "our research," "our data shows," and "we surveyed." Each unique phrase counts toward your score, so vary your research language across the page.
- 2
Add a case study section
The phrase "case study" is a detected signal. Document a real customer outcome, an internal experiment, or a before-and-after comparison with specific numbers. A single case study section adds both a research phrase and substantive original content that AI engines can cite.
- 3
Include data visualizations using chart libraries
The analyzer detects chart HTML elements from Chart.js, D3, Highcharts, Recharts, and Plotly. Adding an interactive chart alongside your research data contributes significantly to the score. Static images of charts do not count -- you need actual chart library elements in the HTML.
- 4
Describe your methodology explicitly
Phrases like "we interviewed 50 customers," "we benchmarked 200 sites," and "we tracked results over 6 months" each count as unique research signals. Describing how you gathered data strengthens both your score and the credibility AI engines assign to your findings.
- 5
Label your research as original
Use ownership signals like "our proprietary data," "original research," and "our original analysis." These phrases are explicitly detected by the analyzer and help distinguish your content from pages that merely reference others' work.
Before & After
Studies show that content marketing generates 3x more leads than traditional marketing. According to industry reports, companies that blog get 67% more leads.
We analyzed 500 B2B companies over 12 months and found that content marketing generated 3.2x more leads. Our data shows that companies publishing weekly saw 67% more leads. We surveyed 200 marketing directors to confirm these findings. [Chart.js bar graph showing lead generation by publishing frequency]
Code Examples
Chart elements detected by the analyzer
<!-- Chart.js canvas (detected) -->
<canvas id="research-chart" width="600" height="400"></canvas>
<!-- D3 visualization (detected by class pattern) -->
<div class="d3-chart" id="findings-visualization"></div>
<!-- Recharts container (detected by class pattern) -->
<div class="recharts-wrapper"></div>Frequently Asked Questions
Does citing others' research count toward this score?
No. This factor specifically detects first-person research language like "we found" and "our data." Citing external studies is evaluated by different factors (External Citations and Source Attribution). This factor rewards content where you are the primary source.
Can I improve my score by adding research phrases without actual research?
The analyzer detects phrase patterns, so the phrases would technically count. However, AI engines evaluate actual content quality when deciding what to cite. Genuine research with supporting data will always outperform keyword-stuffed content. The phrases are meant to reflect real research, not game the score.
Do embedded images of charts count, or must they be interactive chart elements?
Only HTML chart elements are detected -- Canvas elements, SVGs with chart-related classes, and elements from known chart libraries (Chart.js, D3, Highcharts, Plotly, Recharts). Static images of charts in `<img>` tags are not detected. You need actual chart library elements rendered in the HTML.
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