> ## Documentation Index
> Fetch the complete documentation index at: https://withseismic.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Cost Analysis: SaaS Subscription vs Pay-Per-Usage

> Why paying for compute is 10x cheaper than paying for a dashboard seat.

# Cost Analysis: SaaS vs Serverless

When buying data tools, you're usually paying for two things:

1. **The Data** (Compute/Storage)
2. **The UI** (Dashboard/Charts)

For engineers, paying for the UI is wasted budget. Let's break down the economics of keyword research.

## The SaaS Model (AnswerThePublic.com)

* **Plan**: Pro
* **Cost**: \~\$99/month
* **Limits**: Daily search caps apply.
* **Value**: You pay for the convenience of the visualization wheel.

## The Serverless Model (Apify Actor)

* **Plan**: Usage-based
* **Cost**: \~\$0.25 per 1,000 results (estimated compute).
* **Limits**: None.
* **Value**: You pay only for the machine time required to scrape Google.

### The Math

If you run 10 searches a month:

* **SaaS**: $99 / 10 = $9.90 per search.
* **Apify**: \$0.05 per search.

**Winner**: Apify (by a landslide).

If you run 10,000 searches a month (Enterprise scale):

* **SaaS**: You need a custom Enterprise plan (\$\$\$\$).
* **Apify**: You just pay for more compute. The unit economics stay roughly the same.

## Hidden Costs of SaaS

1. **Seat Licenses**: Need your whole team to access data? Pay for more seats. With Apify, you just share the API token or the output dataset.
2. **Export Friction**: Paying an intern to manually click "Download CSV" 50 times is a hidden labor cost. Automation eliminates this.
3. **Unused Capacity**: If you don't use the tool for a week, you still pay the $99 subscription. With Serverless, $0 usage = \$0 cost.

## Conclusion

Subscriptions are for tools you *live in* (like Slack or Jira). For data utilities, **pay-per-usage** is the only logical model.