Systems | Development | Analytics | API | Testing

What if you did not have to open a dashboard, read the charts, and figure out what the numbers mean? What if you could just ask a question and get the answer in plain English?

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.

You have the data. You just can't get to the answer. That changes now. Databox is an AI-powered analytics platform built to give teams clear, trusted answers, fast. No waiting. No spreadsheet tabs. No "I'll loop in Mark.".

Business analytics has changed. Now, it answers back. Meet Databox AI, AI-powered analytics for teams that need answers now. Ask your data anything with Genie, your AI analyst. Don’t just see numbers—understand what changed with AI Performance Summaries. Bring your data into your favorite AI tools with Databox MCP.

Most marketing teams track traffic and leads, but rarely connect the two to understand whether their content is attracting the right audience. In this walkthrough, Rick Kranz, Director of the AI Marketing Lab, demonstrates a powerful weekly growth system that cross-references website traffic, Google Search Console data, and CRM leads to identify which content truly drives ideal customer profile (ICP) engagement.

Two KPIs spiked during monthly client reporting — and there was no obvious reason why. Normally, that means 30 to 60 minutes of logging into multiple integrations, checking channel breakdowns, reviewing landing pages, and trying to manually piece together the story. Instead, Gary Magnone connected Databox to Claude through MCP and asked a simple question: where is this coming from? Within minutes, the analysis.

If you’re consistently posting on LinkedIn, the hard part isn’t getting data — it’s analyzing it. Most people review posts one by one, compare impressions manually, and try to “spot patterns” by eye. That’s slow. And it makes strategy reactive. In this walkthrough, Kamil Rextin, founder of 42 Agency, uses the Databox MCP with Claude to run a fast, AI-driven analysis of his LinkedIn performance — the kind of first-pass review you’d normally assign to a junior analyst.

Most agencies report on growth. But growth alone doesn’t answer the real question clients care about: Are we actually competitive? In this walkthrough, 42 Agency shows how they use the Databox MCP with Claude to benchmark client performance against relevant peer groups — filtered by size, revenue, and industry. Instead of relying on generic industry averages, they combine: The result? Stronger strategy conversations, clearer goal setting, and more confident planning grounded in a real market context.–

Will AI change the way SaaS companies grow? According to Adam Robinson, founder and CEO of Retention.com, AI is not the answer most founders think it is. Adam has built multiple SaaS companies and scaled Retention.com from $0 to $22M ARR in four years without funding. In this episode of Move the Needle, he explains why the companies that scale – and the ones that stall – are separated by one thing.

In this video, we show you how to connect Databox to Make using the Model Context Protocol (MCP). Learn how to give your automated workflows and AI tools direct access to your live business metrics, empowering you to easily fetch context, analyze data, and build data-driven automations faster than ever. Links & Resources: About this series: This video is part of our "Chat with Your Data" series, where we explore the Databox MCP.