| ---
|
| license: cc-by-4.0
|
| task_categories:
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| - tabular-classification
|
| - tabular-regression
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| - time-series-forecasting
|
| language:
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| - en
|
| tags:
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| - synthetic
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| - saas
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| - business-intelligence
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| - analytics
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| - dashboards
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| - startup
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| - growth
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| - mrr
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| - cac
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| - ltv
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| - churn
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| - marketing
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| - tabular
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| pretty_name: Solstice SaaS Growth Pack
|
| size_categories:
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| - 1K<n<10K
|
| configs:
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| - config_name: companies
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| data_files:
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| - split: train
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| path: data/companies/train.csv
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| - config_name: growth_metrics
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| data_files:
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| - split: train
|
| path: data/growth_metrics/train.csv
|
| - config_name: channel_performance
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| data_files:
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| - split: train
|
| path: data/channel_performance/train.csv
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| - config_name: customer_segments
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| data_files:
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| - split: train
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| path: data/customer_segments/train.csv
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| - config_name: metric_definitions
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| data_files:
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| - split: train
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| path: data/metric_definitions/train.csv
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| - config_name: dashboard_suggestions
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| data_files:
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| - split: train
|
| path: data/dashboard_suggestions/train.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 |
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| | `customer_segments.csv` | 18 | company × segment | SMB / Mid-Market / Enterprise unit economics |
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| | `metric_definitions.csv` | 7 | metric | Self-documenting formulas |
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| | `dashboard_suggestions.csv` | 8 | chart | 4 starter dashboards with suggested axes |
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|
|
| **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:
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|
|
| - **Steady PLG** — strong SEO/content/referral, efficient long-term growth
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| - **Paid accelerator** — aggressive paid acquisition, higher CAC
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| - **Enterprise lumpy** — quarter-end deal spikes, lower churn
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| - **Seasonal B2C** — demand seasonality and periodic swings
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| - **Churn recovery** — visible churn event followed by stabilization
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| - **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
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| - User onboarding & first-value experiences
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| - SaaS metrics dashboard templates
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| - Product showcase & sales enablement
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| - Analytics workflow testing (imports, joins, filters)
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| - 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}
|
| }
|
| ```
|
|
|
