We investigate challenges related to the site search function of the ONS website and make recommendations on possible improvements. Although there is a wealth of literature on search engine optimisation (SEO), most solutions are designed for commercial websites that do not share similar goals and constraints as public sector websites. We will discuss why off-the-shelf solutions are not always suitable and where there is a gap, we explore dedicated approaches. We report on ideas that we found promising, as well as experiments that have not led to successful outcomes. We hope that our research will inform the web analytics community and invite suggestions for new ideas.
- Lanthao Benedikt
- Thanasis Anthopoulos
Currently, more than 60% of traffic to the ONS website comes from Google. It is clear that the ONS site search function needs improvement. As part of a wider improvement effort, the ONS Digital Publishing team have launched a project in partnership with the ONS Data Science Campus to investigate and optimise the site search capability.
This research focuses essentially on understanding users’ behaviours and intents. Understand who the users are helps to better meet their needs. The main aim is to inform ONS web developers and content designers on how to retrieve and rank search results in a meaningful way for users.
We investigate how data science techniques such as Natural Language Processing (NLP) - in topic modeling - and Unsupervised Machine Learning can be used to: 1) Bridge the barrier between users’ language and ONS terminology, and 2) Gain a better understanding of what content our users are trying to find on the website.
We collaborate with ONS Digital Publishing team
Code and outputs
A report has been published on the Campus website, discussing our findings and share our experience on ideas that we found promising, as well as experiments that have not led to successful outcomes.
Optimising the ONS site search function with Google Analytics and Natural Language Processing was published in August 2018.
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