How to use ChatGPT to analyze independent foreign trade websites? Find the problem and get the solution

Let us make one thing clear first: URL is not equal to data

Recently, many friends in foreign trade have begun to try to use ChatGPT to analyze independent websites. The most common operation is to send the website address and enter a sentence: Help me analyze the traffic, inclusion, keyword ranking and existing problems of this website.

A few minutes later, a seemingly complete report came out. It may include website positioning, SEO issues, keyword suggestions, content planning, technical optimization, and even traffic judgment. However, just because the report is written completely does not mean that the conclusion has been established.

If only one URL is provided, ChatGPT can mainly analyze the public pages of the website and the public information that can be found during Internet searches. It cannot directly read Google Search Console, GA4, CRM or server backend data based on the URL alone.

In other words, it can determine where there may be problems with the website, but it cannot accurately know the website's real monthly natural traffic, keywords that are generating clicks, effective inquiry pages, declining rankings, effective index pages, visitor loss links, and final transactions.

ChatGPT can browse websites, compare sources, read files, and analyze data as capabilities and permissions allow, but the quality of analysis still depends on the context, files, and available tools provided. Professional website analysis does not simply throw the URL to ChatGPT, but looks at the website's public information, search data, access data, inquiry data and competitor information together.

Provide only the website URL, what can ChatGPT analyze?

Just providing the URL is not without value. This method is suitable for the first round of website diagnosis, especially when taking over a new website, preparing for revision, checking the page structure, or quickly researching competitors.

Judge whether the website positioning is clear

ChatGPT can check whether the homepage can quickly answer: What is the type of enterprise, what it mainly produces or provides, which markets and customers it serves, whether it supports OEM, ODM or customization, what is the difference compared with peers, and whether customers should view products, download catalogs or submit inquiries next.

Many foreign trade websites put a lot of product pictures on their homepages, but do not clearly explain the company's positioning. Visitors can see what's there, but don't know why they should contact you.

Check the website structure and page relationships

Through the public page, you can initially judge whether the navigation conforms to customer search habits, whether the product categories are repeated or too deep, whether the URL naming is unified, whether important products have independent landing pages, whether the blog forms an internal link with the product page, and whether there are problems with isolated pages, inconsistent multi-language structures, or difficulty in finding basic pages.

If the website has many pages, it is best to provide a complete URL list. Not all pages may be discovered by relying solely on navigation and search engine exposure results.

Check basic page SEO

ChatGPT can view Title, Meta Description, H1 to H3 structure, consistency of page theme and keywords, whether the text answers the search question, image ALT, internal links, duplicate content and CTA.

However, this type of analysis determines how the page is written now, not the actual performance of the page in Google.

Check whether B2B purchasing information is complete

Buyers usually need to confirm corporate identity, product applications, specification materials, processes, customization scope, MOQ, sample and bulk delivery, certification testing, quality control, cases, after-sales processing and contact information. Whether this information exists and whether it is easy to find can be initially determined by just looking at the public page.

Therefore, the results obtained by only providing the URL are closer to a website physical examination and cannot replace SEO and conversion analysis based on background data.

Why can't ChatGPT determine the real traffic based on the URL alone?

Website click, traffic, ranking and inquiry data mainly exist in Google Search Console, Google Analytics 4, Bing Webmaster Tools, Ahrefs or Semrush, form and chat systems, CRM and server logs. Without this data, ChatGPT can only make inferences based on public pages, search results, and third-party information.

Third-party estimated traffic is not equal to real traffic

Ahrefs, Semrush and other tools will estimate website traffic based on keyword database, ranking position and click-through rate model. This data is suitable for researching competitors, judging the approximate size, discovering competitive keywords, comparing trends and finding content gaps, but it is not the real access data of the website backend.

For B2B websites with small traffic, scattered keywords, highly specialized products, or multiple language versions, there may be significant differences between third-party estimates and GA4 actual data. The report should clearly state the third-party estimated traffic and cannot directly state the actual traffic of the website.

site:domain name cannot accurately represent Google's inclusion volume

site: Search can quickly view some public pages and can also find abnormal URLs, old pages or irrelevant content, but the number displayed in the search results is not an accurate index statistics.

To determine the indexing situation, you should combine the GSC web page index report, Sitemap status, URL inspection, Canonical, discovered but not indexed, crawled but not indexed, and pages excluded by robots.txt, noindex or redirection. The point is not how many pages are included, but whether important pages are included in the index.

Keyword ranking does not mean traffic

The presence of keywords in Google can only mean that the page has gained a certain degree of search visibility. The ranking is too low, the search demand is too small, the intent does not match, or the searcher is not the target buyer, which may lead to no clicks and inquiries.

When analyzing keywords, at least combine impressions, clicks, CTR, average ranking, landing page, country, search intent, product relevance and inquiry value. The average GSC ranking is also an average of a period of time, multiple users and multiple scenarios, which does not mean that all regions are fixedly ranked in the same position.

Visits does not mean commercial value

A certain blog may bring many visitors from non-target countries, but no product page visits or form submissions. Another product page does not have many visits, but it continues to generate high-quality inquiries. Just looking at Sessions or Users, it's easy to mistake the pages with the most traffic for the most valuable pages.

What independent foreign trade stations ultimately need to focus on is not the traffic itself, but which channels, keywords and pages are bringing customers that meet the target market and procurement requirements.

What data needs to be prepared for ChatGPT to conduct professional analysis?

If you want ChatGPT to find real growth opportunities, it is recommended to prepare five types of information: website public page, Google Search Console, GA4, complete URL list and inquiry or CRM.

Google Search Console data

It is recommended to export the Queries, Pages, Countries, Devices, Dates and Search Appearance data of the past 3 months, the past 6 months and the past 12 months respectively according to the website conditions.

ChatGPT can use this to find high-display low-CTR keywords, key promotion words with an average ranking of 4 to 10, first-page opportunity words from 11 to 20, click-drop pages, mismatch between keywords and landing pages, multiple pages competing for the same topic, changes in different countries, and new growth and loss of keywords.

Don’t ask for conclusions directly as soon as you upload the file. First let ChatGPT check the date range, field meaning, missing values, duplicate data and filter conditions.

GA4 data

It is recommended to export data related to Landing Page, Traffic Acquisition, Country, Device Category, Engagement, Key Events, Form Submission and Organic Search.

These data can help determine real visitor pages, target country participation, pages with traffic but no inquiries, the path from the landing page to the product page, and access behavior before form submission. If GSC answers what search customers used to enter the website, GA4 is more suitable to answer what they did after entering the website.

The premise is that the GA4 tracking settings are correct. If form submission, WhatsApp click, email click, and catalog download are not configured as key events, ChatGPT cannot restore real conversions from the data.

Website complete URL list

The URL list should preferably include the complete URL, page type, language, category, target keywords, Title, H1, Canonical, HTTP status code, index permissions, GSC click display, GA4 access and inquiry status.

Use this checklist to check category hierarchies, duplicate pages, orphan pages, keyword gaps, page merges, 301 redirects, low-value index pages, and multilingual correspondences. Before merging different data sources, the protocol, www, trailing slash, case and trace parameters should be harmonized.

Competitor Information

It is recommended to select 3 to 5 competitors with real reference value, including manufacturers with similar product structures, websites with the same target market, peers with better natural rankings, websites with complete content systems and websites with better inquiry path design.

Suitable for comparing product classification, keyword coverage, page structure, technical content, customization capabilities, factory strength, quality control, certification cases, FAQ, CTA, forms and AI citation conditions. Competitive product data is used to find gaps and cannot prove how many real inquiries the other party has received.

Inquiry and CRM data

You can organize the inquiry date, source, country, product, first entry page, final submission page, target customer judgment, validity, quotation, transaction and non-transaction reasons.

Customer names, email addresses, phone numbers, contracts, quotes and other unnecessary sensitive information should be deleted before submitting data. Analyzing website performance usually does not require uploading complete customer identity data.

A more reliable ChatGPT website analysis process

The first step: to explain the business goals first

At least explain the industry, core products, target countries, target customers, business models, current problems, and whether you want to increase traffic, inquiries, or exposure to a certain type of product. When the same website faces American dealers and European engineering projects, the analysis standards will be completely different.

The second step: check the data first and do not rush to draw conclusions

Let ChatGPT first explain which files it has received, the content of each file, whether the dates are consistent, whether the fields can be understood, whether there are missing values and duplicates, whether the URL can match, whether the GA4 key events are clear, and what data has not been provided.

This step may seem a little slower, but it can prevent the entire report from being based on wrong data.

Step 3: Establish website benchmarks

First determine the natural search click trends, main traffic pages, main search countries, core product words, effective index pages, inquiry conversions and competitor gaps. Without a benchmark, it is difficult to judge whether subsequent optimizations are effective.

Step 4: Divide the problem into three levels of evidence

All conclusions should be marked as: A, issues that have been proven by the data; B, issues that are inferred based on the page; C, issues that still need to be supplemented with data verification.

For example, GSC shows that the continuous decrease in clicks on a certain page is proved by data; unclear positioning of the homepage is judged by page analysis; the form is too long, resulting in a decline in inquiries. If there is no behavioral data, it can only be listed as to be verified. This classification prevents reports from turning speculation into fact.

Step 5: Prioritize by impact and cost

It can be evaluated from four dimensions: traffic or inquiry impact, evidence strength, repair difficulty, and completion time. Prioritize issues with greater impact, clear evidence, and lower execution costs, such as error noindex, high-visibility page titles, and product page purchasing information.

Step 6: Form a verifiable execution plan

The solution cannot stop at strengthening content construction or improving user experience. It is recommended that the modified page, modified content, reason, person in charge, completion time, verification data and review time should be written clearly.

Website analysis instructions that can be directly copied and used

Complete the following template and provide it to ChatGPT together with GSC, GA4, URL list, competing products and desensitized inquiry data.

You are a B2B foreign trade independent station SEO, GEO, data analysis and inquiry conversion consultant.

Website address:
Industry:
Core products:
Target market:
Target customers:
Main business models:
Main competitors:
Current business goals:

I have uploaded the following information:
1. Google Search Console data
2. GA4 data
3. Complete URL list of website
4. Competitor information
5. Inquiry or CRM data (if any)

Please analyze in stages and do not make final conclusions immediately upon receipt of the document.

Phase 1: Check input data
1. List all documents received;
2. Describe the fields, date range and data granularity contained in each file;
3. Check for missing values, duplicates, outliers and caliber conflicts;
4. Check whether GSC, GA4 and URL lists can be matched by standardized URLs;
5. Explain what questions the existing data can answer;
6. List the data that are still missing but would affect the judgment;
7. Don’t make up missing data or treat third-party estimates as true traffic.

Phase 2: Analyze website performance
Please analyze website positioning, natural search trends, page indexes, keywords and landing pages, page structure, technical SEO, GEO conditions, purchasing trust, inquiry paths, competitive product gaps, and the relationship between traffic and effective inquiries.

Stage Three: Marking Levels of Evidence
Each conclusion must be marked as:
A. The data has proven it;
B. Inference based on website pages or public information;
C. Additional data verification is still needed.

Phase 4: Output Solution
Please use the following fields to output: problem, evidence, impact, possible causes, specific solutions, involved pages, priority, execution difficulty, person in charge's suggestions, verification indicators, and recommended review time.

Phase Five: Develop an Execution Plan
Output respectively the repairs that must be completed in the next 30 days, the content and page optimization that should be completed in the next 60 days, and the structural, technical and growth projects that should be promoted in the next 90 days.

Finally, the five most serious problems at present, the 10 pages most worthy of priority optimization, the 20 keywords with the greatest growth opportunities, problems that can be postponed and a list of data that still need to be supplemented are given.

All conclusions must be based on the information provided. For information that cannot be confirmed, please clearly write "further verification is needed" and do not supplement data, traffic, rankings, inquiries or industry conclusions by yourself. 

ChatGPT is most suitable for discovering which foreign trade website opportunities?

Keywords that have been recognized but have not yet entered the ideal position

A large number of keywords are in the average ranking of 4 to 20, indicating that the relevant pages already have a certain search basis. You can continue to check search intent, topic completeness, Title and H1, purchasing information, internal links, keyword conflicts and content freshness. These types of opportunities are usually worth prioritizing over building a new page from scratch.

Page with high display and low clicks

Common reasons include the ranking is still low, the SEO title is vague, does not reflect B2B attributes such as Manufacturer or OEM, the title is inconsistent with the intention, the value of the Meta Description is unclear, or there are advertisements, pictures, videos and AI answers in the search results. Low CTR needs to be judged by combining ranking, query, country, device and SERP.

The gap between content and purchasing decisions

Many factory websites only write product names and parameters, but do not answer MOQ, OEM or ODM, sampling time, materials, quality inspection, packaging, certification, delivery and after-sales questions. Supplementing these contents is not to increase the word count, but to directly affect whether the buyer continues to evaluate the supplier.

Page structure and keyword conflict

Combining the URL list, GSC page data and internal link relationships, ChatGPT can help find problems such as too deep classification levels, scattered similar products, inconsistent URLs, disconnection of blogs and product pages, multiple pages targeting the same keywords, lack of internal links on important pages, inability to support multiple languages, and duplication of old and new pages.

Breakpoint between traffic and inquiries

If there are clicks on GSC and visits on GA4, but there are no valid inquiries from CRM, the problem may come from traffic intent, target country, product information, trust evidence, CTA, form, page performance or contact information. It is necessary to string together search queries, landing pages, on-site behaviors and inquiry results, rather than just looking at one data source.

Whether the website has AI search citation conditions

You can check the company and brand entities, answers to procurement questions, product parameters and conditions, form steps and FAQs, authors and update times, certification cases and data, crawl status and topic content clusters. These factors can improve the conditions for being understood and cited, but there is no guarantee that a certain AI platform will definitely mention the website.

FAQ

Can ChatGPT analyze the website by providing only the URL?

Yes, but it is suitable for public page diagnosis. It can check positioning, content, structure, basic SEO and inquiry paths, and cannot confirm real traffic, ranking, indexing and conversion based on the URL alone.

When analyzing a website, which one is more important, GSC or GA4?

The two solve different problems. GSC reflects Google search display, click and query performance, and GA4 reflects the user's behavior after entering the website. To analyze the relationship between SEO and inquiries, they usually need to be used at the same time.

Are the data from Ahrefs and Semrush still useful?

Useful, especially for competitor research, keyword discovery and trend comparison. However, third-party traffic is an estimate and should be marked separately from the real data on the website's backend.

Can ChatGPT accurately determine the number of Google inclusions?

The URL alone won't work. The GSC web page index report, Sitemap status and key URL inspection results should be provided, and then analyze which important pages are not indexed and their possible reasons.

Can a final conclusion be drawn by uploading data once?

Not recommended. Check files, fields, dates, missing values, and data size before starting analysis. If there is a problem with the input data, it will be meaningless no matter how complete the subsequent report is.

Can CRM data be uploaded directly?

Unnecessary personal information and commercially sensitive information should be deleted first. Usually retaining the country, product, source, landing page, inquiry quality and transaction status is enough to complete most website conversion analysis.

How often is it appropriate to analyze a website?

Key websites can check GSC, GA4 and inquiry changes every month, and conduct a complete page, structure, content and competitor analysis every quarter. When the website is revised, traffic drops significantly, or new product lines are added, it should be reviewed separately.

Conclusion: Starts with three sets of data

It is the first time to use ChatGPT to analyze independent foreign trade websites. There is no need to upload dozens of data at the beginning. First prepare GSC query and page data for the past 6 months, GA4 landing page and key event data for the same period, and a complete list of website URLs.

After uploading, let ChatGPT check the file and data size first, and don’t rush to conclusions. Wait until it can clearly explain which are data-proven issues, which are just page inferences, and which still need to be verified, and then start formulating a 30-day optimization plan.