The Seotistics newsletter is written by Marco Giordano, a Data/Web Analyst with the goal of combining business and web data. Tired of the usual boring Analytics content without any business impact? Seotistics teaches you how to use Analytics, web data and even content in your workflow while helping you with Strategy.
☠️ 5 Data/Strategic Mistakes That Destroy Your SEO Projects
Use Data Or Be Used By Data!The December 4 issue of Seotistics is here for you! |
The last 2 Seotistics issues have been talking about learning Analytics and doing projects. Fair enough but first of all you need solid foundations to understand some basic theory. Today I show you some examples of how bad knowledge in decision-making can make your life impossible. Please move this email to your Primary inbox or reply to it. This is to prevent Seotistics goes into spam by accident. Gmail users can read this tutorial to do it. #1 Data TrapsGoogle Search Console and Google Analytics 4 are tricky tools. For many non-SEOs, it's even better to use 3rd-party data, which is even harder to make sense of. People use Search Volume, Avg. Position and Impressions carelessly and don't even bother reading the official docs. This leads to fatal mistakes and incorrect reporting, e.g. "A page with an Avg. Position of 6 is classified as weak, while it's actually being shown in a Knowledge Panel (which is great)" "Search Volume used to qualify keyword quality"
The other common trap is not understanding sampling and the differences between data sources. Downloading GSC data manually is NOT the same thing as using the API or the BigQuery bulk export. Building a reporting system based on manual exports is the recipe for failure. The solution to this is building a data dictionary, a magical document where you write all of the caveats to pull and combine the data + the interpretation. N.B. Did you know that CTR and Avg. Position aren't available by default if you use bulk export? Now you know it. #2 The Time PitfallIn finance, you may have heard about opportunity costs. If instead of updating an old cluster, you would write a new one, which would be the better option? Many owners rush to publish new content and don't update their old material because they think there is no gain in doing so. Think again, does it cost more time (and possibly resources) to write new articles or to update old ones? This goes case by case but you can say that in 90% of the cases updating content takes less time than writing from scratch. Now I ask you, is it worth spending 4 hours updating meta descriptions? Answer: probably not. For low-adding value tasks, use automation, Python is your friend. The opportunity cost of 4 hours can be invested into more profitable activities, so what moves the needle. In SEO, it's the same, there are high opportunity costs:
⏳ Optimizing TimeSEO means being torn by different choices and limited time/budget. Guess what? You need to choose. The example below shows a very common use case: Time it takes to perform an SEO task: 4 hours per week Automation script: 10 hours to produce? This is under perfect conditions, assuming you can craft something ready for use in only 10 hours. There is a striking convenience in moving forward with the solution. Those who think time isn't a KEY element in SEO are fools. Timeliness and execution speed are what make you money. Now, let's see a more realistic use case. You need to build a solution to monitor SEO performance. In many cases, you can get away with Looker Studio and call it a day. If you are interested in a custom SaaS, things get a little bit different. So you'd look at the following values:
Many often ignore time but it's a crucial point in Analytics (and accidentally SEO). Making faster important decisions is key to winning and slow decisions are often pointless in many instances. #3 Statistical ProblemsWhy do most SEO case studies don't make any sense? Think about it. Why correlation doesn't equal causation? This is also a popular one. These are some of the most frequent questions in the SEO industry and why you need some foundations in Statistics. Many often skip numbers altogether and only focus on software development. This is perfect if you just want to build a SaaS or a tool but terrible for analysis. The majority of SEO case studies are Observational, meaning that you can simply see if there is a correlation (at most). Using GSC Data to do some good ol' Analytics is what you would define Observational. Experimental studies take it to the next level and can be used to prove causation. These are rare in SEO but an example could be testing the impact on rankings if we change title tags. Oh wait, this topic was described by Giulia Panozzo in her talk. Do yourself a favor and read this. In short, do NOT:
HCU hit a lot of websites indiscriminately, there is no scientific and ultimate proof it hit those with a blog roll, for example. #4 Hindsight BiasWhy don't I read many Core Update analyses? Because of hindsight bias, one of the sneakiest biases ever. "I knew this website was going to be hit, the content is bad" Stating you were right and you knew it after something happened. You didn't know before, you validate your idea after the outcome is known. Many bad websites don't get hit and you hardly see people commenting on them. It's easy to evaluate an event that already happened and state your opinion but this is wrong. The HCU showed how strong hindsight bias is. Is it possible that everyone knew in advance which sites would've been hit? Data analysis and content planning are 2 cases where hindsight bias does the most damage: "I have always been sure this cluster would have performed greatly" and when it doesn't, you blame Google. Overrating your predictive abilities makes up for a great deal of problems. Always think twice before evaluating an outcome and ask yourself if you knew before. #5 Accumulating DebtCrazy Python scripts won't save you from debts inside a company. Some may say tech or SEO debt but I think that content debt is much worse. Imagine having 1000 articles and no one cared to update them in 10 years (oh, this actually happened!). Thin or outdated content hinders your organic performance but let's forget about SEO for a minute.
To update articles, you have to:
This should be one of your main interests in Analytics, not simply how to automate processes or to pull GSC data (which is obvious). I will talk more about Content Management in the future because it's a key area where many companies still fail. Needless to say, it intertwines with SEO and Data quite well. What You Can Do TodayIf you want some quick takeaways and actionable things you can do today, here is what I recommend you:
Do this and you will thank me in no time. 👥 Join Our CommunityOur Discord community offers a small place where we can talk business and SEO. If you hate all the noise of social media, then this place is for you.
🔎 Analytics For SEO Ebook (v6)This ebook is aimed at SEOs or Business Owners who want to explore the combination of SEO and Analytics. If you want to start building your data empire, this is the (initial) path to take. It will teach you or your employees to: 👉 Avoid common pitfalls that cost you money 💸 👉 Create meaningful analyses that add value 💯 👉 Shorten the learning time of Analytics ⏳ This comes with monthly updates because I want to create the Ultimate Guide out there. v6 includes the following information: ✅ Strategy in terms of SEO & Data ✅ Decision Making ✅ Integrating Data with SEO
v7 will include additional info on DataViz and topics on request. 📚 Recommended Reads - Peak Content 🗻Peak resources even today and this time we mix things a little bit and check some invaluable ones:
📞 One-Hour CallIf you have doubts about SEO or Analytics, you can book a call with me. Have doubts about your content website or with your data? Look no further, I can help you:
❗️ Feedback and RecommendationsIf you have ideas/recommendations for the next issues of Seotistics, you can simply reply to this email. Marco Giordano Follow me on 🔽🔽🔽: |
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Seotistics - Web Analytics + Business + Strategy
The Seotistics newsletter is written by Marco Giordano, a Data/Web Analyst with the goal of combining business and web data. Tired of the usual boring Analytics content without any business impact? Seotistics teaches you how to use Analytics, web data and even content in your workflow while helping you with Strategy.
Use Data Or Be Used By Data! The October 26 issue of Seotistics is here for you! You read a lot of stuff online decreting the end of SaaS, GA4 and whatever due to AI. Most of it is wrong and shouldn't affect your work or career. I will show and explain you why. Just came back from Athens from SEO On Stage, will post more details on LinkedIn. Please move this email to your Primary inbox or reply to it. This is to prevent Seotistics goes into spam by accident. Gmail users can read this tutorial...
Use Data Or Be Used By Data! The October 19 issue of Seotistics is here for you! I am just back from Rome and AI didn't sleep, we are full of news and updates. As you know if you are working with automation, you need to know this stuff! As I try to recover from multiple conferences in a row, here is the latest summary of what's going on. Most of these topics will be expanded in the next issues as they are too new 💀 Please move this email to your Primary inbox or reply to it. This is to...
Use Data Or Be Used By Data! The October 12 issue of Seotistics is here for you! Measurement did change in the last year and I am here to remind you some basic facts. AI is for sure one of the main culprits but not the only one. I am also writing a huge article on LLM measurement, stay tuned 👀 Hectic week, too much to do, including course updates. Please move this email to your Primary inbox or reply to it. This is to prevent Seotistics goes into spam by accident. Gmail users can read this...