--- title: "Join SEO and conversion data to find the keywords and pages that earn revenue" description: "Connect Search Console, GA4, and CRM data to measure conversion by intent, landing page, and keyword, and test pages without harming rankings." canonical: "https://scalewithsearch.com/articles/cro-seo-data-analysis" date: "2026-03-20" modified: "2026-09-25" --- ## Site navigation - [Scale With Search](https://scalewithsearch.com/) - Real estate - Real estate - [Real estate](https://scalewithsearch.com/for/real-estate) - Work - Start here - [Send your brief](https://scalewithsearch.com/work#send-your-brief) - [Prepare your six-question brief](https://scalewithsearch.com/work#prepare-your-six-question-brief) - Build - [Site build, content library with SEO, signal desk](https://scalewithsearch.com/work) - For your business - Trades and home services - [Auto body and collision shops](https://scalewithsearch.com/for/auto-body-and-collision-shops) - [Foundation and home repair contractors](https://scalewithsearch.com/for/foundation-and-home-repair) - 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Organic traffic grows 40 percent in a quarter, and the SEO report shows the gain. In the same quarter, the organic conversion rate halves, and revenue from search is flat. The SEO team and the conversion rate optimization (CRO) team each see half of the picture. Many organizations split the two. The SEO team measures rankings and traffic. The CRO team measures conversion rates and revenue. The split hides the link between search intent, content quality, and conversion. A searcher who types "email marketing software comparison" is evaluating tools. A searcher who types "email marketing tips" is learning. Both count as one "organic session," yet they convert very differently. This article shows you how to join the data, so that you can measure which queries, pages, and content types produce business results. ## Connect three layers of metrics | Layer | Metrics | |---|---| | Search visibility | Keyword positions, organic impressions, click-through rate from results, organic sessions | | Engagement quality | Engagement rate or bounce rate, time on page, pages per session, scroll depth | | Conversion | Micro-conversions (newsletter signups, downloads), macro-conversions (trials, demo requests, purchases), assisted conversions, revenue per session | The layers form one chain. Rankings produce impressions. Click-through rate turns impressions into sessions. Engagement shows whether the content matches the intent. Conversions measure the business result. In March 2024, GA4 renamed conversions to key events; the reports in this article use the current names where they differ. ## Join the data sources | Source | What it adds | |---|---| | Google Search Console | Query performance: impressions, clicks, click-through rate, position | | Google Analytics 4 | Behavior and conversion tracking by landing page | | Ahrefs or Semrush | Competitor rankings and backlink data | | Hotjar or Crazy Egg | Session recordings and heatmaps | | HubSpot or Salesforce | Revenue attribution from the CRM | Each tool sees part of the path. Search Console shows which queries bring clicks, but not which convert. GA4 shows conversion by landing page, but not the query. GA4 does not receive the Google search query at all. So the join key is the landing page: Search Console gives queries per page, and GA4 gives conversions per page. ## Tag pages so GA4 can group them Send a page category with each page view, so that you can compare page types: ```javascript gtag('event', 'page_view', { page_category: 'comparison', // homepage, blog, pillar, comparison, product, category content_depth: 'comprehensive', // for example, over 2,000 words cta_type: 'demo_request' }); ``` Then register each parameter as a custom dimension in GA4 under **Admin > Custom definitions**. GA4 ignores a parameter in reports until you register it. Use one taxonomy across the site: content type (blog, guide, comparison, tool), topic cluster, and funnel stage (awareness, consideration, decision). Organic traffic carries no UTM parameters, so the taxonomy must live in the page tags. If users move between domains, for example from the marketing site to the app, set up cross-domain measurement: ```javascript gtag('config', 'G-XXXXXXXXXX', { linker: { domains: ['example.com', 'app.example.com'] } }); ``` ## Classify queries by intent Intent predicts conversion. Four categories cover most queries: - informational, such as "what is email marketing" and "how to write subject lines": top-of-funnel awareness and long-term nurture; - commercial investigation, such as "best email marketing platforms" and "Mailchimp vs HubSpot": evaluation with strong qualification signals; - transactional, such as "Mailchimp pricing" and "buy email marketing software": ready to act; - navigational, such as "Mailchimp login" and "HubSpot support": brand searches from customers and prospects. Export the Search Console queries and classify them by word pattern: ```python import pandas as pd BRAND = 'yourbrand' queries = pd.read_csv('search_console_queries.csv') def classify_intent(query): words = set(query.lower().split()) if words & {'what', 'how', 'why', 'guide', 'tutorial'}: return 'informational' if words & {'best', 'vs', 'versus', 'comparison', 'review'}: return 'commercial' if words & {'buy', 'pricing', 'cost', 'discount', 'trial'}: return 'transactional' if words & {'login', 'support', 'contact', BRAND}: return 'navigational' return 'unknown' queries['intent'] = queries['query'].apply(classify_intent) by_intent = queries.groupby('intent').agg( {'impressions': 'sum', 'clicks': 'sum', 'position': 'mean'}) ``` Then map each query to its landing page and merge the GA4 conversion data by page. The result is conversion rate and revenue by intent. For the intent model itself, read [search intent explained](/articles/search-intent-explained). ## Measure conversion by landing page Build a GA4 exploration: 1. Open **Explore** and create a free-form exploration. 2. Add the dimensions **Landing page** and **Session source / medium**. 3. Add the metrics **Sessions**, **Key event rate** (the former conversion rate), and **Total revenue**. 4. Filter to organic search traffic. 5. Sort by key event rate, highest first. The top rows show which content types and intents turn organic visits into results. Build a baseline table by page type: homepage, blog post, pillar page, comparison page, product page, pricing page. Pages closer to a decision, such as pricing and product pages, usually convert higher than informational posts. Your own baseline tells you which pages fall below their type and deserve attention. Find the weak pages. Open **Reports > Engagement > Landing page**, add bounce rate to the report, and filter to organic search. List pages with a bounce rate over 70 percent and meaningful traffic. For each one, ask five questions: 1. Does the content match the query intent? Check the queries in Search Console. 2. Is the depth enough against the top-ranking competitors? 3. Are the calls to action clear and relevant to the intent? 4. Does the page load fast? Check its Core Web Vitals. 5. Can a reader scan it: headings, lists, short paragraphs? ## Credit organic search across the path Many conversions involve several visits. Organic search can start the journey, assist it, or close it: - first touch: a user finds the brand through search and converts later through direct traffic or email; - mid-journey: a user arrives from a paid ad, researches through organic search, and converts direct; - last touch: a user who knows the brand searches for it and converts in that session. A last-click view under-credits the first two patterns. Use the attribution reports in the GA4 **Advertising** section. The conversion paths report shows the sequence of channels. The model comparison report compares last-click with data-driven attribution and shows which channels last-click over- or under-credits. In November 2023, GA4 retired the first-click, linear, time-decay, and position-based models; data-driven and last-click remain. For the wider method, read [attribution modeling for SEO](/articles/attribution-modeling-for-seo). ## Attribute revenue to keywords For ecommerce, send the purchase event with its value: ```javascript gtag('event', 'purchase', { transaction_id: orderId, value: orderTotal, currency: storeCurrency, items: [{ item_id: sku, item_name: productName, price: unitPrice }] }); ``` For lead generation, give each lead type an average value from your closed-deal history. Send the value with the lead event: ```javascript gtag('event', 'generate_lead', { value: averageLeadValue, currency: storeCurrency, method: 'demo_request' }); ``` Then join the two exports: 1. Export Search Console queries with impressions, clicks, click-through rate, and position. 2. Export GA4 landing pages with sessions, key events, and revenue. 3. Match each query to its landing page. 4. Estimate revenue per query. ```text Revenue from query = clicks × (landing page key events ÷ landing page sessions) × average order value ``` The estimate separates queries that earn revenue from queries that only bring traffic. When the sale happens offline, add the missing links. Use call tracking with a unique number per source. Use the performance data in Google Business Profile for local actions. Track coupon codes by source, and ask customers how they found you. Give top-of-funnel actions a value from their historical rate of conversion to closed deals. ## Score content on search and conversion Score each page on two components, each out of 100: | Component | Measure | Points | |---|---|---| | SEO | Average position, weighted by search volume | 30 | | SEO | Organic traffic | 25 | | SEO | Backlinks to the page | 15 | | SEO | Impressions | 15 | | SEO | Click-through rate | 15 | | CRO | Conversion rate against the site average | 35 | | CRO | Revenue per session | 30 | | CRO | Engagement rate | 20 | | CRO | Pages per session | 10 | | CRO | Average session duration | 5 | Combined score = (SEO score × 0.4) + (CRO score × 0.6). The weight favors business results over traffic. Raise the CRO weight for ecommerce, and raise the SEO weight for media sites that sell traffic. Then plot pages on two axes, traffic against conversion rate, and act by quadrant: | Quadrant | Action | |---|---| | High traffic, high conversion | Maintain, expand, and create similar content | | High traffic, low conversion | Fix the calls to action and the user experience | | Low traffic, high conversion | Raise search visibility with optimization and backlinks | | Low traffic, low conversion | Consolidate or delete | Some high-volume queries convert poorly, and some low-volume queries convert well. To compare them, calculate expected value: monthly searches × click-through rate × ranking probability × conversion rate × average order value. Large volume can win on total revenue. High-conversion queries usually cost less and win faster. Target both: pillar content for volume, supporting content for commercial terms. ## Run conversion tests without harming rankings Google's guidance on website testing sets three rules. Do not cloak: show Googlebot the same variants that users can get, and never exclude it by user agent. Use `rel="canonical"` from each variant URL to the original. Use a 302 redirect, not a 301, when a test redirects users. Run each test only as long as it needs; 2 to 4 weeks is a common window. | Usually safe to test | Can affect rankings | |---|---| | Call-to-action color, text, and placement | H1 headings and title tags | | Form length and field labels | Main body content and keyword use | | Pricing page layout | URL structure | | Product image size | Internal link patterns | | Navigation menu order | Adding or removing major sections | Record the variant with each page view, and register it as a custom dimension: ```javascript gtag('event', 'page_view', { ab_test_variant: 'variant_b' }); ``` Segment results by variant, so that a conversion change is not mistaken for a change in traffic quality. To separate the two in general, keep control pages: similar pages that you did not change. If the changed pages improve and the controls stay flat, the change worked. If both improve, traffic quality improved site-wide. If only new visitors convert better, traffic quality is the likely cause. The test designs themselves are in [SEO A/B testing methods](/articles/seo-ab-testing-methods). ## Find competitor gaps across both Gather competitor rankings and traffic estimates from Ahrefs or Semrush, and traffic source and engagement estimates from Similarweb. Use BuiltWith to see their technology and CRO tools. Review their funnels and calls to action by hand. Look for three openings. The first is a keyword where a competitor ranks but gives a poor experience. The second is a high-traffic competitor page with weak conversion elements. The third is a commercial keyword cluster the competitor does not cover. An example: a competitor ranks first for "project management software." Similarweb estimates a high bounce rate for the page. It has no clear call to action above the fold, a poor mobile layout, and generic content. A page with a better experience can win more conversions from that query, even from position 2 or 3. The broader method is in [competitor SEO analysis for marketing](/articles/competitor-seo-analysis-marketing). ## Report to stakeholders monthly Build one dashboard in Looker Studio that connects GA4, Search Console, and CRM data. Give it four sections: - visibility: organic traffic with its monthly change, average position for tracked terms, impressions and click-through rate, and page 1 rankings gained and lost; - revenue: organic-attributed revenue by model, conversion rate by channel, revenue per organic session, and the top revenue queries; - content: the top 10 pages by traffic and revenue, early results of new content, refresh impact, and pages with high traffic and low conversion; - competition: visibility share against the top 3 competitors, keyword gaps, and differentiators kept or lost. For build steps, read [Looker Studio for SEO reporting](/articles/looker-studio-seo-reporting). Check the dashboard weekly for anomalies, analyze trends monthly, and review strategy quarterly. After a major algorithm update or site change, check daily for two weeks. Set alerts for large swings. 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Scale With Search 2026 [scalewithsearch.com](https://scalewithsearch.com) ```