Automation
Commit-time validation, scheduled runs, auto-deploy and webhooks reduce repeated setup and QA.
What could your team save?
Adjust the inputs to estimate the annual value of using Siamang Cloud. This model uses Cloud Pro at $200 per month. Looking for Studio plans?
Net annual benefit
Payback {{ paybackLabel }}ROI {{ roiLabel }}
- Analyst hours saved / year
- {{ hoursLabel }}
- Labor value recovered
- {{ laborLabel }}
- Re-fielding cost avoided
- {{ errorLabel }}
- Tool spend replaced
- {{ toolReplacedLabel }}
- Cloud Pro / year
- −$2,400
With the $1,200 first-year Cloud Pro pre-order, estimated payback is {{ paybackPreLabel }}.
An illustrative estimate, based on the assumptions below.
How this estimate is calculated
Labor value = study-instances × 26.5 hours × share saved × analyst rate. Re-fielding avoided = instances × error rate × $2,000 × error reduction. Net annual benefit = labor value + re-fielding avoided + tool spend replaced − $2,400.
The 26.5 hours and scenario percentages are planning assumptions, not measured results. Replace the inputs with your own figures and validate them in a pilot. Payback is the subscription cost divided by estimated monthly gross benefit.
Where the savings
can come from.
Less repeated work across the research lifecycle.
Earlier error checks
Broken logic is caught at commit time, before fieldwork starts.
Built-in analysis
Cleaning, crosstabs, weighting and SQL dashboards share one workflow.
Fewer separate tools
A connected pipeline with standard exports can replace parts of a fragmented toolchain.
Value beyond the estimate.
Versioned instruments and repeatable results make review easier. Standard exports and a source-available engine keep your research portable.
Run a pilot.
Measure the difference.
Try a real study and compare the hours with your own workflow.