Fix Low Fact Density: Add Statistics to Content
Your page has too few concrete facts, numbers, and statistics for its length. Vague, claim-heavy prose is harder for Google to trust and for AI answer engines to extract and cite. The fix is to replace generic assertions with specific quantified facts, tie each to a named and dated source, and mark them up so they survive extraction by ChatGPT, Perplexity, and Google AI Overviews.
What this means
"Fact density" is a rough measure of how many verifiable, concrete data points a page contains per unit of text: numbers, percentages, dates, measurements, named entities, and cited findings. The audit flagged low_fact_density and no_statistics because your content leans on generalized claims ("many users prefer," "significantly faster," "a growing number of businesses") instead of specific figures ("38% of users," "loads in 1.2s," "up from 12,000 last year").
This is not about stuffing arbitrary numbers into the page. It means your content makes assertions it never backs with evidence. A page can be well written and still be almost entirely unfalsifiable opinion. Both search engines and large language models treat unsupported claims as low signal, because there is nothing concrete to verify, index as a fact, or lift into an answer.
The no_statistics sub-signal specifically means the crawler found no quantitative data points (percentages, counts, currency figures, dated measurements) in the main content at all. That is common on thin service pages, generic "ultimate guide" intros, and AI-generated drafts that were never fact-checked or sourced.
Why it matters
For classic Google ranking, fact density is a proxy for the Experience and Trust parts of E-E-A-T. Google's Search Quality Rater Guidelines direct raters to reward content that shows first-hand knowledge and supports its claims, and specific numbers, tested results, and named sources are exactly what separates a genuine expert page from generic filler. Fact-dense pages also tend to be more link-worthy: original data and statistics attract referring domains that opinion pieces rarely earn, and links remain a core ranking factor. A single well-cited statistic can become the reason other sites link to you.
For AI answer engines the effect is more direct. ChatGPT, Perplexity, and Google AI Overviews build answers by pulling out discrete, verifiable statements and citing where they came from. A specific, sourced statistic ("median LCP dropped from 3.1s to 1.9s after the migration") is a clean, liftable unit an engine can quote and attribute to you. A vague sentence ("performance improved a lot") is not liftable, so it earns no citation. Perplexity in particular shows several numbered inline citations per answer and favors pages that read like sourced reference material. If your page supplied the number, you become the cited source.
The two channels compound. Pages that get cited by AI engines and linked by other sites accumulate authority, which feeds back into classic rankings. Low fact density quietly caps both at once.
How to fix it
- 1
Find the unsupported claims, then quantify them
Read the page and highlight every sentence a skeptic could challenge: "faster," "popular," "most," "growing," "affordable," "better." Each highlight is a place a number belongs. Replace the adjective with a figure. "Popular" becomes "used by 4 of the top 10 vendors"; "faster" becomes "cuts build time from 90s to 22s." Aim for content where the core claims are verifiable, not for an arbitrary number-per-paragraph quota. Even three or four well-chosen, sourced statistics move a page from opinion to evidence.
- 2
Attach a named, dated source to every statistic
An unsourced number is only marginally more trustworthy than an adjective, and AI engines will not cite a stat they cannot attribute. For each figure, name the source and the year inline: "according to the 2026 Stack Overflow Developer Survey" or "in our own analysis of 1,200 audits (June 2026)." Link to the primary source, not a blog that re-quotes it. First-party data you collected yourself is the most valuable kind, because it is unique, hard to copy, and gives other sites a reason to cite you specifically.
- 3
Make the numbers machine-readable and scannable
Put key statistics where both humans and crawlers find them fast: in headings, bolded lead sentences, bulleted lists, and comparison tables rather than buried mid-paragraph. A
<table>of figures or a bulleted "by the numbers" block is trivial for an LLM to parse. Use real semantic markup (<table>,<ul>,<strong>), not styled<div>s. See the code example for a scannable table plus optional structured data that states what a headline number represents and where it came from. - 4
Never invent figures; verify them or describe the direction
Fabricated statistics are worse than none. They fail fact-checking, erode trust, and can get AI-generated pages demoted. If you do not have a hard number, state the direction honestly ("response times dropped after we enabled HTTP/2") instead of inventing "73% faster." Where well-established norms exist, cite the norm as a benchmark. Google treats LCP under 2.5s, INP under 200ms, and TTFB under roughly 800ms as good, so you can compare your real result against those. Verifiable and modest beats impressive and fake every time.
- 5
Add a first-party data point if you can
The highest-leverage fix is to publish something only you can: results from your own tests, a survey of your users, aggregated numbers from your product, or a benchmark you ran. Pages built around original data tend to attract more backlinks and AI citations than commentary. Even a small, honest dataset ("across 300 sites we audited, 41% failed the mobile viewport check") becomes a magnet other writers quote and link, which feeds both rankings and AI visibility.
- 6
Re-audit and keep figures current
After editing, re-run the audit to confirm
low_fact_densityandno_statisticsclear. Then set a reminder to revisit stale numbers. A 2023 survey cited in 2026 signals neglect to readers and to freshness signals, and outdated figures get dropped from AI answers in favor of current ones. Pair this with a visible last-updated date so engines can see the data is maintained.
Example
<!-- 1. Human- and machine-readable 'by the numbers' block -->
<table>
<caption>Core Web Vitals before vs. after HTTP/2 migration</caption>
<thead>
<tr><th>Metric</th><th>Before</th><th>After</th><th>Google "good" threshold</th></tr>
</thead>
<tbody>
<tr><td>LCP</td><td>3.1s</td><td><strong>1.9s</strong></td><td>< 2.5s</td></tr>
<tr><td>INP</td><td>310ms</td><td><strong>140ms</strong></td><td>< 200ms</td></tr>
<tr><td>TTFB</td><td>1.2s</td><td><strong>0.6s</strong></td><td>< 800ms</td></tr>
</tbody>
</table>
<p>Source: our own field data across 1,200 page loads, June 2026.</p>
<!-- 2. Optional structured data for a headline claim + citation -->
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Claim",
"text": "Migrating to HTTP/2 reduced median LCP from 3.1s to 1.9s.",
"citation": {
"@type": "CreativeWork",
"name": "HTTP/2 migration field data",
"datePublished": "2026-06-01",
"author": { "@type": "Organization", "name": "Your Company" }
}
}
</script>Make a headline statistic scannable for humans and extractable by crawlers with a real table. The optional Claim JSON-LD states what the number is and where it came from; it earns no rich result in Search, but gives AI crawlers explicit structure. Use your own verified data.
Platform-specific steps
Edit the post in the block editor and use native blocks for your data: the Table block for comparisons, List blocks for a "by the numbers" section, and bold the key figure in each. This is a content edit, so Yoast and Rank Math will not fix it for you, though Rank Math's Content AI and Yoast's analysis panels nudge you toward adding specifics. For a headline claim, paste the JSON-LD from the code example into a Custom HTML block, or use Rank Math's schema tools. Link statistics to primary sources with normal editor links.
On product and collection pages, replace vague marketing copy in the description with concrete specs and figures: dimensions, capacity, tested battery life, share of customers who reorder. Use the rich-text editor's table and list tools, or add a metafield-driven specs section in your theme. For blog articles, edit in the online store blog editor and add sourced statistics the same way. Keep numbers current when you update products.
Open the page in the Wix Editor and add a Table element or a bulleted text block for your key figures instead of leaving them in a paragraph. Bold the headline number. Wix does not expose raw JSON-LD easily, but you can add custom schema via Settings > Custom Code, scoped to the specific page and placed in the head. The core fix here is editorial: swap adjectives for sourced numbers.
Edit the page and use a Markdown or Code block for a clean data table, or Text blocks with bold figures plus a List block for a stats summary. Link each statistic to its primary source. To add Claim or citation JSON-LD, use Settings > Advanced > Code Injection at the page-level header (Business plan and above). As elsewhere, the substance is the edit: real numbers with named, dated sources.
Use semantic markup so crawlers and LLMs parse figures cleanly: <table> for comparisons, <ul>/<ol> for stat lists, <strong> for headline numbers, and <time datetime="..."> for dates. Inject the Claim JSON-LD via a <script type="application/ld+json"> tag; in Next.js, render it in the head or through a structured-data component. Keep first-party data in a typed data file so figures are easy to update in one place and stay consistent across the site.
Frequently asked
There is no fixed quota, and stuffing numbers to hit a target backfires. The real test is whether your significant claims are backed by evidence. A focused 800-word page might need only three or four well-sourced figures; a 3,000-word guide needs proportionally more. Prioritize quality and relevance. One specific, sourced, first-party statistic beats ten generic ones pulled from a listicle.
Yes, and it is one of the most direct levers you have. These engines build answers by extracting discrete, verifiable statements and citing where they came from. A specific sourced statistic is a clean unit an engine can quote and attribute to you; a vague claim is not liftable and earns no citation. Perplexity in particular shows several numbered citations per answer and favors pages that read like sourced reference material, so being the page that supplied the number is how you get cited.
Only if you dump numbers without context. State the figure, then explain what it means and why it matters in one sentence: "Enabling Brotli cut our average page weight by 21%, which pushed mobile LCP under the 2.5s threshold Google treats as good." That reads as expertise, not filler. The goal is claims backed by evidence, not a spreadsheet in prose form.
Start with primary sources: official industry surveys, government and standards-body data, first-party numbers from your own analytics or product, and reputable research reports. Always link the original source rather than a blog that re-quotes it, and include the year. Best of all is data you generate yourself, such as a small test, benchmark, or user survey, because it is unique, hard to copy, and gives other sites a reason to cite you.
There is no ranking signal literally named "fact density." But it is a strong proxy for signals Google does use: the Experience and Trust parts of E-E-A-T, and link-worthiness. The Search Quality Rater Guidelines reward content that supports its claims and shows first-hand knowledge, and data-rich pages reliably attract more referring domains than opinion pieces. So while no single metric moves, improving fact density strengthens several signals that genuinely influence rankings.
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