Data-Driven SEO: Correlation Does Not Equal Causation
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Data-Driven SEO: Correlation Does Not Equal Causation Talk for Mississippi State University's Advanced Statistics Class, 11/2020 TLDR: https://starwarsintrocreator.kassellabs.io/#!/CMLLbd91eqIcOecTDDtN SEO Resources: http://bit.ly/seo-tools-2018
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Data-Driven SEO: Correlation Does Not Equal Causation
- 1. Mississippi State 2020 1 What is Data-Driven SEO? Correlation ≠ Causation
- 2. Mississippi State 2020 Renee Girard 2 2011 UW-Milwaukee Business Marketing Undergrad 2012 - Early 2020 Agency-Side SMB to Fortune 1000s and Global 200s Today Client-Side Crate and Barrel Holdings (CBH) https://www.linkedin.com/in/reneegirard/
- 3. Mississippi State 2020 The process of improving your site’s free or organic rankings in search engines. 3 What is Search Engine Optimization (SEO)?
- 4. Mississippi State 2020 4 Source: https://web.dev/discoverable/
- 5. Mississippi State 2020 Anything in the Search Engine Result Page (SERP) not marked with the “Ad” or “Sponsored” label. 5 Where are the free or organic listings in Google?
- 6. Mississippi State 2020 How does Google Search work? 6Source: https://www.youtube.com/watch?v=tFq6Q_muwG0
- 7. Mississippi State 2020 Short Answer: It’s complicated. ¯_(ツ)_/¯ 7 How does Google determine rankings?
- 8. Mississippi State 2020 Long Answer: PageRank, DeepRank, and other search algorithms weight hundreds of different ranking signals to calculate a relevance score and probability distribution for each page. Google algos are updated 6X/day on average and rigorously tested by Search Quality Raters. 8 How does Google determine rankings?
- 9. Mississippi State 2020 Google’s Major Algo Releases Mobile First and Core Web Vitals Mobilegeddon, Mobile-First Indexing (MFI), and the need for speed 2018 - Today RankBrain and DeepRank (BERT) Machine learning for things, not strings Natural Language Processing (NLP) using neural- networks NL API Demo 2015 - 2019 Penguin Low quality, spammy links 2016 Panda Low quality, thin content 2015 Pigeon Local search and Google Maps 2014 Hummingbird Semantic search 2013
- 10. Mississippi State 2020 Google Ranking Factor Correlation Studies 10 Sources: Ranking Correlation Study using Polynomial and Linear Regression https://backlinko.com/google-ranking-factors
- 11. Mississippi State 2020 SERP Analysis Using Pearson’s Correlation Coefficient 11
- 12. Mississippi State 2020 SERP Analysis using Pearson’s Correlation Coefficient 12
- 13. Mississippi State 2020 SERP Analysis using Pearson’s Correlation Coefficient 13 Copy Meta Data Schema Indexing Crawl Links
- 14. Mississippi State 2020 The process of improving your organic rankings using both quantitative and qualitative data as the primary driver for decision-making. 14 What is Data-Driven SEO?
- 15. Mississippi State 2020 Qualitative Analysis SERP Analysis Competitive Analysis Customer Feedback and Reviews Google Assumptions Content Analysis Quantitative Analysis Impressions Clicks Rankings Click-Through-Rates (CTR) Crawl to Index Ratio Visits Revenue Competitive Gap Analysis Projections and ROI Search Demand and Google Trends Data-Driven SEO Data-Driven SEO
- 16. Mississippi State 2020 16
- 17. Mississippi State 2020 Correlation ≠ Causation 17
- 18. Mississippi State 2020 Data-Driven SEO Use Cases 18
- 19. Mississippi State 2020 ROI Calculation via BrightEdge Source: https://www.brightedge.com/resources/organic-search-roi-opportunity-calculator
- 20. Mississippi State 2020 Simple ROI Calculation via Click Curves & Google Sheets 20 Source: https://www.advancedwebranking.com/ctrstudy/ Source: https://www.searchenginejournal.com/calculate-roi-seo-targeting-keywords/380636/ Clicks / Impressions = Click-Through Rate %
- 21. Mississippi State 2020 Google Lighthouse Scores From Weighted Averages 21 Source: https://web.dev/performance-scoring/
- 22. Mississippi State 2020 Google Lighthouse Scores 22
- 23. Mississippi State 2020 Server Log File Analysis for Technical SEO
- 24. Mississippi State 2020 The Business Impact of Broken Pages (404s)
- 25. Mississippi State 2020 25 N-Gram Phrase Models Turn Written Language Into Data N-Grams are words, or combinations of words, broken out by the number of words in that combination. Sources: https://www.seerinteractive.com/blog/what-are-ngrams-and-uses-case/ https://blog.xrds.acm.org/2017/10/introduction-n-grams-need/
- 26. Mississippi State 2020 26 Keyword Analysis and Unigram N-Gram Models Free option: https://seodataviz.com/ngram.php
- 27. Mississippi State 2020 KPI Comps Report Automation via Google Data Studio 27
- 28. Mississippi State 2020 Statistical Computing and SEO R, Python, and Machine Learning 28
- 29. Mississippi State 2020 Python vs. R 29 Source: https://www.datacamp.com/community/blog/when-to-use-python-or-r
- 30. Mississippi State 2020 ML for SEO Automation and Faster Results 30 Source: https://www.searchenginejournal.com/machine-learning-seo/208415/ Artificial Intelligence Machine Learning Deep Learning
- 31. Mississippi State 2020 Google PageRank Calculations using R 31 Source: https://rdrr.io/cran/seoR/man/screamingfrog_internalPagerank.html
- 32. Mississippi State 2020 32 Search Intent Modeling and Funnel ClassificationIntenttoPurchase Source: Internal Google Data
- 33. Mississippi State 2020 33 Python and ML for Automated Search Intent Modeling Sources: https://venturebeat.com/2019/11/30/a-super-fast-machine-learning-model-for-finding-user-search-intent/ https://www.searchenginejournal.com/automated-intent-classification-using-deep-learning-google-sheets/353910/
- 34. Mississippi State 2020 TL;DR 34 1. SEO is defined as the process of improving organic rankings in search engines. 2. Google determines organic rankings through complex algorithms that weight hundreds of rankings factors. 3. Data-driven SEO is defined as SEO decision-making using both quantitative and qualitative data. 4. “Correlation does not imply causation” is very true for organic search. 5. SEOs use data for everything including getting buy-in through ROI calculations and estimated traffic projections, measuring KPIs, and keyword analysis. 6. SEOs can automate processes for faster results using machine learning algos, APIs, and computer programming languages like Python and R.
- 35. Mississippi State 2020 35 I have spoken. SEO 101 Resources: http://bit.ly/seo-tools-2018
Editor's Notes
- Excited to be here virtually with you all today! Fun fact: Met Professor France when undergrad bus student @UW-Milwaukee Attended a guest lecture like this one where I got to learn about SEO for the first time Looking back, that one class ended up completely changing my life forever I connected with the guest speaker after his talk and he ended up hiring me Agency-side for 8 years - loved it! Ready for in-house - love e-commerce! Client-side for 10 months now as Sr. Manager of SEO for a leading furniture retailer with 100+ nationwide stores
- What is the definition of SEO without saying Search Engine Optimization? [Wait for the class to respond] [1 min] My definition: The process of improving your site’s free or organic rankings in search engines. Google’s definition: to be easily discoverable to ensure users can find your site through search. Making sure search engines can FIND and automatically UNDERSTAND your content, you are improving the visibility of your site for relevant searches
- Google’s mission: to organize the world’s information and make it universally accessible and useful’ Google’s definition: to be easily discoverable to ensure users can find your site through search. Making sure search engines can FIND and automatically UNDERSTAND your content, you are improving the visibility of your site for relevant searches
- What do the free or organic listings look like in G? [30 sec] Anything in the SERP not labeled as Ad or Sponsored (generated by pay-per-click or PPC ads)
- How does G Search work? Why not hear it straight from G’s latest film - highly recommend [1.5 min] [Play film]
- Now that we’re all craving lasagna (thanks, G), how does Google determine who ranks #1 vs #2 and beyond? [1 min] Short answer: it’s complicated and no one really knows because G won’t tell us and if they did, I wouldn’t have a job! Long answer: algorithms based on mathematical instructions which weight 100s of ranking signals to output a probability distribution and relevance score Updated av. 6x/day and rigorously tested by people called Search Quality Raters Amount of complexity and signal flux makes correlation analysis extremely difficult
- ALGO = set of mathematical instructions kind of like a recipe Google’s algo = to return high-quality info based on a user’s query Now that we’re all craving lasagna (thanks, G), how does Google determine who ranks #1 vs #2 and beyond? [1 min] Short answer: it’s complicated and no one really knows because G won’t tell us and if they did, I wouldn’t have a job! Long answer: algorithms based on mathematical instructions which weight 100s of ranking signals to output a probability distribution and relevance score Updated av. 6x/day and rigorously tested by people called Search Quality Raters Amount of complexity and signal flux makes correlation analysis extremely difficult
- Major G algo updates = run different jobs to improve relevant results [1 min] Things have changed since I first started in SEO G no longer tells us when the algo is updating since so freq unless it is major release Named after animals More recent algos (2015-2019) use AI and machine learning to better understand search queries and Natural Language Processing (NLP) BERT = Bidirectional Encoder Representations from Transformers BERT models to understand search queries RankBrain = AI to transform written language into mathematical entities called vectors that the computer can understand October 25, 2019 BERT Update Google announced the BERT Update, calling it the biggest change to Google search in the past 5 years. Google uses BERT models to better understand search queries. Google said this change impacted both search rankings and featured snippets and BERT (which stands for Bidirectional Encoder Representations from Transformers) will be used on 10 percent of U.S. English searches. RankBrain uses artificial intelligence to embed vast amounts of written language into mathematical entities — called vectors — that the computer can understand.
- called vectors that the computer can understand Google Ranking Factor Correlation Studies = NERD SPECULATION/HOLD ONTO YOUR TIN HATS PEOPLE [1.45 min] SEOs love to try and reverse engineer the algos to figure out the secret sauce That means correlation studies where data scientists analyze tens of millions of search results to garner key takeaways based on pos/neg correlation trends Data mining APIs for third party data Data analysis using mostly Polynomial regression applied to all numeric variables Hierarchy of SEO Needs - Regardless of all the noise, there are some definitive SEO needs that are tried-and-true [1 min] Similar to Maslow's Hierarchy of Needs Bottom of the pyramid is most important (barrier to entry) Top of the pyramid gives you competitive advantage Crawl - can G discovery your pages? Indexing - can G render and parse your pages? Schema, meta data, copy - help G understand your pages Links = signal of importance, vote for trust
- Business KPI Comps Analysis via GDS Review business KPIs weekly across the different channels using GDS + AA GDS is free - highly recommended for data visualization and reports = automation! More time analyzing, no time data pulling Lots of API integration options AA - analytics platform that tracks performance, very expensive, GA is a free option Will have to use either AA or GA and GDS if you go into ecom, analytics or DM
- Business KPI Comps Analysis via GDS Review business KPIs weekly across the different channels using GDS + AA GDS is free - highly recommended for data visualization and reports = automation! More time analyzing, no time data pulling Lots of API integration options AA - analytics platform that tracks performance, very expensive, GA is a free option Will have to use either AA or GA and GDS if you go into ecom, analytics or DM
- Business KPI Comps Analysis via GDS Review business KPIs weekly across the different channels using GDS + AA GDS is free - highly recommended for data visualization and reports = automation! More time analyzing, no time data pulling Lots of API integration options AA - analytics platform that tracks performance, very expensive, GA is a free option Will have to use either AA or GA and GDS if you go into ecom, analytics or DM
- What is data-driven SEO? [1.45 min] My definition: The process of improving organic rankings using both quantitative and qualitative data as the primary driver for all decision-making
- Mostly quantitative but with some qualitative Qualitative analysis (descriptive observations and conceptual) Quantitative (KPI measurements) My top KPIs = rankings and visits since our go
- Correlation does not imply causation - this famous saying in statistics applies to SEO
- Recent example: SEO tool vendor stated that there was a direct correlation with our forecasted traffic recovery at the same time that we started using their platform Who can tell me the issue with this chart? [Wait for the class to respond] The pandemic has influenced our traffic, at times over 200%+ YoY, very unfair assessment to take credit for a global crisis causing people to need home offices and furniture This is why we can’t have nice things!
- Data-Driven SEO Use Cases [2.5 min] Now that we know how G search works and what data-driven SEO means, let’s talk through the different use cases where we use analytics and data to solve SEO problems
- ROI Calculations As if SEOs don't have it hard enough battling G algos, we often are met with exec push-back and need to illustrate the value of investing in organic search constantly even though it's typically the channel that generates the most traffic Can do potential traffic value projections using an expensive enterprise SEO tool called BrightEdge It states the revenue gain opportunity if we were to increase our ranking based on a moderate rank strategy and an estimated traffic value forecast model
- Good news! You don’t need any fancy SEO software to do traffic projections because we can do it for free using click curves and automated G Sheets formulas to plug and chug Clicks / Impressions = Click-Through Rate % Click curve = average CTR per ranking position, massive lift in positions 5 and up where everything else barely gets the same CTR We can make traffic assumptions based on our current clicks, impressions, CTR, and positions specific to a keyword target then apply it to average CTRs per position based on the click curve. The traffic payoff from moving from page 2 to page 1 or #2 to #1 will be greater than moving from #10 to #7 Example: “vashon” is currently ranking 7 and with SEO, they want to rank in #5 Based on the average CTR of pages ranking in position 5, we can calculate the rest of the values to determine the extra clicks, impressions and CTR we will earn from optimization
- Lighthouse Score Calculations - G has a need for speed! They score site speed using their tool called Lighthouse Weighted averages of different factors that quantify web performance and site speed Co-lead web perf team that optimizes for the Lighthouse Score We focus on optimizing for the weights with the most value
- Example: implemented a recommendation from the Google Lighthouse audit which resulted in our score going from a little under 80 to 92/100
- ooglebot Bad Crawl Budget Loss via Log Files Log files or server logs are files located on your web server that give info on each interaction or hit between your site and your users and bots I use another fancy tool called Sumo Logic and Botify that reads the raw logs and analyzes the data for me including a metric called bad crawl budget loss which is the percentage of pages that are wasting Googlebot crawl resources such as 404 errors and other blockers to indexing Goal = smallest bad crawl budget loss as possible
- 404s via Quantum Metric - When i first started, did audit of website, 404s were by far the biggest technical SEO issue QM = cross-device digital intelligence platform = marketers are low key watching you navigate the site LOL QM can help illustrate the business impact of not fixing page not found/broken pages/404 errors by assigning a conversion value showing sessions vs CR value differences when the user encountered an error
- Instantly pull out themese that would be hard
- The most effective marketing strategies target a market by focusing on customers at any stage of the buying process Right place, right time, right people Organic search can do just that from education < investigation < pre-decision < decision < post-decision As someone moves through each stage from education up, the intent to purchase increases SEO ensures that if you build content that reaches all stages of decision making, it can be found in search engines to reach the right people, at the right time and place Targets customers at all points of the buying cycle Optimizations reach beyond a single phrase or keyword – think traffic based on topics
- Business KPI Comps Analysis via GDS Review business KPIs weekly across the different channels using GDS + AA GDS is free - highly recommended for data visualization and reports = automation! More time analyzing, no time data pulling Lots of API integration options AA - analytics platform that tracks performance, very expensive, GA is a free option Will have to use either AA or GA and GDS if you go into ecom, analytics or DM
- Python is an amazing programming language that will help you become better SEOs. You can use python for SEO by dropping your reliance on Excel and stop using spreadsheets, by leveraging APIs, by automating the boring tasks and by implementing machine learning algorithms.
- Python for machine learning and Google stack
- Machine learning (ML), a subset of artificial intelligence (AI), is basically the ability to learn without explicitly being programmed by combining statistics and programming. Machine learning “learns” with either supervised or unsupervised learning. It needs training datasets that feed into the ML algorithms which are used to create the model. Loss function measures how off you are from the most accurate answer. ML is predicted to play a larger role in SEO and could be used at scale for creating automated metadata, image captions, transposing podcasts, and much more. Machine learning uses algorithms to parse data, learn from that data, and make informed decisions based on what it has learned. Deep learning structures algorithms in layers to create an "artificial neural network” that can learn and make intelligent decisions on its own.
- https://searchengineland.com/improve-internal-linking-calculate-internal-pagerank-r-246883 If you’re not familiar with R, it’s a free software for statistical computing and graphics that runs on a wide variety of platforms. Download and install it, if you don’t already have it. Install the igraph library by launching the R console and executing: install.packages("igraph") Once the library is installed, you will be able to use the following code in conjunction with the Screaming Frog crawl for your site: Simply follow the code comments (denoted by #) and don’t forget to: Specify the path to your Screaming Frog CSV file. Specify your domain and TLD extension. Name your output file, which will contain the Internal PageRank of each individual page on your website. takes into account which links are linking to that page in the network, rather than just the quantity of links.
- The most effective marketing strategies target a market by focusing on customers at any stage of the buying process Right place, right time, right people Organic search can do just that from education < investigation < pre-decision < decision < post-decision As someone moves through each stage from education up, the intent to purchase increases SEO ensures that if you build content that reaches all stages of decision making, it can be found in search engines to reach the right people, at the right time and place Targets customers at all points of the buying cycle Optimizations reach beyond a single phrase or keyword – think traffic based on topics