Today, we're changing that. We're launching Scoop for Slack, and it's not just another analytics integration. We've taught AI how to think like a data scientist, investigate like an analyst, and communicate like a trusted colleague—all inside your Slack conversations.
The Problem Nobody Wants to Admit
Here's the dirty secret about business intelligence: Nobody actually wants dashboards. What they want are answers. They want to understand why revenue dropped, what's driving customer churn, which deals are really at risk, and what they should do about it.
But traditional BI tools? They're like giving someone a speedometer when they're asking for directions. Sure, you can see how fast you're going, but that doesn't tell you if you're headed in the right direction or about to drive off a cliff.
Even with all the "self-service" BI tools out there, the reality is that when something important happens—when revenue drops or churn spikes—what do people do? They don't open a dashboard. They message their analyst on Slack: "Hey, can you dig into why enterprise revenue dropped last month?"
Then they wait. And wait. And schedule a meeting. And wait some more.
What If Your Analyst Never Slept?
We asked ourselves: What if every person had their own data scientist who never slept, never got frustrated by follow-up questions, and could investigate complex problems in minutes instead of days?
That's what we built with Scoop for Slack. But here's the thing—we didn't just connect charts to Slack. Anyone can do that. We built something fundamentally different: an AI that can actually reason through complex business questions.
When you ask Scoop "Why did enterprise revenue drop last month?"—it doesn't just show you a chart. It investigates. It might:
- Analyze revenue by segment to find where the drop occurred
- Identify specific customers driving the change
- Examine product mix shifts
- Look for seasonal patterns
- Check for correlation with other metrics
- Synthesize all findings into a clear narrative with specific recommendations
The whole investigation takes 2-3 minutes. Try getting that from your analyst team.
The Magic of Multi-Step Reasoning
The breakthrough came when we realized that good analysts don't just run queries—they investigate. They form hypotheses, test them, dig deeper based on what they find, and synthesize everything into actionable insights.
So we taught our AI to do exactly that. When you ask a "why" question, Scoop offers you two choices:
- Quick View (15-30 seconds): Just give me the chart
- Deep Analysis (2-3 minutes): Investigate this properly
Choose Deep Analysis, and you can watch as the AI plans its investigation, executes multiple analytical steps, and progressively shares what it's discovering. It's like having a data scientist think out loud while they work through your problem.
Zero Setup, Infinite Scale
Here's what really gets me excited: We made enterprise-grade analytics as easy as installing a Slack app.
Our channel-based security model is stupidly simple but incredibly powerful. Join the #sales-americas channel? You automatically see Americas data. Join #executive-team? You see everything. No IT tickets, no permission requests, no training courses.
Every user also gets their own personal analytics workspace. Drop a CSV in Slack, and boom—you're doing machine learning on it 30 seconds later. We're bringing enterprise functionality to non-enterprise users, just like we always promised.
Real ML, Not Toy Analytics
When I say we democratized data science, I mean it. Ask Scoop to:
- "Find patterns in customer behavior" → Runs EM clustering
- "What predicts churn?" → Builds a decision tree
- "Score all customers for upsell potential" → Creates and applies an ML model
But here's the key: You don't need to know what EM clustering is. You just need to know your business. The AI handles the data science and explains everything in plain English.
The Viral Effect We're Already Seeing
The coolest thing? Analytics is becoming social. When someone discovers an important insight, they can share it with one click. The whole team sees:
- Who found it
- What question they asked
- The complete analysis
- How to build on it
Teams are literally learning from each other's curiosity. One person asks about revenue, another digs deeper into their findings, someone else applies it to their region. Knowledge compounds.
In one beta customer, we watched a churn pattern discovered by a CSM in the morning become a scored model pushed to Salesforce by afternoon, triggering saves on three at-risk accounts by end of day. That's the power of democratized analytics.
Why This Matters
I've built analytics companies before. Birst was about bringing enterprise BI to the cloud. But even after our success there, I kept seeing the same problem: The gap between questions and answers was still too wide. Too much friction. Too much specialized knowledge required.
With Scoop for Slack, we've collapsed that gap. We've made getting answers as easy as asking a colleague—except this colleague has perfect memory, infinite patience, and a PhD in data science.
We're not trying to replace analysts or data scientists. We're trying to give everyone else their capabilities. Because in today's world, every decision should be data-driven, but not everyone can afford a data team.
Try It Yourself
Look, I could keep talking about features, but that's not what this is about. It's about a fundamental belief: Business intelligence shouldn't require an IT project. Getting answers shouldn't require SQL. Understanding your business shouldn't require a data science degree.
If you believe that too, come try Scoop for Slack. Install takes 60 seconds. Your first insight takes 2 minutes. The ROI—well, that's up to you and your curiosity.
We've taught AI what BI is. Now let's see what your team can discover.
—Brad
P.S. - We're offering 14 days free because I'm confident that once your team experiences this, they won't want to go back to the old way. Why wouldn't you want PhD-level data science for less than the cost of a dashboard license?
