Himanshu Sharma’s Post

🤯 I stopped blocking all AI chatbots from using my website content. It's useless. Because they find a way to use it the other way but this time without citing you as the original source. The end result, you get more AI traffic. #Chatgpt is now the number 1 referring website for my blog. Most of the referral traffic is now from AI chatbots. I predict organic search traffic will continue to decline as AI gains popularity and will be replaced by AI traffic. The reality is that if AI chatbots do not mention your brand, you are done. They are becoming the new search engines.

💡 Here is the correct way to set up cross-domain tracking between two different websites with separate #GA4 properties, which even Google is not aware of. 👇 Let us suppose you have two different websites: www .optimizesmart. com and www .eventeducation .com . Both of these websites have their own separate GA4 properties. You want to set up cross-domain tracking between them. . . If you follow Google's advice, you will need to use the same GA4 property and the same web data stream for cross-domain tracking. But you have separate GA4 properties for each domain. So, you will have to reinstall the GA4 tracking for one of the domains involved in cross-domain tracking so that both domains use the same measurement ID. . . However, this is not a practical approach, as many users want to keep separate GA4 properties for each domain and may not want to consolidate them just for cross-domain tracking purposes. . . What you should do is set up a new GA4 property that uses the same Google tag for both domains. Instead of consolidating two GA4 properties into one and reinstalling the GA4 tracking for one of the domains involved in cross-domain tracking, create a third GA4 property that will be used exclusively for the purpose of cross-domain tracking. . . Send GA4 data from both properties into this new GA4 property and then add both domains to the ‘Configure your domains’ section of the new GA4 property. That way, you can set up cross-domain tracking while also keeping separate GA4 properties for each domain. I tested this approach, and it worked. . . Benefits of this approach: 1) Maintains Separate Data – Your original GA4 properties retain their individual data for each domain, allowing for independent analysis. 2) Centralized Cross-Domain reporting – The new cross-domain property acts as a central hub, collecting data from both domains and providing insights into user journeys across them. 3) Flexibility – This method does not require consolidating historical data or reinstalling tracking tags, minimizing disruption.

🤔I also have a similar theory about LinkedIn. The user engagement is not what I hoped for, considering the massive follower count. Shadow banned on X and shadow banned on Linkedin or I am serving the bots. If you don't like, comment or share, there is really no incentive for me to continue. Just being honest here.

💡 4 simple steps to exclude subdomain traffic in #GA4. 👇 1) Make sure that your primary domain and subdomain do not use the same measurement ID. 2) Make sure that you haven’t added the subdomain as an additional data stream in the GA4 property meant for your primary domain. 3) Use a different Google Tag and GA4 property to track your subdomain traffic. 4) Do not set up cross-domain tracking between your main domain and the subdomain you want to exclude.

💡 GA4 Tip >> Here is how you can determine whether a website uses Server Side (SS) tagging. 👇 1) Do you see a cookie/consent banner on the target website? If not, is the website based in the Western world, esp. EU? If yes, the website is likely using SS Tagging. Many SS tagging users foolishly believe they no longer need user consent as they are not placing third-party cookies on users' browsers. . . 2) To confirm the SS tagging on the target website, follow the steps below: Step-1: In Google Chrome, right click on a web page and then select 'Inspect'. Step-2: Click on the 'Network' tab and search for '/collect'. Step-3: Click on the search result that starts with '/collect?V=2'. Step-4: Look at the request URL under the 'Headers' section. The request URL will not start with something like 'https ://region1 .google-analytics. com/g/collect?' but will start with a subdomain like 'https ://sgtm .abc. com/g/collect?v=2' That's a strong indication that the website is using SS tagging. . . Step-5: Click on the "Application" tab in the Developer Tools panel. Step-6: Expand the 'Cookies' section. Step-7: Click on the website's domain you are investigating. Step-8: Locate the FPID cookie.  . . Step-9: Once you find the FPID cookie, look at the "HttpOnly" column. It should display a checkmark (✓) if it's set to true. If you find an FPID cookie with the HttpOnly flag set (checkmark in the HttpOnly column), it's a strong indication that the website is using SS tagging. Step-10: Install and activate an ad blocker extension in your web browser and visit the target website. If the website still manages to send tracking events (like page views, add to cart, etc.) despite the ad blocker being active, it might be using SS tagging.

🤔 FAQ: How do I know whether my #GA4 property collects modelled data? In your GA4 Admin, navigate to 'Reporting Identity' under 'Data Display' and look for the following notification (in the screenshot). Don't be surprised if data modelling is not available for you. Very few GA4 properties qualify for data modelling.

🤖 Advanced AI Traffic Analysis Reports in #GA4 👇

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💥 🛑 Moving to first-party data collection is nonsense in terms of privacy compliance because you are still collecting third-party non-essential data but now in a first-party context. The nature of the data collection often remains the same, even if it is done in a 'first-party' context. When companies shift from third-party to first-party data collection, the data collected often includes the same type of non-essential, tracking-based information that third-party cookies would have previously collected.  . . In this context, the main privacy concern is not eliminated; it is simply reframed as 'first-party data collection.' Whether the data is collected by a first party or a third party, the real privacy issue lies in how the data is used, how much control users have over it, and whether they are aware of its collection. . . Many websites that claim to use "first-party" data are still sharing that data with third-party vendors or services (e.g., Google Analytics, Facebook Pixel), even if the data is collected in a first-party context. In other words, user data is still being funnelled to third-party service providers, but now it’s happening through the first party as an intermediary. . . There are only two categories of data collection in terms of privacy compliance: Essential and Non-essential. Essential data collection is necessary for a website or service's basic functionality or security (e.g., session management, fraud prevention). Non-essential data collection refers to data used for purposes like marketing, analytics, personalization, and tracking, which aren't required for the core operation of a website but are often used for business or optimization purposes. . . Which means, Not all first-party cookies (like Google Analytics cookies) are essential cookies. Not all third-party cookies are non-essential cookies. Not all first-party data collection is privacy-compliant. Not all third-party data collection is bad for privacy. . . The data collection method (first-party vs. third-party) is not the most important factor in privacy compliance. What truly matters is the purpose and necessity of the data being collected. . . >> Instead of moving to first-party data collection, focus on privacy-driven data collection. It emphasizes that privacy is the priority, regardless of whether the data comes from first-party or third-party sources. Stop being obsessed with first-party and third-party distinctions. Focus on privacy-driven data collection. [That's like a keynote talk I shared with you for free. You don't need to travel to a conference to get such a gem of insight. Just follow me. 😁 ]