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Do you know what SERP is used for in technical marketing? 🤔 👉SERP (i.e. search engine results page) is used for analyzing how well your website or content ranks in search engines like Google. 👉In technical marketing, SERP insights help marketers understand the visibility of their content, identify which keywords are driving traffic, and monitor competitors’ rankings. By optimizing for SERP features (like snippets, videos, and featured links), marketers can improve click-through rates (CTR) and drive more organic traffic to their websites. 📚Read more about SERP and digital advertising concepts in our Technical Marketing Handbook, a free online resource for anyone interested in Technical Marketing! Visit handbook.teamsimmer.com to start learning. 💬 Did you find this post useful? Share your thoughts in the comments below. 🙂 #teamsimmer #technicalmarketing #serp #serpoptimization #seo #technicalmarketinghandbook

Are you familiar with our “Chrome DevTools for Digital Marketers” course? 💻 The DevTools suite in Google Chrome is one of the most powerful toolkits for technical marketers! 🔧 With DevTools, you can inspect, manipulate, and test various marketing technologies right on any website. But don’t just take our word for it, Gerry's success with DevTools says it all. 👏 Head over to teamsimmer.com to explore the course and start mastering these essential skills today! 🚀 #teamsimmer #technicalmarketing #chromedevtools #marketinganalytics #testimonial

There's a new blog post on Simmer Blog! 📣 In this post, Simo walks you through "How to use the Firebase SDK to send app data to server-side Google Tag Manager." 👉 Learn step-by-step how to configure Firebase's powerful SDK to streamline your app's data flow directly into GTM's server-side container. This is a must-read for anyone looking to optimize data tracking and improve app performance! Check it out now and take your technical marketing skills to the next level! 💫 Link in the comments below. #teamsimmer #technicalmarketing #firebase #googletagmanager #serverside #tutorials #marketing #googleanalytics #marketinganalytics

5 Tips for Cost-Efficient BigQuery Usage 💡 When working with BigQuery, keeping an eye on query costs is key to managing expenses effectively. Here’s how you can save: 1️⃣ Check your estimated costs first – As you compile your SQL queries, make sure you focus on the little preview text in the top-right corner of the query interface. This will always tell you how many bytes will be processed if you were to run your query. If those bytes are in the range of hundreds of gigabytes, you might want to consider formatting your query to be less costly. 2️⃣ Query only what you need – By far the best way to keep your query cost down is to only query tables and columns that you need. Use the WHERE clause liberally – this is how you confine your query to only pull data from the columns that you actually need. 3️⃣ Limit partitioned tables – Similarly, if you’re querying a sharded or partitioned table, you can use the WHERE clause to limit your query to only certain tables or partitions. 4️⃣ Avoid “SELECT *” – You often hear about the destructiveness of the “SELECT *” statement. While BigQuery does optimize queries that span your entire table, it’s still important to delimit these broad statements with an appropriate WHERE clause. 5️⃣ Use the Preview feature – Even better, if your sole purpose is to explore the source table, use the Preview feature in BigQuery studio that lets you scan the full table data at no cost at all. Was this helpful? Share your thoughts in the comments! 😊 #teamsimmer #technicalmarketing #bigquery #marketingbudget #querytips

📣 Upcoming talks by Simo Ahava 📣 If you're around, make sure you don't miss these talks by Simo this week. 1️⃣ Digital Analytics Summit, Amsterdam, 10th October 2024 🇳🇱 Simo will deliver the opening keynote, titled "Out of the frying pan, into the fire". It's a cynical but also eye-opening talk about the state of our (technical) digital analytics industry. Simo will discuss the cult-like chase for "more data" at all costs, as he reviews some of the most recent trends that affect our work as analysts. The event is sold out, but if you've already got a ticket, come say hi! 2️⃣ MeasureSummit, 9th–11th October, 2024, virtual event Simo's talk will be on Friday, and it's going to be all about "Data stream consolidation with server-side Google Tag Manager". Grouping those data streams together is one of the most important use cases of server-side tagging, and Simo will share examples and useful tips on how to work with this approach. You can still get tickets: 🎉 All-Access Pass => https://lnkd.in/dsjih8fQ 🎁 Free ticket => https://lnkd.in/dUvYctCf

Why bother learning BigQuery and SQL when AI tools like ChatGPT can give you the SQL code with a simple prompt? 🤔 This question makes the rounds quite frequently, and it’s a good one. ChatGPT and other LLM systems are getting more and more proficient with not only producing solid code but also understanding the underlying data schema, especially if it’s a popular and public one like Google Analytics 4. 🤖 If your only goal is to produce SQL code, then there’s probably very little reason to go beyond prompting for those queries. It’s like being a tourist abroad, equipped with just a tourist dictionary that gives you the phrases that you most often need. That’s quite enough for ordering food and asking for directions to your hotel. 💡 However, SQL is more than just a language. It’s also an approach for storing, structuring, and modeling data. Understanding how SQL can be used efficiently on the datasets you use on a daily basis can be vital for producing analyses that go beyond simple, prompted reports. 🧑🎓 To continue the tourist phrasebook analogy, by learning BigQuery and SQL yourself, you’ll be able to communicate with the locals more fluently, you’ll be able to avoid traps based on cultural differences, and by engaging in genuine dialogue with the locals, you’ll be able to find conversation paths that you wouldn’t have spotted otherwise. ➕ You’ll also be able to build richer prompts for the AI systems. Understanding the logic behind the queries allows you to instruct the AI more precisely, leading to more accurate and efficient results. 💬 Thoughts? Share them in the comments section below! #teamsimmer #technicalmarketing #sql #marketinganalytics #chatgpt #ai #googleanalytics

Team Simmer at Nordic Business Forum today and tomorrow - we’re taking in all the insights and finding inspiration from great leaders such as Adam Grant, Brené Brown and Liz Wiseman 🤩🤩✨ #teamsimmer #nordicbusinessforum

What is the difference between Google BigQuery, SQL, and the Google Analytics 4 BigQuery export? 🤔 These three concepts are often mixed up or used interchangeably, but they shouldn’t be. Here’s a short summary of the differences. 👇 1️⃣ Google BigQuery  BigQuery is Google’s scalable cloud data warehouse. It’s a fully managed storage and query system for your structured data. It comprises automation that handles infrastructure, computation, and data access for you, so that you don’t have to worry about any of those things. 2️⃣ SQL in BigQuery Structured Query Language (SQL) is the language used to interact with data stored in BigQuery. SQL allows you to query and manipulate the data and extract meaningful information from your datasets within BigQuery Studio. 3️⃣ Google Analytics 4 BigQuery Export The Google Analytics 4 BigQuery export is the name of an integration between Google Analytics 4 and BigQuery. This integration automatically exports your daily Google Analytics 4 data into tables that are then stored in your Google BigQuery project. In summary: You open Google BigQuery to query data stored there by Google Analytics 4, assuming the BigQuery integration has been enabled. BigQuery Studio allows you to write SQL queries that access this GA4 data and combine it with other data sources (such as Google Ads) for a comprehensive view of your marketing channels. Did you find this useful? Let us know if you have any questions or comments. 🙂 #teamsimmer #technicalmarketing #bigquery #ga4 #sql #marketinganalytics #googleanalytics

🔔 The SIMMER NEWSLETTER has been sent to 10K+ inboxes just now. 🔔 If you haven't already, make sure you subscribe at https://lnkd.in/d6e7Ysi Here are the topics of the latest edition: 📣 See (and hear) Simo speak at some upcoming events: 1️⃣ MeasureSummit, October 9–11 (virtual). Get the All Access Pass at an early bird discount (https://lnkd.in/dUvYctCf) or register for free (https://lnkd.in/dsjih8fQ) 2️⃣ Digital Analytics Summit, October 10 (NL). Get your ticket with a 20% discount by using the code SIMOSPEAKS (https://lnkd.in/eCbT846S) 3️⃣ Piwik PRO Day, October 22nd (virtual). Join for free at https://lnkd.in/dYsz7ZSj. ⚖️ Yelp files an anti-trust lawsuit against Google. 📲 Report emerges that attributes some truth to the conspiracy theory where phones listen to what you say and sell the data to advertisers. 🔎 Google introduces Confidential Matching technology to secure first-party data flows. 👋 Google Cloud deprecates "Integrations", a very useful feature for Cloud Run setups. Remember to subscribe at https://lnkd.in/d6e7Ysi

What’s the Difference Between Server-side Tagging and Server-side Tracking? 🤔 Although “Server-side Tagging” and “Server-side Tracking” are often used interchangeably, they’re actually distinct concepts, with some overlap. 👉 “Server-side Tracking” quite literally means “tracking that happens server-side”. In other words, it’s a tracking process that doesn’t involve a client device operated by a user. Examples include sending events from the CRM to an analytics or advertising vendor, collecting telemetry data from your backend processes, or parsing log files and ingesting that information into a data warehouse. 👉 “Server-side Tagging” is broader. It can be described as a single input expanded into one or more outputs. In the web, this would be a Data Layer event detected by the tag management system, which then fires tags to send this information to vendors. The overlap? You can “track” data server-side and then use server-side tagging to distribute it to various systems. While browsers and devices are the typical request sources in server-side tagging, you could just as well fire the tags when a server-side request comes in. Did you find this useful? Let us know if you have any questions or comments. ☺️ #tagging #tracking #serverside #simmer #KeepLearning #TechnicalMarketing