How can you proactively identify and resolve SEO issues with anomaly detection?
If you want to optimize your website for search engines, you need to monitor and analyze your SEO data regularly. But sometimes, you may miss or overlook some important signals that indicate a problem or an opportunity. That's where anomaly detection comes in. Anomaly detection is a data science technique that helps you identify unusual or unexpected patterns in your SEO data that may require further investigation or action. In this article, you will learn how to use anomaly detection to proactively identify and resolve SEO issues and improve your website performance.
Anomaly detection is the process of finding outliers or deviations from the normal behavior of a data set. Anomalies can be caused by various factors, such as errors, fraud, changes in user behavior, seasonality, or external events. Anomaly detection can help you discover and understand these factors and their impact on your SEO metrics, such as traffic, conversions, rankings, or crawlability. Anomaly detection can also help you avoid false alarms or irrelevant fluctuations that are not significant for your SEO goals.
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La notion d'anomalie pour un site internet est définissable de plusieurs manières. La première et la plus évidente est de faire confiance au consortium international W3C : celui-ci met à disposition des propriétaires de sites internet des outils permettant de valider le respect des normes de codage HTML en vigueur. Moins d'erreur Javascript, moins d'erreur HTML. La seconde manière est d'utiliser des outils en lignes tels que Semrush, Ahref ou encore Majestic SEO. Ceux-ci vont scanner votre site afin de vérifier que les pages ne retournent pas de code erronés comme des erreurs 404 ou des erreur serveurs.
To use anomaly detection for SEO, you need to have a reliable and comprehensive source of SEO data that covers different aspects of your website, such as content, technical, links, and user signals. You also need to have a clear definition of what constitutes a normal or expected range of values for each SEO metric. Then, you need to apply an anomaly detection algorithm or tool that can compare your actual data with the expected range and flag any anomalies that exceed a certain threshold or level of confidence. There are different types of anomaly detection algorithms and tools available, such as statistical, machine learning, or rule-based methods.
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La notion de site sans anomalie selon les moteurs de recherche est clairement définie, notamment par Google à travers son guide pour les webmasters. Suivre ces recommandations à la lettre permet de présenter des sites fonctionnels aux internautes ainsi qu'aux moteurs de recherche et donc son positionnement dans les résultats de recherche.
Once you have detected an anomaly in your SEO data, you need to investigate the root cause and the impact of the anomaly. You need to ask questions such as: What is the source of the anomaly? When did it start and how long did it last? How did it affect your SEO performance and KPIs? What are the possible explanations or hypotheses for the anomaly? How can you verify or test your hypotheses? How can you fix or prevent the anomaly from happening again? Depending on the nature and severity of the anomaly, you may need to take different actions, such as fixing a technical error, updating your content, adjusting your strategy, or informing your stakeholders.
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Il est important de comprendre le type d'anomalie parce qu'il a des anomalies spécifiques à une seule page et des anomalies qui vont se répercuter sur des milliers, simplement parce que l'anomalie provient d'un problème dans le modèle de fichier par exemple ou parce qu'une règle logique d'affichage a mal été définie. Il est primordial de s'atteler d'abord aux anomalies qui touchent le plus grand nombre de pages parce qu'avec une simple correction on peut impacter une grande parties des anomalies.
Anomaly detection can help you gain valuable insights and advantages for your SEO efforts. Automating the detection of SEO issues and opportunities saves time and resources, while reducing noise and bias in data analysis increases accuracy and confidence. Anomaly detection also enhances creativity and innovation by discovering new patterns and trends in your data. Lastly, it increases agility and responsiveness by quickly reacting to changes in your data and the market conditions, allowing you to stay ahead of competitors.
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Corriger les anomalies sur votre site web permet : - de réduire son temps de chargement - de réduire sa consommation énergétique - de faciliter sa navigation et sa compréhension par les internautes - de faciliter son crawl par les moteurs de recherche - de permettre un meilleur positionnement dans les résultats des moteurs de recherche
If you are interested in using anomaly detection for SEO, you can start by exploring some of the tools and resources available online. For example, you can use Google Analytics' Anomaly Detection feature, which automatically detects and highlights anomalies in your traffic and conversion data. You can also use Google Search Console's Performance report, which shows you how your site performs in Google Search and alerts you of any issues or changes. You can also use third-party tools or platforms that offer anomaly detection capabilities for SEO, such as Moz, SEMrush, or Screaming Frog. Alternatively, you can build your own anomaly detection system using Python, R, or other programming languages and frameworks.
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