After operating a technical blog with approximately 500,000 monthly pageviews for several years, I recently completed a migration from Google Analytics (GA4) to Plausible Analytics. The primary driver was financial, but the operational and data quality benefits were a significant secondary gain. This post details the concrete cost savings and architectural observations for others considering a similar move.
**Previous Cost Structure with Google Analytics**
While Google Analytics is often termed "free," its integration with Google's ecosystem creates indirect costs that become substantial at scale.
* **Google Cloud Billing:** To leverage BigQuery for raw event export and analysis (a necessity for any serious data work), we were funneling data through Google Tag Manager to GA4, then using the GA4 BigQuery Link. This incurred BigQuery storage and query costs. Our average monthly bill for this pipeline was approximately $220-$280.
* **Engineering Overhead:** Maintaining the tag configuration, debugging discrepancies, and managing the ETL pipeline from BigQuery to our internal dashboards consumed roughly 10-15 engineering hours per month. At a conservative rate, this represented an additional $1,200-$1,800 in monthly operational cost.
* **Data Lag & Complexity:** The 24-48 hour latency for data availability in BigQuery hindered real-time operational decisions. Furthermore, the GA4 data model's complexity (events, parameters, user_properties) required continuous transformation to be usable.
**Plausible Cost and Configuration**
Plausible operates on a straightforward monthly pageview bucket model. For 500,000 monthly pageviews, the current pricing tier is $360/month when billed annually. There are no additional costs for team seats, historical data retention, or API access. The implementation is notably lightweight.
```html
<!-- Plausible script - placed in site -->
```
The data is available in near real-time (lag of less than 2 minutes). Their dashboard provides core web vitals, goal conversions, and custom event tracking without requiring a complex data model rebuild.
**Quantified Savings**
| Cost Component | Google Analytics (Indirect) | Plausible (Direct) | Monthly Savings |
| :--- | :--- | :--- | :--- |
| Platform Fee | $0 (but not truly free) | $360 | -$360 |
| BigQuery Costs | ~$250 | $0 | +$250 |
| Engineering Overhead | ~$1,500 (10 hrs @ $150/hr) | ~$150 (1 hr @ $150/hr) | +$1,350 |
| **Total** | **~$1,750** | **~$510** | **~$1,240** |
**Technical and Observability Trade-offs**
* **Data Depth:** Plausible does not offer a raw data export equivalent to BigQuery. This is its most significant limitation for deep-dive, custom machine-learning, or advanced attribution modeling. For standard blog analytics (traffic sources, top pages, bounce rates), it is more than sufficient.
* **API Limits:** The Plausible API is well-documented and sufficient for building operational dashboards in Grafana. We replaced our previous BigQuery data source with it successfully for high-level SLO dashboards.
* **Privacy & Performance:** The reduction in client-side JavaScript payload and the absence of cookie banners simplified our frontend stack and improved Core Web Vitals scores marginally.
**Conclusion**
For a use case focused on actionable, high-level analytics rather than deep raw data mining, the migration resulted in approximately **85% reduction in total cost of ownership** when factoring in engineering time. The simplification of the data stack is a non-trivial benefit. The key decision factor for others will be the absolute requirement for raw, unsampled event data. If that is not a strict necessity, the cost efficiency of a product like Plausible is compelling at this scale.
Regards, Luke
Measure everything.
So you're basically paying Google for the privilege of analyzing your own data? Classic.
BigQuery costs are no joke, but I'm more stuck on the engineering overhead. 10-15 hours a month to babysit a GA4 pipeline? That's the real crime. Plausible's API is dead simple, you can probably rebuild the one dashboard you actually need in an afternoon.
The switch makes sense, but wait until you hit 1M pageviews. Their pricing gets spicy too.