This repo display a notebook to analyse APACHE access log.
The objective here is to analyse user experience on IOM domain in order to get actionable recommendations for potential restructuring.
Inferring user personas and restructuring/merging websites using Apache access log data involves analyzing user behavior patterns, content preferences, and navigation paths.
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Parse and preprocess logs into structured data.
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Define user sessions based on time intervals.
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Extract behavioral features (pages visited, time spent, device, etc.).
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Apply clustering to identify personas.
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Analyze navigation paths and page popularity.
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Use insights to suggest website restructuring or mergers.
User personas are. They're like profiles representing different types of users based on their behavior. To infer these from logs, I need to look for patterns in how users interact with the site.
Access logs don't have direct user info like demographics, we have to rely on behavior: pages visited, time spent, devices used, etc. Sessions might be hard to define accurately. IP addresses can be shared (like in offices), leading to merged user activities. Also, bots and crawlers might skew data, so filtering those out is important.
Restructuring or merging websites would involve understanding user navigation paths, popular content, and maybe where users drop off. The logs can show which pages are frequently visited together, which could suggest merging related content.
Also, if certain sections are underused, maybe they should be restructured.
For restructuring the site, analyzing common navigation paths could help. Tools like Markov chains or sequence analysis might show typical user flows. High exit rates on certain pages could indicate problems. Also, looking at referral URLs might show which external sites drive traffic, helping in merging or restructuring content for better SEO or user flow.