Systems | Development | Analytics | API | Testing

Why did our pipeline drop? Find the cause in HubSpot deal notes (Databox HubSpot MCP)

Why did our pipeline drop? Ask Genie, the Databox AI Analyst, and it reads your HubSpot deal notes through the HubSpot MCP connector to find the cause. In this example, open pipeline is down 17.5% to $1.04M. Genie traces it to 2 deals lost on price after a Sept 1 rate change and 1 deal that lost its champion. In this video: Chapters Key terms Tools and data sources shown: HubSpot (CRM integration and HubSpot MCP connector), Google Analytics, Stripe, Slack. All data is a fictional demo account.

Why did my organic traffic drop? Find the cause with AI (Databox Semrush MCP)

Why did my organic traffic drop? Ask Genie, the Databox AI Analyst, with the Semrush MCP connector. Genie checks your Google Analytics traffic, then runs keyword, competitor, backlink and site audit research in Semrush, all in one answer. In this example, two causes explain almost the whole 14% drop: a competitor took two top keywords, and a canonical tag error went live with a site release. In this video.

Why did MRR drop? Find the cause in Stripe with AI (Databox Stripe MCP connector)

Why did MRR drop this month? Connect Stripe to Genie, the Databox AI Analyst, with the Stripe MCP connector and ask. Genie checks the MRR metric in Databox, then reads the subscriptions, invoices and payments in Stripe. In this demo, two canceled subscriptions and three failed payments explain the whole 3.9% drop, and $2,900 of it is still recoverable. In this video: Chapters.

Why Trusted Data Is the New AI Moat (w+ Rick Kranz from the AI Marketing AUtomation Lab)

Rick Kranz has built over 100 AI automations for his community and clients — he has no reason to defend Databox. But when he tried to run his AI analysis without the Databox MCP, it just stopped working. In this episode, Rick and Pete break down exactly why: the semantic layer, the metric definitions, and the standardized math that make an AI's answer trustworthy instead of a guess. If you've ever wondered why connecting five random MCP servers to Claude doesn't give you the same results as a purpose-built data layer, this is the episode.

From Prompt to Report: Artifacts in Databox

Ask Genie a question. Get a report back, ready to share, with real data already in it. This is Genie Artifacts, Databox’s AI analyst turning a prompt into a finished document. Watch it build a report from scratch, convert that report into a slide deck with a single follow-up prompt, then get shared as a public link anyone can open, no Databox login needed. What you’ll see: Genie pulls from 130+ connected data sources, so every report and deck is built on numbers your team already trusts. No manual formatting, no rebuilding for a different format, no dashboard for the recipient to log into.

Databox Skills Marketplace - Free AI Analytics Skills for Claude

The Databox Skills Marketplace is a free library of AI analytics skills and workflows - download them, connect your Databox data, and get structured reports inside Claude in seconds. How it works: connect Databox MCP to Claude, run a skill with a single prompt, and Claude writes the analysis from your live data. No exports. No copy-paste. No manual setup. What's in the marketplace: All free. All built on Databox MCP.

How to Scale Paid Media Across 5 Channels Without Losing Visibility (Google, Meta, LinkedIn, TikTok)

Agencies hit the same wall every time they try to grow: who is going to actually run the campaigns, and how do you keep visibility across every client and every channel when you do? Ashish Chaturvedi, data analyst of Atidiv, walks through how Atidiv and Databox solve both sides of the problem. Atidiv handles campaign execution across Google Ads, Meta, LinkedIn, TikTok, and email. Databox gives you the visibility layer: one interactive view where you can see spend, revenue, and return across every channel without chasing updates in Slack, email, or spreadsheets.