| --- | |
| 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} | |
| } | |
| ``` | |