Scoop Analytics

Scoop Analytics is an AI-driven business intelligence platform that empowers non-technical users to become data scientists through natural language conversations. Simply ask questions like "What predicts customer churn?" to receive instant predictive models, uncover hidden customer segments, and gain actionable insights from your CRM, marketing, and support data—no SQL or coding needed.

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About Scoop Analytics

Scoop Analytics democratizes advanced data analysis by enabling business users to uncover critical insights through simple conversational queries. Unlike traditional BI tools that require SQL skills or data science expertise, Scoop allows anyone to identify patterns, forecast outcomes, and generate reports by asking questions in plain English. The platform combines enterprise-grade machine learning with an intuitive chat interface, automatically exploring vast data combinations to surface statistically significant insights. Whether in marketing, sales, or customer success, Scoop reveals impactful results—such as identifying high-converting customer segments or predicting churn weeks in advance—driving smarter business decisions.

How to Use

Connect your data sources, ask questions in plain English, receive instant predictive insights and visualizations, then export reports or integrate results into your CRM systems for seamless decision-making.

Features

Uncover hidden patterns and customer segments using advanced machine learning algorithms

Ask questions naturally and get immediate analytical insights

Identify key drivers of your metrics through automated analysis

Create interactive dashboards with a simple drag-and-drop interface

Automatically generate reports and executive presentations

Build predictive models without any coding or SQL knowledge

Push predictions and scores directly to your CRM systems

Connect over 100 data sources including Salesforce, HubSpot, and databases

Predict customer churn, deal closing, and revenue outcomes with a single click

Analyze millions of data rows in seconds using in-memory processing

Use Cases

Customer Segmentation and Targeting

Sales Pipeline Optimization

Executive Business Reporting

Churn Prediction and Prevention

Deal and Revenue Intelligence

Lead Scoring and Qualification

Revenue Forecasting

Customer Health Score Automation

Marketing Attribution Analysis

Cross-Sell and Upsell Opportunities

Best For

Revenue Analytics AgenciesBusiness Intelligence TeamsFractional CFOsExecutives and LeadershipMarketing AgenciesMarketing ProfessionalsRevenue LeadersBusiness TeamsSales ProfessionalsFinance DepartmentsCustomer Success Teams

Pros

No technical skills like SQL or Python needed; designed for business users.

Self-service analytics reduce reliance on data teams and IT support.

Provides explainable insights and accurate predictive models.

Integrates effortlessly with existing BI systems and CRMs to enhance functionality.

Proven ROI with average revenue discoveries exceeding $2 million and 287% ROI increase.

Identifies hidden patterns, segments, and key drivers for new opportunities.

SOC 2 Type II certified, ensuring data security and privacy; data is never used to train AI.

Enables early churn detection and improves forecast accuracy.

Automates data analysis, reporting, and presentation processes.

Cons

No specific disadvantages are listed; the platform is focused on delivering benefits for business users.

Pricing Plans

Choose the perfect plan for your needs. All plans include 24/7 support and regular updates.

Trial

Free

One-month free trial for one user, single static viewer, one data source, with support documentation. No onboarding or collaboration features included.

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Individual

$99/month

Per user, billed annually. Includes a free trial license, unlimited static viewers, two data sources, one hour onboarding, and support documentation. Collaboration features are not included.

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Team

$149/month

Per user, billed annually. Includes a free trial for 2+ users, unlimited static viewers, five data sources, five hours onboarding, and support with collaboration options.

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Enterprise

Custom pricing

Billed annually. Contact sales for user count, unlimited viewers, unlimited data sources, tailored onboarding, and premium support including AI, email, and phone assistance.

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Frequently Asked Questions

Find answers to common questions about Scoop Analytics

Do I need technical expertise to operate Scoop?

No. If you can write an email or use Excel, you can operate Scoop. Our AI handles all complex data science tasks automatically.

How does Scoop differ from ChatGPT or Claude?

While ChatGPT processes text, Scoop analyzes your actual business data. It connects directly to your systems, applying real machine learning to uncover patterns, make predictions, and generate insights specific to your company.

Which data sources can I connect to Scoop?

Scoop supports over 100 integrations, including Salesforce, HubSpot, Zendesk, Google Analytics, Snowflake, PostgreSQL, Excel, and more. You can also upload files or access data via API.

How accurate are the predictive models?

Prediction accuracy varies by use case and data quality, but most customers achieve 80-90% accuracy for churn and over 85% for deal closure. Each prediction includes confidence scores for trustworthiness.

Is my data protected and secure?

Yes. Scoop is SOC 2 Type II certified, uses enterprise-grade encryption, and never shares data between clients. We support SSO, RBAC, and can sign custom security agreements.

How quickly can I start seeing results?

Most users find their first valuable insight within 30 minutes of data connection. Full deployment typically takes around 2 weeks.

Can I export insights to other tools?

Absolutely. Export reports to PowerPoint, Google Slides, PDFs, or push insights directly into your CRM. We also offer APIs for custom integrations.

What support options are available?

All plans include support. Growth and higher tiers receive priority response times under 2 hours. Enterprise clients get dedicated success managers.