Connect sources, ask, and save to share with your team.
Start with CSV or connect Google Sheets, PostgreSQL, HubSpot, and more.
Use natural language to get charts and answers instantly.
Pin answers to a dashboard that stays updated when you refresh data.
From revenue attribution to pipeline analysis, Daymark connects your tools and gives you insight-ready answers for the decisions that matter most.
Which channels are actually driving revenue?
"Show me sessions and revenue by source/channel for the last 30 days"
Reallocate budget to channels that generate revenue, not just traffic. Stop optimizing for vanity metrics and focus on conversion-backed performance.
Save reports to a dashboard, share a link, and collaborate from a single source of truth. No more stale Slack links, no more version confusion. Everyone works from the same numbers.
PostgreSQL
Google Sheets
HubSpot
Google Analytics
Google Ads
Meta Ads
Google Search Console
ShopifyConnect your databases, ad platforms, CRM, and analytics tools in minutes. No data migration or complex setup required.
See reporting workflows across GTM, product, and ecommerce teams.
Prioritise SEO opportunities by connecting Search Console data to real conversion metrics. Know which pages to update next.
See how it worksConnect Google Analytics with your revenue data to separate high-converting channels from high-volume ones that never close.
See how it works
Analyse your HubSpot pipeline stage by stage to find where deals stall, which rep patterns win, and where to focus sales coaching.
See how it worksStart with CSV if needed, then connect live sources for always-updated reports.
Manual reporting
Daymark AI reporting
Keep access read-only and scoped while AI context stays limited to schema metadata.
Access
Daymark uses the minimum scopes required for every integration and never writes to your production systems. All connectors are read-only by design.
AI safeguards
Our AI agents work only with schema metadata and limited query results to generate insights. Your underlying data is never stored on our servers, never used to train models, and never shared with third parties.
Daymark doesn't generate or guess numbers. It pulls data directly from your connected sources — Google Analytics, HubSpot, PostgreSQL, etc. — and runs analysis on that synced data. The AI generates the logic and interpretation, not the underlying numbers. SQL users can inspect every reasoning step in the 'Steps' tab before sharing.
Yes — that's the core use case. Ask a cross-source question like 'which ad channels drove the most pipeline last month' and Daymark joins your Google Ads spend with HubSpot data automatically. No manual spreadsheet merging or SQL joins required.
Reports are based on the latest sync from your connected sources — not a live query. Data freshness depends on your sync frequency. If you need up-to-the-minute accuracy for a critical decision, check when your source last synced before sharing the report.
It depends on your use case. Daymark is built for GTM and product teams who need self-serve answers fast — not for building company-wide BI infrastructure or pixel-perfect dashboards. If your team spends more time requesting reports than using them, Daymark is the faster path.
No. Daymark's AI only accesses your schema metadata and the query results needed to answer your question. Your underlying business data is never stored by Daymark or used for model training.
No SQL knowledge required. Ask questions in plain English — Daymark generates the query logic and visualisations automatically. If you are technical, you can still view and validate the generated steps.
