Analytics

Measuring What Matters

For a One Person Enterprise, analytics should be lightweight and actionable. You do not need a data team or a BI, (Business Intelligence), platform — you need to know whether your website is growing, where visitors come from, and which content drives enquiries.

Claude Code can take raw data from simple analytics tools and turn it into a clear weekly or monthly summary that informs decisions.

Setting Up Lightweight Analytics

Recommended tools for solo operators:

Tool	Why It Works
Plausible	Privacy-focused, simple dashboard, CSV export, GDPR-compliant without cookie banners
Fathom	Similar to Plausible, clean API, good for low-traffic sites
Umami	Self-hosted option, full data ownership, free
Google Analytics 4	Most powerful, but most complex — use only if you need it

For most solo operators, Plausible or Fathom is the right choice. Both offer CSV exports and simple APIs that Claude Code can work with directly.

Interpreting Data With Claude Code

Raw numbers from an analytics dashboard are often less useful than a structured interpretation. Claude Code excels at this.

Weekly summary from CSV export:

1. Export last 7 days of data from Plausible as CSV
2. Save to /analytics/raw/2026-03-04.csv
3. Run:

Read /analytics/raw/2026-03-04.csv.
Produce a weekly analytics summary:
- Total visits and unique visitors (vs last week)
- Top 5 pages by views
- Top 5 traffic sources
- Top 3 countries
- Any pages with zero visits this week that had visits last week
- One observation and one suggested action based on the data
Save to /analytics/summaries/2026-03-04.md

Over time, these summaries become a valuable record of what is working.

Automated Weekly/Monthly Reporting

Turn this into a scheduled habit:

CLAUDE.md entry:

## Analytics
- Export Plausible data every Monday morning to /analytics/raw/
- Run analytics summary prompt and save to /analytics/summaries/
- Compare to same week last month

With a task scheduler (cron on Mac/Linux, Task Scheduler on Windows) and a Claude Code CLI invocation, this can run automatically.

Funnel and Conversion Analysis

If you have a clear conversion goal (contact form submission, newsletter sign-up, product purchase), Claude Code can help you analyse where people drop off.

Simple funnel analysis:

I have page view data in /analytics/funnel-2026-03.csv.
The conversion path is: Homepage → Services → Contact.
Calculate:
- Drop-off rate at each step
- Which traffic source has the highest conversion rate
- Which page has the highest exit rate before Contact
Suggest two specific improvements based on the data.

Cohort and Trend Analysis

For longer-term patterns:

Read all monthly summary files in /analytics/summaries/ from 2025 onwards.
Identify:
- Months with the highest growth
- Content topics that consistently drive traffic
- Traffic sources that are growing vs declining
- Seasonal patterns
Produce a 2025 annual review and 2026 focus recommendations.

• How to interpret basic web metrics: sessions, bounce rate, time on page, conversion rate
• How to set up goal tracking in your analytics tool
• How to export and structure data for analysis
• Basic SQL queries (useful for querying your own SQLite analytics database)

Innovative Ideas

• Anomaly alerts: Ask Claude Code to compare today's traffic to the 30-day average and send you an alert (via a file or email draft) if any metric is more than 2 standard deviations off
• Content performance ledger: Maintain a CSV of all published content with publish date, word count, and monthly views. Ask Claude Code to update it monthly and identify your best-performing content patterns.
• Competitor traffic estimation: Use publicly available tools (SimilarWeb, Ahrefs free tier) and ask Claude Code to compare your growth trajectory against competitors
• UTM parameter manager: Maintain a utm-codes.md file and ask Claude Code to generate properly formatted tracking URLs for every campaign