Data-Driven SEO with Python: Solve SEO Challenges with Data Science Using Python / Поисковая оптимизация на основе данных с помощью Python: Решайте задачи SEO с помощью науки о данных и Python
Год издания: 2023
Автор: Voniatis Andreas / Вониатис Андреас
Издательство: Apress Media LLC
ISBN: 978-1-4842-9175-7
Язык: Английский
Формат: PDF/EPUB
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 596
Описание: Solve SEO problems using data science. This hands-on book is packed with Python code and data science techniques to help you generate data-driven recommendations and automate the SEO workload.
This book is a practical, modern introduction to data science in the SEO context using Python. With social media, mobile, changing search engine algorithms, and ever-increasing expectations of users for super web experiences, too much data is generated for an SEO professional to make sense of in spreadsheets. For any modern-day SEO professional to succeed, it is relevant to find an alternate solution, and data science equips SEOs to grasp the issue at hand and solve it. From machine learning to Natural Language Processing (NLP) techniques, Data-Driven SEO with Python provides tried and tested techniques with full explanations for solving both everyday and complex SEO problems.
This book is ideal for SEO professionals who want to take their industry skills to the next level and enhance their business value, whether they are a new starter or highly experienced in SEO, Python programming, or both.
What You'll Learn
See how data science works in the SEO context
Think about SEO challenges in a data driven way
Apply the range of data science techniques to solve SEO issues
Understand site migration and relaunches are
Who This Book Is For
SEO practitioners, either at the department head level or all the way to the new career starter looking to improve their skills. Readers should have basic knowledge of Python to perform tasks like querying an API with some data exploration and visualization.
Решайте проблемы SEO с помощью науки о данных. Эта практическая книга содержит код на Python и методы науки о данных, которые помогут вам генерировать рекомендации на основе данных и автоматизировать работу по SEO.
Эта книга представляет собой практическое современное введение в науку о данных в контексте SEO с использованием Python. В связи с развитием социальных сетей, мобильных устройств, меняющимися алгоритмами поисковых систем и постоянно растущими ожиданиями пользователей от использования веб-сервисов в Интернете генерируется слишком много данных, чтобы специалист по SEO мог разобраться в электронных таблицах. Для достижения успеха любому современному специалисту по SEO важно найти альтернативное решение, а наука о данных помогает оптимизаторам понять суть проблемы и решить ее. От машинного обучения до методов обработки естественного языка (NLP), поисковая оптимизация на основе данных с использованием Python предоставляет проверенные методы с полным объяснением для решения как повседневных, так и сложных задач SEO.
Эта книга идеально подходит для профессионалов в области SEO, которые хотят поднять свои профессиональные навыки на новый уровень и повысить ценность своего бизнеса, независимо от того, являются ли они новичками или имеют большой опыт в SEO, программировании на Python или и том, и другом.
Что вы узнаете
Посмотрите, как наука о данных работает в контексте SEO
Подумайте о задачах SEO на основе данных
Применяйте различные методы анализа данных для решения проблем SEO.
Поймите, что такое миграция и перезапуск сайтов.
Для кого предназначена эта книга.
Специалисты в области SEO, как на уровне руководителей отделов, так и на начальном этапе карьеры, которые хотят повысить свою квалификацию. Читатели должны обладать базовыми знаниями Python для выполнения таких задач, как запрос к API, а также для анализа и визуализации данных.
Примеры страниц (скриншоты)
Оглавление
About the Author ................................................................................................... xiii
About the Contributing Editor ..................................................................................xv
About the Technical Reviewer ...............................................................................xvii
Acknowledgments ..................................................................................................xix
Why I Wrote This Book ............................................................................................xxi
Foreword ...............................................................................................................xxv
Chapter 1: Introduction ............................................................................................ 1
The Inexact (Data) Science of SEO .......................................................................................... 1
Noisy Feedback Loop .............................................................................................................. 1
Diminishing Value of the Channel ............................................................................................ 2
Making Ads Look More like Organic Listings ............................................................................... 2
Lack of Sample Data ............................................................................................................... 2
Things That Can’t Be Measured ................................................................................................. 3
High Costs ............................................................................................................................... 4
Why You Should Turn to Data Science for SEO .............................................................................. 4
SEO Is Data Rich ...................................................................................................................... 4
SEO Is Automatable ................................................................................................................. 5
Data Science Is Cheap ............................................................................................................. 5
Summary ...................................................................................................................................... 5
Chapter 2: Keyword Research .......................................................................................................... 7
Data Sources ................................................................................................................................. 7
Google Search Console (GSC) ....................................................................................................... 8
Import, Clean, and Arrange the Data ........................................................................................ 9
Segment by Query Type ......................................................................................................... 11
Round the Position Data into Whole Numbers ....................................................................... 12
Calculate the Segment Average and Variation ....................................................................... 13
Compare Impression Levels to the Average .......................................................................... 15
Explore the Data .................................................................................................................... 15
Export Your High Value Keyword List .......................................................................................... 18
Activation ............................................................................................................................... 18
Google Trends ......................................................................................................................... 19
Single Keyword ...................................................................................................................... 19
Multiple Keywords ................................................................................................................. 20
Visualizing Google Trends ...................................................................................................... 23
Forecast Future Demand ........................................................................................................ 24
Exploring Your Data ............................................................................................................... 25
Decomposing the Trend ......................................................................................................... 27
Fitting Your SARIMA Model .................................................................................................... 30
Test the Model ....................................................................................................................... 33
Forecast the Future ............................................................................................................... 35
Clustering by Search Intent ......................................................................................................... 38
Starting Point ......................................................................................................................... 40
Filter Data for Page 1 ............................................................................................................. 41
Convert Ranking URLs to a String ......................................................................................... 41
Compare SERP Distance ........................................................................................................ 43
SERP Competitor Titles ............................................................................................................... 57
Filter and Clean the Data for Sections Covering Only What You Sell .................................................. 58
Extract Keywords from the Title Tags ............................................................................................ 60
Filter Using SERPs Data ................................................................................................................ 61
Summary .................................................................................................................................... 62
Chapter 3: Technical ................................................................................................................... 63
Where Data Science Fits In ......................................................................................................... 64
Modeling Page Authority ............................................................................................................. 64
Filtering in Web Pages ................................................................................................................ 66
Examine the Distribution of Authority Before Optimization .............................................................. 67
Calculating the New Distribution ............................................................................................... 70
Internal Link Optimization ........................................................................................................ 77
By Site Level .......................................................................................................................... 81
By Page Authority .................................................................................................................. 97
Content Type ........................................................................................................................ 107
Anchor Texts ........................................................................................................................ 111
Anchor Text Relevance ........................................................................................................ 117
Core Web Vitals (CWV) ......................................................................................................... 125
Summary ............................................................................................................................. 150
Chapter 4: Content and UX .................................................................................................... 151
Content That Best Satisfies the User Query .............................................................................. 152
Data Sources ....................................................................................................................... 152
Keyword Mapping ..................................................................................................................... 152
String Matching ................................................................................................................... 153
Content Gap Analysis ................................................................................................................ 160
Getting the Data ................................................................................................................... 161
Creating the Combinations .................................................................................................. 168
Finding the Content Intersection ......................................................................................... 169
Establishing Gap .................................................................................................................. 171
Content Creation: Planning Landing Page Content ................................................................... 174
Getting SERP Data ............................................................................................................... 176
Extracting the Headings ...................................................................................................... 182
Cleaning and Selecting Headings ........................................................................................ 187
Cluster Headings ................................................................................................................. 191
Reflections ........................................................................................................................... 197
Summary .................................................................................................................................. 198
Chapter 5: Authority ................................................................................................................... 199
Some SEO History ..................................................................................................................... 199
A Little More History ................................................................................................................. 200
Authority, Links, and Other ........................................................................................................ 200
Examining Your Own Links ........................................................................................................ 201
Importing and Cleaning the Target Link Data .......................................................................... 202
Targeting Domain Authority ................................................................................................. 206
Domain Authority Over Time ................................................................................................ 208
Targeting Link Volumes ....................................................................................................... 212
Analyzing Your Competitor’s Links ............................................................................................ 216
Data Importing and Cleaning ............................................................................................... 216
Anatomy of a Good Link ....................................................................................................... 221
Link Quality .......................................................................................................................... 225
Link Volumes ....................................................................................................................... 231
Link Velocity ........................................................................................................................ 234
Link Capital .......................................................................................................................... 235
Finding Power Networks ........................................................................................................... 238
Taking It Further .................................................................................................................. 243
Summary ............................................................................................................................. 244
Chapter 6: Competitors ............................................................................................................ 245
And Algorithm Recovery Too! .................................................................................................... 245
Defining the Problem ................................................................................................................ 245
Outcome Metric ................................................................................................................... 246
Why Ranking? ...................................................................................................................... 246
Features .............................................................................................................................. 246
Data Strategy ............................................................................................................................ 246
Data Sources ............................................................................................................................. 248
Explore, Clean, and Transform ................................................................................................... 249
Import Data – Both SERPs and Features ................................................................................... 250
Start with the Keywords ........................................................................................................... 252
Focus on the Competitors ......................................................................................................... 254
Join the Data ............................................................................................................................. 268
Derive New Features ................................................................................................................. 270
Single-Level Factors (SLFs) ...................................................................................................... 274
Rescale Your Data ..................................................................................................................... 277
Near Zero Variance (NZVs) ........................................................................................................ 279
Median Impute .......................................................................................................................... 284
One Hot Encoding (OHE) ............................................................................................................ 286
Eliminate NAs ............................................................................................................................ 288
Modeling the SERPs .................................................................................................................. 289
Evaluate the SERPs ML Model .................................................................................................. 292
The Most Predictive Drivers of Rank ......................................................................................... 293
How Much Rank a Ranking Factor Is Worth .............................................................................. 296
The Winning Benchmark for a Ranking Factor .......................................................................... 299
Tips to Make Your Model More Robust ...................................................................................... 299
Activation ............................................................................................................................ 299
Automating This Analysis ........................................................................................................ 299
Summary ............................................................................................................................. 300
Chapter 7: Experiments .......................................................................................................... 301
How Experiments Fit into the SEO Process ............................................................................... 301
Generating Hypotheses ......................................................................................................... 302
Competitor Analysis ............................................................................................................. 302
Website Articles and Social Media .......................................................................................... 302
You/Your Team’s Ideas ......................................................................................................... 303
Recent Website Updates ...................................................................................................... 303
Conference Events and Industry Peers .................................................................................. 303
Past Experiment Failures ..................................................................................................... 304
Experiment Design ............................................................................................................... 304
Zero Inflation ....................................................................................................................... 308
Split A/A Analysis ................................................................................................................. 311
Determining the Sample Size .............................................................................................. 320
Running Your Experiment ................................................................................................... 327
Ending A/B Tests Prematurely ............................................................................................. 327
Not Basing Tests on a Hypothesis ....................................................................................... 328
Simultaneous Changes to Both Test and Control ................................................................. 328
Non-QA of Test Implementation and Experiment Evaluation ..................................................... 329
Split A/B Exploratory Analysis .............................................................................................. 332
Inconclusive Experiment Outcomes .................................................................................... 340
Summary .................................................................................................................................. 341
Chapter 8: Dashboards ................................................................................................................ 343
Data Sources ............................................................................................................................. 343
Don’t Plug Directly into Google Data Studio ........................................................................... 344
Using Data Warehouses ....................................................................................................... 344
Extract, Transform, and Load (ETL) ........................................................................................... 344
Extracting Data .................................................................................................................... 345
Transforming Data ............................................................................................................... 365
Loading Data ....................................................................................................................... 370
Visualization .............................................................................................................................. 373
Automation .......................................................................................................................... 374
Summary .................................................................................................................................. 374
Chapter 9: Site Migration Planning ........................................................................................... 377
Verifying Traffic and Ranking Changes ..................................................................................... 377
Identifying the Parent and Child Nodes ............................................................................... 379
Separating Migration Documents ........................................................................................ 385
Finding the Closest Matching Category URL ............................................................................. 389
Mapping Current URLs to the New Category URLs .............................................................. 393
Mapping the Remaining URLs to the Migration URL ............................................................ 395
Importing the URLs .............................................................................................................. 399
Migration Forensics .................................................................................................................. 412
Traffic Trends ....................................................................................................................... 413
Segmenting URLs ................................................................................................................ 423
Time Trends and Change Point Analysis .............................................................................. 437
Segmented Time Trends ...................................................................................................... 440
Analysis Impact ................................................................................................................... 442
Diagnostics .......................................................................................................................... 454
Road Map ............................................................................................................................ 463
Summary .................................................................................................................................. 467
Chapter 10: Google Updates ........................................................................................................ 469
Algo Updates ............................................................................................................................. 470
Dedupe ...................................................................................................................................... 477
Domains .................................................................................................................................... 479
Reach Stratified ................................................................................................................... 485
Rankings .............................................................................................................................. 493
WAVG Search Volume .......................................................................................................... 495
Visibility ............................................................................................................................... 496
Result Types .............................................................................................................................. 504
Cannibalization ......................................................................................................................... 512
Keywords .................................................................................................................................. 520
Token Length ....................................................................................................................... 520
Token Length Deep Dive ...................................................................................................... 525
Target Level ............................................................................................................................... 533
Keywords ............................................................................................................................. 533
Pages ................................................................................................................................... 537
Segments .................................................................................................................................. 544
Top Competitors .................................................................................................................. 544
Visibility ............................................................................................................................... 550
Snippets .............................................................................................................................. 557
Summary .................................................................................................................................. 561
Chapter 11: The Future of SEO ..................................................................................................... 563
Aggregation ............................................................................................................................... 563
Distributions .............................................................................................................................. 564
String Matching ........................................................................................................................ 564
Clustering .................................................................................................................................. 565
Machine Learning (ML) Modeling ................................................................................................... 565
Set Theory ................................................................................................................................. 566
What Computers Can and Can’t Do ............................................................................................. 566
For the SEO Experts .................................................................................................................. 566
Summary .................................................................................................................................. 567
Index ........................................................................................................................................ 569
