It’s easy to get swept away by monthly search volume and to forget that behind every search there is a person with a specific motivation and set of needs to fulfil. This talk will look at how you can use Google’s algorithmic rewriting of the SERPs to help you identify those motivations so you can effectively optimise for intent and query context to improve the ranking performance of your landing pages. This talk will also help you understand how you can use this information to create more tailored online experiences for your prospective customers and how the same workflows can be applied for more general business intelligence insights.
13. Google isn’t ranking a page based on how it
uses a keyword
On-page Optimisation
@RoryT11
14. • User intent
• Query context
• Topical relevance
• Word relationships
Target the keyword, but optimise for this.
How does Google provide accurate results?
@RoryT11
24. There are
four ways you
can get this.
You need
Jupyter Notebook
What is
that?
25. The Jupyter Notebook is an open-source web
application that allows you to create and share
documents that contain live code, equations,
visualizations and narrative text. Uses include:
data cleaning and transformation, numerical
simulation, statistical modeling, data visualization,
machine learning, and much more.
Jupyter.org
@RoryT11
27. Jupyter Notebook is an environment on my laptop
where I can learn Python by copying scripts
created by people significantly smarter than me
and breaking them or making them do something
slightly different.
Rory Truesdale
Python Charlatan
@RoryT11
28. Resources to get started…
Jupyter
Notebook –
Getting
Started Guide
Robin Lord
Find
scripts
Paul Shapiro JR Oakes Hamlet Batista
Find
scripts
Find
scripts
56. •Align pages with the motivations of a searcher
•What language will resonate with your target audience
•Use to improve on page optimisation
HOW CAN WE APPLY THIS?
@RoryT11
57. Can we use
NLP to uncover
topical trends
in the SERPs?
Topic
modelling
@RoryT11
58. Topic
modelling
Topic modelling is an NLP method that assumes a
corpus contains a mixture of topics. It looks at how
words and phrases co-occur in a corpus and attempts
to group them in coherent themes or topics.
@RoryT11
66. •Reference for content ideation
•Internal linking and content recommendations
•Optimise effectively for semantic relevance
HOW CAN WE APPLY THIS?
@RoryT11
67. Can we make our
scripts work
across other data
sources to
understand our
customers?
Other
useful
applications
@RoryT11