Ivan Palii 🇺🇦

10 things you have to figure out yourself if you decide to build the SEO monitoring platform for your agency with AI, to save $200/mo: 1. BigQuery export for GSC data starts empty. No year-over-year report for the first 12 months unless you build a second pipeline to backfill from the API 2. Build a reconnect flow for 30+ client Google accounts: different owners, revoked access. 3. Write URL rules for joining GSC and GA4: http/https, www, trailing slash, uppercase, UTM params, , GA4 path vs. GSC full URL, domain vs. URL-prefix property. 4. Write tests that compare your numbers to the native GSC and GA4 UIs for every client. 5. Build a settings UI for page segments, keyword segments (brand / non-brand, topics) and target URLs in rank tracking. 6. Set up separate access levels for owners, employees and clients. 7. You need a SERP API and a cost model for keyword × location × device × day. 8. Every time Google adds a new way to block the SERP parsing, positions shift and the parser breaks. Someone has to find the time to fix it this week, not next quarter. 9. Build pre-aggregated reports for common questions. Otherwise the LLM pulls raw rows every time and you get high token bills and overflowing context. 10. Keep up with GSC/GA4 API changes + have a plan for when a person who built it leaves. What did I miss? I bet building and maintaining such platform will have a negative ROI for you. Instead, try Sitechecker. We solved all the above and fix issues in days if they appear on Google side. Sitechecker gives Claude your GSC, GA4, rankings, AI visibility, site content changes and technical audit in 1 connector. Unlimited users. Unlimited API & MCP. Try for free for 2 weeks -> sitechecker.pro/ Get peace of mind and focus on delivery for your customers.

Our data study shows that 74% of SEO agencies don't use AI tools for reporting. I have a hypothesis why agencies don't trust AI tools in this job yet 42%! still use Google Docs/Slides and 32% still use Looker Studio. While reporting is one of the most important touches with your customer, it has 2 big pifalls: 1/ Any inacuracies in data can kill a trust to your agency and the work you've done 2/ A good reporting involves too many context. You have not just show that some metrics improved, but also: - what you've delivered - which of your hypotheses worked and which don't - which specific page segments and pages were winners and losers and why - what was the impact of external changes (Google and LLMs updates) on metrics This is hard. If you include only high level metrics in reporting you say NOTHING. You've added a lot of data sources to your AI tools, and it helps in quick answers and analyses, but for reporting this is still not good enough. The environment changes, topics we target change and the work we do also change. AI still miss part of this context. If you do it in Looker Studio, you also know well about all the limitations on data blending, maintaining, constant errors in data loading. That's why we designed our own reporting tool at Sitechecker. It allows you to include performance by highly specific metrics (page segments, pages, keywords) from different sources (rankings, AI citations, GSC and GA4), add notes and send it to multiple users. If you aren't satisfied with your current reporting workflow, let me know and I'll share an interactive prototype with you.

Better to see a picture once than to read text from Claude for a minute. What type of analysis you would like to do in AI chats and what in tools itself? In my case, it's page audit. Yes, Claude will find you similar insights, but it will present it in tables and you'll have to read a wall of text. Instead when I use native UI at Sitechecker, I can detect many insights in one view: - the spike in clicks and impressions - the spike in impressions by only one keyword - how the average position by top ranking keywords changed - did the content of this page have changed for the last 90 days - whether we already have conversions by this landing page in GA4 What about you? Have you completely switched to AI assistants interfaces? P.S. Now I have 2 hypotheses why there is so huge spike by "se ranking alternatives": bot requests from rank trackers / AI tracking tools or real users because rank tracker at SE Ranking didn't work for a lont time.

If your SERP tracking tool is broken again because of Google's new limits on resolving /goto URLs, remember there is a platform that will give you peace of mind.

Building your own SEO reporting with MCPs feels amazing for about 2 weeks. No devs, no SaaS bill that goes up every year and you built it yourself. Then the 6th client signs, then the 15th client. Every client means more wires: GSC, GA4, rankings, AI visibility, site health, content changes. Separate connectors, separate auth, separate API limits. And suddenly you’re the guy who: - fixes a connector that silently broke; - explains to a client why last week’s numbers changed; - is the only person on the team who knows how it all works. When we polled our customers about building reporting with AI, the AI wasn’t what broke, the data connections were. So we built Sitechecker MCP: one connector instead of five, for every client site. Pipe it into Claude Code, ChatGPT Codex or your own tools. Keep the AI. Lose the wires.

Sitechecker MCP is live. It checks GSC, GA, rankings, AI visibility & site changes. 5 reasons it beats DIY MCP setups: 1/ The numbers are correct When you connect Search Console to AI assistant directly, the AI receives only the top rows of your data. Google also hides anonymized queries. So when you ask for last month’s clicks or CTR, the AI adds up an incomplete list and gives you a number that looks right but isn’t. In Sitechecker, totals are calculated on our side, the same way the Performance report does it. The AI gets the final number and just explains it. 2/ Most of the analysis is already done We calculate page segments, keyword cannibalization, new and lost keywords, and GSC + GA4 conversions in advance. You set up segments once in Sitechecker, and they work in every chat. Without this, the AI has to pull thousands of raw rows and rebuild the same logic every time you ask, and that’s where most made-up insights come from. 3/ You get history that Google doesn’t store Search Console doesn’t record your daily rankings, whether you appeared in AI Overviews last month, which pages ChatGPT cited, or what changed on a page before traffic dropped. Sitechecker records all of this. So when a client asks why traffic fell, your AI can check what changed on the site and in the SERP during the same week. 4/ All client sites in one place If you manage 20 sites with separate MCPs, the AI has to figure out which GSC property, GA4 property and rank tracker project belong to the same client. In Sitechecker, each client is one project, with all data sources already connected to it. You just name the site. 5/ Setup takes one URL The official Google Analytics MCP needs a Google Cloud project, enabled APIs, credentials and Python on your machine. Other tools need their own API keys. With Sitechecker, you paste one server URL into Claude, ChatGPT, Cursor or Codex and sign in with your account. Want to try it for free for 2 weeks?

Next Tuesday I'll speak on a hot topic: how to grow a Reddit community for B2B brands. This is a free AI SEO Webinar, organized by Search Engine Watch, includes 3 sessions. 1/ @seosmarty will share how to measure and improve brand reputation to improve AI visibility. 2/ Kevin Lee will share how choose tactics that both lift AI visibility and pay off on their own. 3/ Join my session to learn about: - 3 reasons to build a Reddit community - For which brands it makes no sense to create a subreddit (it's definitely not for everyone) - Why the drop in Reddit citations in LLMs doesn't mean that Reddit became less valuable - The metrics I aim for in 1-3-6 months, launching a community - 5 methods to speed up the growth of the community - The biggest pitfall of growing a Reddit community Register here: searchenginewatch.com/events…

What's changed in SEO and AI visibility reporting at your agency over the last year? Some have built their entire reporting process using AI and cancelled popular SEO platforms. Others have tested AI but returned to their previous tools. If you are curious about how reporting approaches have evolved at other agencies, or if you are facing significant challenges in this area, please take part in my survey. sitechecker.typeform.com/to/… I've created a short survey with 5 questions (each with a ready to choose list of answers). - What has changed the most in your delivery and operations this year? - Which tools did you cancel or stop using this year? - Which new tools did you start using this year? - Where do you build client reporting now? - If you’ve tried building SEO or AI visibility reporting with AI, what were the biggest issues? Take 2 minutes to take part and find out how reporting is changing among SEO agencies.

4 red flags that make me deny buying or exchanging a brand mention on the website: 1/ they suggest renting the mention, not a permanent placement; 2/ their site is completely AI-generated, with no additional value; 3/ their site is cited in LLMs, but has almost 0 traffic in Google; 4/ the site has bad content formatting and low-quality editing policies. what's your red flag?