נתונים שיעזרו לקבל החלטות חכמות יותר

שלושת המקורות לא שווים. הנה סדר ההתחלה המומלץ:

1. כנס ל-Google Ads → Reports → Predefined reports → Search terms
2. שנה את טווח התאריכים ל-90 ימים אחרונים
3. ודא שהעמודות כוללות: Search term, Impressions, Clicks, CTR, Avg CPC, Conversions, Cost
4. לחץ על סמל ה-Download (⬇) → CSV
5. שמור בשם ads-search-terms-90d.csv

You are helping me export a Google Ads Search Terms report. I need you to walk me through it step by step.

Context: I manage Google Ads for a Hebrew-language law firm website (thelaw.co.il). I need the last 90 days of search term data.

Steps to walk me through:
1. Navigate to Google Ads → Reports → Predefined reports → Search terms
2. Set date range to last 90 days
3. Confirm which columns to include: Search term, Impressions, Clicks, CTR, Avg CPC, Conversions, Conv. rate, Cost
4. Download as CSV

After I provide the CSV, please:
- Identify the top 20 search terms by clicks
- Group them by intent category (legal service type, geographic, brand, question-based)
- Flag any Hebrew terms that appear misspelled or truncated
- Output a clean table with: term | clicks | conversions | intent-category | recommended-page

Output language: English for column headers, keep Hebrew search terms as-is.

1. ב-Google Ads → Reports → Predefined reports → Landing pages
2. טווח: 90 ימים אחרונים
3. עמודות: Landing page, Impressions, Clicks, Conversions, Cost, Mobile-friendly click rate
4. הורד CSV → שמור בשם ads-landing-pages-90d.csv

I have a Google Ads Landing Pages CSV report (90 days) for thelaw.co.il, a Hebrew law firm.

Please analyze it and:
1. List all unique landing page URLs, sorted by clicks (descending)
2. Flag which URLs use Hebrew slugs (e.g., /עורך-דין-מסחרי/) vs. date-based paths (/2024/01/01/slug/)
3. Mark any URL that appears to be a high-priority migration target (>50 clicks OR >1 conversion)
4. Output format:
   URL | clicks | conversions | url-type | migration-priority

migration-priority values: CRITICAL (do not change URL), HIGH (keep or 301), LOW (can redirect freely)
Keep Hebrew in the URL column as-is. All other columns in English.

1. ב-Google Ads → Keywords → Search keywords
2. הוסף עמודות: Quality Score, Landing page exp., Expected CTR, Ad relevance
3. טווח: 90 ימים אחרונים
4. הורד CSV → שמור בשם ads-keywords-90d.csv

I have a Google Ads Keywords CSV (90 days) for thelaw.co.il.

Please:
1. Filter to keywords with Quality Score data (QS 1-10)
2. Sort by QS ascending (lowest first — these are the biggest problems)
3. For QS ≤ 5: explain what "Landing page experience: Below average" means in practice
4. Group low-QS keywords by which landing page they point to
5. Output:
   keyword | QS | landing-page-exp | expected-CTR | ad-relevance | destination-url | action-needed

action-needed values: "Rewrite page content", "Create dedicated landing page", "Good — no action"

This will help us prioritize which pages to improve during the site rebuild. Keep Hebrew keywords as-is.

1. ב-Google Ads → Reports → Custom report → Table
2. Rows: Landing page
3. Columns: Clicks, Impressions, Cost, Conversions, Conv. rate, Cost/conv.
4. טווח: 90 ימים; מיון לפי Conversions (גבוה לנמוך)
5. הורד CSV → שמור בשם ads-conversions-per-page-90d.csv

I have a Google Ads custom report: conversions per landing page (90 days) for thelaw.co.il.

Please:
1. Rank pages by conversion rate (not just raw conversions)
2. Identify the top 5 "golden pages" — high conv. rate with meaningful traffic
3. Identify "wasted budget pages" — high cost, zero conversions
4. Output two tables:

Table 1 — Golden Pages:
URL | clicks | conversions | conv-rate | cost | notes

Table 2 — Wasted Budget:
URL | clicks | conversions | cost | recommendation

recommendation values: "Pause ad", "Redesign page", "Add clear CTA", "Check conversion tracking"

All output in English except Hebrew URLs which should be kept as-is.

1. כנס ל-GA4 → Reports → Engagement → Pages and screens
2. שנה תאריכים ל-90 ימים אחרונים
3. ודא שהעמודות כוללות: Page path, Views, Users, Avg engagement time, Bounce rate
4. לחץ על Export (למעלה בצד) → CSV
5. שמור בשם ga4-pages-90d.csv

I have a GA4 "Pages and screens" CSV report (90 days) for thelaw.co.il, a Hebrew law firm.

Please:
1. Filter to top 50 pages by views
2. Categorize each page: homepage, article, practice-area-page, category, tag, form/contact, other
3. Flag pages with engagement time < 30 seconds AND views > 100 (high bounce risk)
4. Output:
   page-path | views | users | avg-engagement-sec | category | bounce-risk | migration-priority

migration-priority: CRITICAL (top 20 by views), HIGH (21-50), NORMAL (rest)

Keep Hebrew page paths as-is. All column headers in English.

1. GA4 → Reports → Acquisition → Traffic acquisition
2. טווח: 90 ימים אחרונים
3. עמודות: Session default channel group, Sessions, Users, Engaged sessions, Conversions, Revenue
4. Export → CSV → שמור בשם ga4-traffic-sources-90d.csv

I have a GA4 Traffic Acquisition CSV (90 days) for thelaw.co.il.

Please:
1. Show the channel breakdown as percentages (organic, paid, direct, referral, social)
2. Flag if paid search > 60% of sessions (means SEO dependency is lower, paid is critical)
3. Flag if organic > 50% (means SEO is the core asset — migration risk is higher)
4. Calculate engaged session rate per channel
5. Output summary table:
   channel | sessions | % of total | engaged-sessions | engagement-rate | conversions | assessment

assessment values: "Primary driver", "Secondary", "Negligible", "Investigate"

All output in English.

1. GA4 → Reports → Engagement → Events
2. טווח: 90 ימים אחרונים
3. מיון לפי Event count (גבוה לנמוך)
4. שים לב לאירועים: generate_lead, form_submit, click, file_download
5. Export → CSV → שמור בשם ga4-events-90d.csv

I have a GA4 Events CSV (90 days) for thelaw.co.il, a Hebrew law firm.

Please:
1. Identify all conversion-type events (form_submit, generate_lead, contact, phone_click, outbound_click)
2. If NO conversion events exist: flag this as "GA4 may not be configured for conversion tracking"
3. For each conversion event: show count, and if available, the page it fired on
4. Distinguish between automatically collected events (page_view, scroll, session_start) and custom events
5. Output:
   event-name | event-count | event-type | is-conversion | notes

event-type: "auto-collected", "enhanced-measurement", "custom"
notes: explain what the event means in plain English

Flag critical finding if total conversion events = 0.

1. GA4 → Explore → Path exploration
2. Starting point: Session start → Step 1: Page path
3. הצג את 10 הדפים הראשונים שאנשים מבקרים אחרי הכניסה לאתר
4. צלם מסך (Snapshot) — דוח זה לא ניתן ל-Export ישיר לCSV
5. לחלופין: Free form exploration עם Rows: Landing page, Cols: page_view count
6. שמור את ה-Snapshot בשם ga4-user-flow-snapshot.png

I'm sharing a screenshot of a GA4 Path Exploration for thelaw.co.il (Hebrew law firm).

The path starts at Session Start → shows which pages users visit next.

Please analyze the screenshot and:
1. Identify the top 3 entry pages (most traffic enters here)
2. Identify drop-off points (where most users exit)
3. Identify if users reach "contact" or "form" pages from any major path
4. Flag if the homepage leads to contact vs. articles (this affects navigation architecture)
5. Output:
   - Top entry pages list
   - Top exit pages list
   - Key paths that lead to contact/conversion
   - Navigation recommendation for the new site

All output in English. Hebrew page names can be transliterated or kept as-is.

1. כנס ל-Google Search Console → Performance → Search results
2. שנה טווח ל-Last 28 days
3. ודא שה-"Queries" tab פעיל
4. גלול למטה → לחץ Export (ראש הדף) → Download CSV
5. שמור בשם gsc-queries-28d.csv

I have a Google Search Console Queries CSV (28 days) for thelaw.co.il, a Hebrew law firm.

Please:
1. List top 30 queries by clicks
2. Group them by topic: commercial-intent (hiring a lawyer), informational (legal questions), brand, navigational
3. Identify queries with high impressions but low CTR (< 2%) — these are "optimization opportunities"
4. Identify queries where we rank position 4-10 (page 1 but not top 3) — easy wins for the new site
5. Output:
   query | clicks | impressions | CTR | avg-position | topic-group | opportunity-type

opportunity-type: "Quick win (pos 4-10)", "CTR fix needed", "Strong performer", "Impressions only"

Keep Hebrew queries as-is. All other output in English.

1. GSC → Performance → Search results
2. לחץ על ה-tab Pages (ולא Queries)
3. טווח: 28 ימים
4. Export → Download CSV → שמור בשם gsc-pages-28d.csv

I have a GSC Pages CSV (28 days) for thelaw.co.il.

Please:
1. List top 20 pages by clicks
2. For each page, categorize: homepage, article (/YYYY/MM/DD/slug/), practice area, category, tag, other
3. Cross-reference: flag if any page has high impressions (>500) but zero clicks (CTR = 0%) — these have indexing or title/description problems
4. Output:
   url | clicks | impressions | CTR | avg-position | page-type | flag

flag values: "CTR problem", "Strong performer", "Low traffic — monitor", "Impressions only — check meta"

Keep Hebrew URLs as-is. All other output in English.

1. GSC → Indexing → Pages
2. בחן: כמה דפים ב-"Indexed", כמה ב-"Not indexed"
3. לחץ על Not indexed → ראה את הסיבות (Crawled but not indexed / Excluded by noindex / Soft 404)
4. Export → Download CSV → שמור בשם gsc-coverage-report.csv
5. גם: לחץ על Sitemaps → בדוק אם יש שגיאות

I have a GSC Coverage (Indexing) CSV for thelaw.co.il.

Please:
1. Summarize: total indexed vs. not indexed count
2. For "not indexed" pages — list the top reasons and count per reason
3. Flag any "Soft 404" or "Duplicate without user-selected canonical" issues
4. Cross-reference with known garbage pages: /form-test/, /formtest/, /test/, /4234/, /4306/ — are these indexed?
5. Output:
   - Summary table: status | count | % of total
   - Not indexed reasons table: reason | count | recommended action
   - Garbage pages status: url | indexed-yes/no | action

All output in English.

1. GSC → Links (בתפריט הצד שמאל)
2. תחת External links → Top linking sites → לחץ More
3. לחץ על Export external links (למעלה) → Download more sample links
4. שמור בשם gsc-backlinks-full.csv
5. בנוסף: Top linked pages → Export → שמור בשם gsc-top-linked-pages.csv

I have two GSC backlink CSVs for thelaw.co.il (Hebrew law firm):
1. gsc-backlinks-full.csv — linking sites with link counts
2. gsc-top-linked-pages.csv — which pages on our site receive the most external links

This is critical data: these backlinks pass "link equity" to specific URLs. If we migrate the site and any of these destination URLs return 404, we lose that SEO value permanently.

Please:
1. From backlinks CSV: list top 20 linking domains by link count. Categorize each:
   - Legal directories (משפט, עו"ד)
   - News/media sites
   - Government/official
   - Business directories
   - Unknown/spam

2. From top-linked-pages CSV: list the exact destination URLs that receive the most external links. These are the HIGHEST PRIORITY pages for the migration — their URLs must either be preserved exactly or receive a 301 redirect.

3. Output:
   Table 1 — Linking Domains:
   domain | linking-pages | category | authority-guess (high/medium/low)

   Table 2 — Link Destinations (MUST PRESERVE):
   destination-url | external-links | migration-action

   migration-action: "KEEP URL EXACTLY", "301 redirect mandatory", "Monitor"

4. Flag: are any of the top 5 linked pages currently planned as 410 Gone? (Cross-reference: /form-test/, /formtest/, /test/, /4234/, /4306/)

All output in English. Keep Hebrew URLs as-is.

אם אתה רוצה להשתמש ב-Claude Desktop, ChatGPT, או כל AI אחר כדי לנהל את כל תהליך ייצוא הנתונים מהתחלה — הדבק את הפרומפט הזה בתחילת הסשן. הוא יוביל אותך שלב-שלב דרך כל 12 הדוחות.

You are a data extraction and SEO migration assistant. I'm rebuilding thelaw.co.il, a Hebrew-language law firm website (25+ years, Tel Aviv area). I have three data sources to extract from: Google Ads, Google Analytics 4, and Google Search Console.

I need you to walk me through extracting exactly 12 reports, one at a time. After I complete each extraction and provide you the CSV (or screenshot), analyze it before we move to the next one.

=== CONTEXT ===
- Site: thelaw.co.il (WordPress, soon migrating to Next.js + Sanity + Cloudflare Pages)
- Language: Hebrew RTL
- GSC access: only ~3 weeks of data (viewer access recently granted)
- Ads: active Google Ads campaigns, exact budget unknown
- Goal: inform migration priorities, keyword architecture, conversion tracking setup

=== TIME RANGES ===
- Google Ads reports: Last 90 days
- GA4 reports: Last 90 days
- GSC Queries and Pages: Last 28 days
- GSC Backlinks: All time (historical, no date filter)

=== THE 12 REPORTS (in priority order) ===

PRIORITY 1 — Google Ads (most actionable):
  Report 1: Search Terms — navigate to Reports > Predefined > Search terms → export CSV
  Report 2: Landing Pages — navigate to Reports > Predefined > Landing pages → export CSV
  Report 3: Keywords with Quality Score — navigate to Keywords > Search keywords, add QS columns → export CSV
  Report 4: Conversions per Landing Page — navigate to Reports > Custom report (Table), rows=Landing page, cols include Conversions → export CSV

PRIORITY 2 — Google Analytics 4:
  Report 5: Pages and Screens — Reports > Engagement > Pages and screens → export CSV
  Report 6: Traffic Acquisition — Reports > Acquisition > Traffic acquisition → export CSV
  Report 7: Events — Reports > Engagement > Events → export CSV
  Report 8: Path Exploration — Explore > Path exploration → screenshot (cannot export to CSV)

PRIORITY 3 — Google Search Console:
  Report 9: Top Queries — Performance > Search results > Queries tab → export CSV
  Report 10: Top Pages — Performance > Search results > Pages tab → export CSV
  Report 11: Coverage/Indexing — Indexing > Pages → export CSV
  Report 12: Backlinks — Links > External links > Top linking sites → Export external links CSV
             ALSO: Top linked pages → export CSV (save as separate file)

=== OUTPUT FORMAT FOR EACH REPORT ===
After I give you each CSV:
1. Print a 3-line summary of what you found
2. Flag any critical issues immediately (in bold)
3. Output a clean normalized table with English column headers (keep Hebrew text in content cells as-is)
4. Name the output table after the report (e.g., "Report 1 — Search Terms Analysis")

=== FILE NAMING CONVENTION ===
When I save the files locally, I will use:
  ads-search-terms-90d.csv
  ads-landing-pages-90d.csv
  ads-keywords-90d.csv
  ads-conversions-per-page-90d.csv
  ga4-pages-90d.csv
  ga4-traffic-sources-90d.csv
  ga4-events-90d.csv
  ga4-user-flow-snapshot.png
  gsc-queries-28d.csv
  gsc-pages-28d.csv
  gsc-coverage-report.csv
  gsc-backlinks-full.csv
  gsc-top-linked-pages.csv

All files will go into: migration/inventory/google-data/

=== SPECIAL INSTRUCTIONS ===
- Never normalize or translate Hebrew text in data cells
- If a column header is in Hebrew in the export, translate it to English in your output
- Flag immediately if any source appears unconfigured (e.g., GA4 with zero conversion events)
- After all 12 reports: produce a final "Migration Priority Matrix" ranking the top 20 pages by combined score across all sources

Start now: tell me the exact steps to get Report 1 (Google Ads Search Terms). Wait for me to paste the CSV before moving to Report 2.

מסמך ה-STATUS.md מציין 4 פערים ידועים. הנה מה שכל דוח עוזר לסגור:

תצור תיקייה migration/inventory/google-data/ ותניח שם את כל הקבצים. שמות הקבצים המומלצים מופיעים בצ'קליסט למטה. כשתרגיש שזה מוכן — תגיד לי "נתונים מוכנים" ואני אנתח.