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By Nevena Rudan
86% pick generative AI before any BI tool for analytical work. Trust ranks fourth in their reasons. Speed and convenience rank first.
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By Nevena Rudan
Connecting Salesforce to Claude via MCP is the advancement the SERP says it is. You authenticate once, your AI agent queries live CRM data, and you stop copying deal records into chat windows. For a Revenue Operations Manager who spent Q1 begging an admin to export pipeline snapshots, that matters.
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By Nevena Rudan
The pricing page tells you what Free includes. This piece tells you whether Free fits how you actually work.
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By Nevena Rudan
The decision is not which product to choose. It is whose performance you are reporting on.
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By Nevena Rudan
Most agencies compare plans by scanning feature grids. The ones that pick the right plan on the first try do arithmetic instead.
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By Nevena Rudan
The plan that fits your workflow is rarely the one you land on if you shop the pricing page first.
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By Špela Jurič
A year ago we announced that Databox is becoming an AI-first company. At the time, that mostly meant what it meant for many companies in 2025: AI becoming a strategic priority. Teams were encouraged to experiment and adopt new tools, as it was clear that AI wasn’t a trend we could ignore. That was the easy part. What’s become clear over the last year is that there’s a significant difference between being AI-first and being AI-native.
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By Peter Caputa IV
Every team we talk to has a running list of questions they wish they could get fast, reliable answers to. What changed in our performance last month and why. Which clients are showing the early signs of churn. Which channels are actually pulling weight and which ones are quietly burning budget. The pull toward AI for this kind of work is obvious. The answers should be a question away.
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By Monise Branca
Ask three people in your company to pull the number of active customers this month, and you’ll probably get three different answers, even though each person labeled the metric the same way. One counts everyone who logged in, another counts only paying users, and a third filters down to a single plan tier. Nobody is wrong here. They’re all working from real data; they just never agreed on a single definition. Do that enough times, and the data itself becomes the thing everyone argues about.
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.
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?
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.
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Databox pulls all your data into one place, so you can track performance and discover insights in real-time.
Databox is an app that serves as a personal data assistant, helping business users pay attention to what matters, when it matters. From a morning briefing that makes sure you start the day knowing where you stand and how you’re progressing towards your goals, to smart alerts throughout the week that let you know when something needs your attention, Databox makes sure you’re never in the dark about the data that matters most to you. With Databox, you can focus on driving results -- not putting out fires.
Do you know how your data performed today?
- Track everything all in one place, from any device: Connect all your data sources to track all your company’s performance in one place, from any device. Just one login to track Google Analytics, HubSpot, Salesforce, Facebook Ads, Google AdWords, and 50+ others.
- Launch beautiful dashboards, no coding required: Choose from our library of pre-made templates, or create your own dashboard using our drag and drop editor, and have beautiful, real-time visualizations of your data in minutes.
- Focus more on the metrics that matter: Set goals and monitor progress in real time so your whole team can spot issues as they happen and make the adjustments needed to stay on target.