# Data-driven synthesis: Product feature `feature-nano-ai` (`/nano-ai`)

**Auto-generated:** 2026-04-02 (UTC) · **Script:** `v2/scripts/product-pages/generate-feature-page-data-synthesis.php`

**Registry `docs_dir`:** `docs/content/pages/product-pages/nano-ai`. Add human notes in `KEYWORD_DECISION.md`, FAQ outlines, and post-deploy checks. **FAQ SSOT:** `misc-faqs` + `faq-answers-optimized.json` per [PRODUCT_PAGE_FAQ_GUIDE.md](../PRODUCT_PAGE_FAQ_GUIDE.md).

## 1. GSC page aggregate (`data/performance-gsc.json`)

- **Date range:** `2026-01-02`–`2026-04-02`
- **Clicks:** 20 · **Impressions:** 496 · **Avg position:** 6.06

## 2. GSC queries (top 15 by impressions, `data/gsc-queries.json`)

| Query | Clicks | Impressions | Position |
|-------|--------|-------------|----------|
| nano ai | 1 | 81 | 6.26 |
| nanoai | 0 | 24 | 5.96 |
| ordio workspace | 0 | 17 | 3.18 |
| personaleinsatzquote | 0 | 17 | 12.65 |
| ordio | 0 | 6 | 1.5 |
| nono ai | 0 | 4 | 6.5 |
| perchat ai | 0 | 4 | 7.75 |
| nano aiei | 0 | 2 | 5.5 |
| nano.ai | 0 | 2 | 5 |
| ordio zeiterfassung | 0 | 2 | 28.5 |
| work nano | 0 | 2 | 6.5 |
| ai nono | 0 | 1 | 6 |
| gibt es smart assistant, die sich auf das tägliche leben konzentrieren und aufgaben abnehmen? | 0 | 1 | 16 |
| namo ai | 0 | 1 | 7 |
| nano chat | 0 | 1 | 11 |

## 3. SISTRIX (`data/keywords-sistrix.json`)

| Keyword | Notes |
|---------|-------|
| ki assistent personalabteilung | volume≈0 |
| hr chatbot deutsch | volume≈0 |
| ki schichtplanung chat | volume≈0 |
| schichtplan per spracheingabe | volume≈0 |
| personalsoftware ki assistent | volume≈0 |
| arbeitszeiten ki auswertung | volume≈0 |
| nano ai ordio | volume≈0 |

## 4. SISTRIX SERP top 10 (`data/sistrix-keyword-serp.json`)

- **Collected:** `2026-04-02T15:14:59Z` · **Credits (this run):** 8
- **Source:** SISTRIX API keyword.seo (limit=10, full SERP incl. ordio.com) — v2/scripts/product-pages/collect-feature-page-keyword-serp.php

| Keyword | Ordio rank | #1 non-Ordio domain |
|---------|------------|---------------------|
| ki assistent personalabteilung | — |  |
| hr chatbot deutsch | — |  |
| ki schichtplanung chat | — |  |
| schichtplan per spracheingabe | — |  |
| personalsoftware ki assistent | — |  |
| arbeitszeiten ki auswertung | — |  |
| nano ai ordio | — |  |
| natürliche sprache dienstplan | — |  |

Narrative and keyword picks: `data/KEYWORD_DECISION.md`.

## 5. SISTRIX domain-keyword SERP (VIP, `data/sistrix-domain-kw-serp.json`)

*Optional —* `keyword.domain.seo` + `kw` (~100 credits/keyword, cap 5): `php v2/scripts/marketing-pages/collect-marketing-page-domain-kw-serp.php --page=feature-nano-ai` or pipeline `--with-sistrix-domain-kw`. See [VIP_MARKETING_SEO_DATA_TIERS.md](../../marketing-pages/VIP_MARKETING_SEO_DATA_TIERS.md).

## 6. PAA / research (`data/faq-research.json`)

- **Source note:** Serper MCP (google.de, hl=de) + GSC query stems + HR/Personio topic scrape via Firecrawl MCP; SERPER_API_KEY unset in CLI pipeline.
- **Question stems / PAA:**
  - Was ist ein KI-Assistent in der Personalabteilung?
  - Was sind HR-Chatbots und wofür nutzt man sie?
  - Wie funktioniert ein HR-KI-Assistent mit Zugriffsrechten?
  - Welche Aufgaben kann ein KI-Assistent im Schichtplan übernehmen?
  - Sind KI-Assistenten im HR DSGVO-konform?
  - Braucht man Schulungen für einen KI-Chat in der Personalsoftware?
  - Kann ein KI-Assistent Zeiterfassung und Überstunden auswerten?
  - Wo liegen die Daten, wenn ich per Chat mit Ordio Nano arbeite?

## 7. Competitor FAQ scrape (`competitor-faq-analysis.json`)

- **Collected:** 2026-04-02 · Firecrawl MCP markdown scrape (HRworks news, Personio Assistant) + registry competitor_urls; topic extraction only — no competitor wording copied into Ordio FAQs.
- **:** 0 FAQ-like extractions
- **:** 0 FAQ-like extractions
- **:** 0 FAQ-like extractions

## 8. Editorial (manual)

- **Primary keyword:** `data/KEYWORD_DECISION.md`.
- **FAQ iteration:** [FEATURE_PAGE_IMPROVEMENT_WORKFLOW.md](../FEATURE_PAGE_IMPROVEMENT_WORKFLOW.md).
- **Post-deploy:** Re-check GSC/GA for `/nano-ai` after 4–8 weeks.

## 9. FAQ diff ideas (from data — human review)

- Map high-impression GSC queries (section 2) and PAA stems (section 6) to missing or weak FAQ H2s.
- Use SERP gaps (sections 4–5: Ordio weak/absent) and competitor headings (section 7) as **topic** hints; do not copy wording.
- After edits: `python3 v2/scripts/product-pages/validate-faq-answers.py --page=…` (registry `feature-*` or legacy key) and Rich Results Test.