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license: cc-by-4.0
task_categories:
- tabular-classification
- tabular-regression
- time-series-forecasting
language:
- en
tags:
- synthetic
- saas
- business-intelligence
- analytics
- dashboards
- startup
- growth
- mrr
- cac
- ltv
- churn
- marketing
- tabular
pretty_name: Solstice SaaS Growth Pack
size_categories:
- 1K<n<10K
configs:
- config_name: companies
data_files:
- split: train
path: companies.csv
- config_name: growth_metrics
data_files:
- split: train
path: growth_metrics.csv
- config_name: channel_performance
data_files:
- split: train
path: channel_performance.csv
- config_name: customer_segments
data_files:
- split: train
path: customer_segments.csv
- config_name: metric_definitions
data_files:
- split: train
path: metric_definitions.csv
- config_name: dashboard_suggestions
data_files:
- split: train
path: dashboard_suggestions.csv
---
# Solstice SaaS Growth Pack (Sample)
**A dashboard-ready synthetic SaaS metrics dataset.** Import the 6 CSVs straight into any BI tool and have a credible SaaS growth dashboard in under 10 minutes — no cleanup, no modeling.
Built by [Solstice AI Studio](https://www.solsticestudio.ai/datasets) as a free sample of a larger commercial pack. 100% synthetic — no real company, customer, or personal data.
## What's in the box
| File | Rows | Grain | Purpose |
|---|---|---|---|
| `companies.csv` | 6 | company | Master dimension — 6 synthetic startups spanning 6 distinct growth narratives |
| `growth_metrics.csv` | 540 | date × company | Daily revenue, MRR, customer counts, CAC, LTV, churn |
| `channel_performance.csv` | 3,780 | date × company × channel | Marketing channel impressions, clicks, conversions, cost, attribution |
| `customer_segments.csv` | 18 | company × segment | SMB / Mid-Market / Enterprise unit economics |
| `metric_definitions.csv` | 7 | metric | Self-documenting formulas |
| `dashboard_suggestions.csv` | 8 | chart | 4 starter dashboards with suggested axes |
**Period:** 90 days. **Currency:** USD. **Dates:** ISO-8601 (`YYYY-MM-DD`). **Join key:** `company_id`.
## Growth narratives included
Each company embodies a distinct SaaS growth profile — so dashboards show realistic variance instead of random noise:
- **Steady PLG** — strong SEO/content/referral, efficient long-term growth
- **Paid accelerator** — aggressive paid acquisition, higher CAC
- **Enterprise lumpy** — quarter-end deal spikes, lower churn
- **Seasonal B2C** — demand seasonality and periodic swings
- **Churn recovery** — visible churn event followed by stabilization
- **Capital infusion** — growth acceleration after mid-period expansion
## Why this dataset
**Clean joins, zero cleanup.** Stable IDs, one clear grain per table, no null-heavy columns, no ambiguous foreign keys. Import order: companies → growth_metrics → channel_performance → customer_segments.
**Pre-calculated SaaS metrics.** MRR, CAC, LTV, churn rate, conversion rate, CTR — all included, formulas documented in `metric_definitions.csv`. Users get to insight on first import.
**Cross-table consistency.** Daily channel `conversions` sum exactly to `new_customers`. Daily channel `cost` sums exactly to `marketing_spend`. Active customer counts respect `prev + new − churned = active` on every row.
**Realistic magnitudes.** Daily revenue reconciles to MRR over a month. ARR, LTV:CAC, and payback periods sit in credible SaaS ranges.
## Use cases
- Instant demo dashboards for BI / analytics tools
- User onboarding & first-value experiences
- SaaS metrics dashboard templates
- Product showcase & sales enablement
- Analytics workflow testing (imports, joins, filters)
- Startup & growth analytics education
- Customer success & retention analysis
- Marketing performance & attribution analysis
## Quick start
```
companies.csv → dimension table
growth_metrics.csv → primary fact (time × company)
channel_performance.csv → secondary fact (time × company × channel)
customer_segments.csv → segment roll-up
```
Join key is `company_id`. All dates are ISO-8601. All currency is USD.
**Suggested first dashboard: SaaS Growth Overview**
- Line chart: `date` × `revenue`, filter by `company_name`
- Dual-axis line: `date` × (`mrr`, `active_customers`), filter by `company_name`
Full dashboard recipes in `dashboard_suggestions.csv`.
### Load with pandas
```python
import pandas as pd
companies = pd.read_csv("companies.csv")
growth = pd.read_csv("growth_metrics.csv", parse_dates=["date"])
channels = pd.read_csv("channel_performance.csv", parse_dates=["date"])
segments = pd.read_csv("customer_segments.csv")
# Monthly MRR per company
monthly_mrr = (
growth.assign(month=growth["date"].dt.to_period("M"))
.groupby(["company_name", "month"])["mrr"].mean()
.reset_index()
)
```
## Data quality checklist
- All foreign keys resolve (0 orphans)
- No nulls in required columns
- No negative revenue, spend, or counts
- Derived metrics reproduce from inputs (mrr, cac, ltv, churn_rate, conversion_rate, click_through_rate)
- Continuity invariant holds: `prev_active + new − churned = active` on every row
- `impressions ≥ clicks ≥ conversions` on every channel row
## Schema
See `SCHEMA.md` for full column definitions, join model, metric formulas, and synthetic profile documentation.
## License
Released under **CC BY 4.0** — use freely for demos, research, internal tooling, education, and commercial templates. Attribution appreciated.
Synthetic data only — no real company, customer, or personal information.
## Get the full pack
This repo is a **6-company, 90-day sample**. The production pack scales to any company count (12 / 50 / 500+), any date range (1 quarter / 1 year / 3 years), any seed for reproducibility, custom growth-profile mixes, and custom industry / channel configurations.
**Self-serve (Stripe checkout):**
- [**Sample Scale tier — $5,000**](https://buy.stripe.com/7sY5kD2j85QTfSb5lfeEo03) — ~25K records, one subject, 72-hour delivery.
**Full pack + enterprise scope:**
- [www.solsticestudio.ai/datasets](https://www.solsticestudio.ai/datasets) — per-SKU pricing across Starter / Professional / Enterprise tiers, plus commercial licensing, custom generation, and buyer-specific variants.
**Procurement catalog:**
- [SolsticeAI Data Storefront](https://solsticeai.mydatastorefront.com) — available via Datarade / Monda.
## Citation
```bibtex
@dataset{solstice_saas_growth_pack_2026,
title = {Solstice SaaS Growth Pack (Sample)},
author = {Solstice AI Studio},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/solsticestudioai/saas-growth-pack}
}
```
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