Quantum Lab / templates
Start from a working notebook
From pricing analysis to customer segmentation, these Quantum Lab templates give you a working starting point with SQL, Python, charts, and Kole. Open one and make it yours.
Revenue
Analyze revenue streams, segment performance, and pipeline health with SQL and Python.
Revenue by Segment
Break down revenue by customer segment across time periods. Uses SQL to pull order data and pandas to pivot by segment, with trend charts and a written summary.
Revenue Waterfall
Visualize quarter-over-quarter revenue changes by source. Identifies which segments drove growth or contraction with a waterfall chart.
Pipeline Health Review
Analyze sales pipeline stages, conversion rates, and deal velocity. Surfaces stalled opportunities and forecasts close rates by segment.
Customer Analytics
Understand customer behavior, retention patterns, and segmentation with data analysis.
Cohort Retention
Track user retention by signup cohort over weeks or months. Builds a retention matrix and heatmap from event data with pandas.
Customer Segmentation
Group accounts by behavior using K-means clustering. Loads usage and purchase data, normalizes features, and visualizes clusters with scatter plots.
Churn Risk Analysis
Identify accounts at risk of churning based on activity patterns. Computes engagement scores and flags accounts below threshold with a risk table.
Pricing
Optimize pricing strategy with willingness-to-pay analysis, basket analysis, and market modeling.
Willingness to Pay
Analyze survey responses to find optimal price points by segment. Computes willingness-to-pay distributions, income bracket analysis, and market capture curves.
Market Basket Analysis
Identify high-impact product pairings from transaction data. Uses association rules to find cross-sell opportunities and co-purchase patterns.
Operations
Track KPIs, monitor SLAs, and analyze operational funnels with automated notebooks.
Weekly KPI Dashboard
Automated weekly KPI tracking for key business metrics. Pulls from your warehouse, computes week-over-week changes, and renders a chart dashboard.
Funnel Analysis
Measure conversion rates across signup, activation, and engagement stages. Identifies drop-off points and computes stage-over-stage conversion.
SLA Monitoring
Track response times and resolution rates against SLA targets. Flags breaches and surfaces patterns by team, priority, and time period.
Visualization
Transform data into geographic maps, sentiment charts, and interactive visual stories.
Geographic Distribution
Map customer or revenue distribution by region. Aggregates data by geography and renders comparison charts across territories.
Sentiment Analysis
Analyze customer feedback text for sentiment patterns. Processes reviews or support tickets and visualizes sentiment trends over time.
Forecasting
Forecast demand, detect anomalies, and project trends with statistical and ML models.
Demand Forecasting
Forecast product demand using time series analysis. Fits historical sales data with statistical models and projects forward with confidence intervals.
Anomaly Detection
Detect unusual patterns in time series metrics. Uses statistical methods to flag outliers in revenue, traffic, or operational data.
Financial
Track revenue metrics, unit economics, and financial health with automated analysis.
Customer Lifetime Value
Estimate and segment CLV using historical purchase data. Computes per-cohort LTV, plots distribution curves, and identifies high-value segments.
MRR / ARR Tracking
Monthly and annual recurring revenue trends with expansion, contraction, and churn components broken out by segment.
Unit Economics Dashboard
CAC, LTV, payback period, and gross margin per customer segment. Pulls from billing and marketing spend data.
Product & Growth
Measure feature adoption, activation funnels, and product-led growth metrics.
A/B Test Analysis
Statistical significance calculator with sample size, lift, and confidence interval reporting for experiment results.
Feature Adoption Tracker
Adoption curves, activation rates, and usage frequency for shipped features. Tracks rollout progress over time.
Product Usage Cohorts
Daily, weekly, and monthly active user retention by signup cohort and engagement tier with heatmap visualization.
Activation Funnel
New user onboarding steps with drop-off rates, time-to-activate metrics, and segment-level comparison.
Marketing
Analyze campaign performance, attribution, and acquisition channels.
Campaign Performance
ROI, CPA, and conversion rates across channels with spend allocation view and trend comparison.
Attribution Analysis
Multi-touch attribution modeling: first-touch, last-touch, linear, and time-decay models side by side.
SEO and Traffic Analysis
Organic traffic trends, keyword ranking changes, and page-level performance with week-over-week comparison.
Supply Chain
Optimize inventory, vendor performance, and cost structures with data.
Inventory Optimization
Stock levels, reorder points, carrying costs, and stockout risk by SKU with safety stock calculations.
Cost Structure Analysis
Fixed vs. variable cost breakdown with margin sensitivity scenarios and break-even analysis.
Vendor Scorecard
Supplier performance on delivery time, defect rate, cost variance, and responsiveness with composite scoring.
Customer Success
Monitor customer health, NPS, and support quality with composite scores.
NPS Survey Analysis
Net Promoter Score trends, promoter and detractor segmentation, and verbatim response clustering.
Support Ticket Analysis
Ticket volume, resolution time, CSAT scores, and topic categorization over time with team-level breakdown.
Customer Health Score
Composite health scoring from usage, support, billing, and engagement signals with alert thresholds.
Data Science
Explore datasets, build models, and run statistical analyses from a notebook.
Exploratory Data Analysis
Automated profiling for any dataset: distributions, correlations, missing values, and outlier detection with summary charts.
Time Series Decomposition
Trend, seasonality, and residual breakdown for time series data using statistical decomposition methods.
Clustering Explorer
K-means and DBSCAN clustering with elbow plot, silhouette scores, and interactive cluster profiles.
Regression Analysis
Linear and logistic regression with feature importance, residual diagnostics, and prediction intervals.
Ready to start?
Open Quantum Lab and begin from any template, or ask Kole to build a notebook from your question.
Open Quantum Lab