Used For

• +**Your team exports CSVs from 5 different tools to build one report** → Everything syncs automatically into one database you can query with drag-and-drop
• +**Your HubSpot data gets deleted after 90 days but you need historical trends** → Keeps all your data forever, even stuff your source tools throw away
• +**Non-technical team members can't write SQL but need custom reports** → Drag-and-drop query builder lets marketers build their own dashboards
• +Connects to 100+ tools automatically - no writing API scripts or dealing with rate limits
• +AI flattens messy JSON data into clean tables without manual schema mapping

Best For

• >Your data is scattered across 8 tools and your CEO keeps asking for 'one source of truth'
• >Marketing team needs reports but you don't have a data engineer (and can't afford a $120k salary)
• >You're manually exporting CSVs from different tools every week like some kind of digital peasant

Not For

• -Teams under 20 people — you're paying enterprise data warehouse prices for startup data volumes
• -Companies with 3+ data engineers — you can build this cheaper with Airflow and save $20k annually
• -Anyone needing real-time data — the cheapest plan only syncs every hour, not exactly lightning fast

Pairs With

• *Tableau (because Panoply's built-in dashboards are functional but not executive-presentation pretty)
• *Slack (where you get notifications when data syncs fail at 3am)
• *dbt (for complex data transformations that Panoply's AI can't handle automatically)
• *Salesforce (one of the most common sources people connect for sales pipeline reporting)
• *HubSpot (to combine marketing data with sales data for attribution reporting)
• *Google Analytics (because every company wants to see web traffic alongside CRM data)

The Catch

• !Minimum $18,700/year even if you're just connecting 3 tools — there's no small business pricing tier
• !Row-based pricing gets expensive fast if you have high-volume data sources (hello, web analytics)
• !The drag-and-drop interface is great until you need complex transformations, then you're back to SQL anyway

Bottom Line

Data warehouse for teams who can't afford data engineers but can afford $1,500/month to avoid hiring one.