Customer Insight Lab
A full customer analytics toolkit — from segmentation and churn to pricing and brand perception. Upload your data once and run any of 30+ analyses across four business questions.
Overview
30+ customer analyses
Segmentation, churn, satisfaction, pricing, and brand — all in one toolkit.
Upload once, analyze many
Load your CSV once and run any analysis without re-uploading.
Export & AI Chat
Download results as CSV, PNG, or Word — or ask the AI Chat to interpret your findings.
What you need
What you can do
How it works
Some analyses need no file at all
Some analyses run purely from on-page inputs — no upload required. Others use your uploaded data. Either way, when you do upload, one file works across every analysis in this lab.
Select an analysis
Pick an analysis from the sidebar. Before any data is loaded, the page opens on an intro screen for that analysis.
Check what it needs
The intro splits inputs into REQUIRED (needed to run) and OPTIONAL ones that refine the result. Map the columns you have. Use the Guide or load the sample dataset to see the format.
Upload or set inputs
Drag a CSV or Excel file anywhere onto the page — a drop zone appears; release to upload. One upload works across every analysis. Input-only analyses just take values on the page.
Map your columns
Open the Variables dropdown and match your columns to the fields each analysis needs. Most auto-detect from the names; the result renders as soon as they’re mapped — no Run button.
On an analysis page
At the top of every analysis page you'll find a Variables dropdown — assign your columns to the fields each analysis needs (most fields auto-detect from the column names) — and a Guide button that explains the method. Both stay at the top while you work.
Reading your results
Once it renders, the result comes in two parts: a plain-language Summary with the headline finding and key findings, followed by the detailed output — metric cards, tables, and charts.
AI Chat — ask anything about your result
Once an analysis runs, a circular toggle button appears at the bottom of the results panel. Click it to open AI Chat — the AI already knows which analysis was run and what the result was, so you can ask follow-up questions without re-explaining the context.
Explain results in plain language
Translates output into plain sentences — useful for stakeholders who don't read statistics.
Interpret key numbers
Ask about any metric in the result — what it means, whether it's significant, and why it matters.
Suggest next steps
Ask what the result implies in practice and what you should consider doing next.
Draft a summary
Request a written paragraph based on the result, ready to copy into a report or presentation.
Analysis sections
Customer Insight Lab organizes its analyses into 4 sections by business question.
Customers
Who are your customers and what are they worth?
Segments
Customer Segments
Cluster customers into groups by behavior and demographics — k-means or hierarchical clustering with profile breakdown.
LCA Segmentation
Latent Class Analysis — uncover hidden segments from categorical survey responses with class-membership probabilities.
Customer Personas
Turn segments into named, descriptive personas with representative traits, needs, and behaviors.
Customer Value
CLV / LTV
Customer Lifetime Value — projected net profit per customer over the relationship, from retention and margin inputs.
CAC vs LTV
Weigh acquisition cost against lifetime value to test whether each customer pays back.
High Value Customers
Rank and flag the top customers by spend, margin, or value contribution (the Pareto 20%).
Profit Segments
Group customers by profitability tier to see who drives — or drains — the bottom line.
Value Migration
Track how customers move between value tiers over time — upgrading, downgrading, or churning.
Loyalty
Why do customers stay or leave?
Satisfaction
Satisfaction Dashboard
Headline view of CSAT, NPS, and CES with trends and segment breakdowns.
CSAT Detail
Customer Satisfaction Score — distribution, drivers, and drill-down by segment or touchpoint.
CES Detail
Customer Effort Score — how hard it is to do business with you, with effort-driver analysis.
Retention
Churn Prediction
Model which customers are likely to leave, with risk scores and the factors driving each.
Cohort Retention
Track retention by signup cohort over time in a retention curve and heatmap.
Lifecycle Stage
Classify each customer into a lifecycle stage — new, active, at-risk, dormant, lost.
Win-back Targets
Identify lapsed customers worth re-engaging and estimate win-back potential.
Next Best Action
Recommend the most effective next offer or contact for each customer.
Voice of Customer
Sentiment Analysis
Score open-text feedback as positive, neutral, or negative, with trends over time.
Topic Modeling
Surface the recurring themes in reviews or comments without predefined categories.
Review Insights
Mine product and service reviews for strengths, weaknesses, and frequent mentions.
Complaint Detection
Flag and categorize complaints in free-text feedback for triage.
Behavior
How do customers act and where do they go?
Behavior
Customer Journey
Map the sequence of touchpoints customers follow from first contact to purchase and beyond.
Repeat Purchase
Measure how many customers buy again and how repeat behavior differs by segment.
Purchase Frequency
Analyze how often customers buy and the gaps between orders.
RFM Analysis
Score customers on Recency, Frequency, and Monetary value to rank engagement and worth.
Basket Analysis
Find products frequently bought together using association rules (support, confidence, lift).
Drop-off Funnel
Trace where prospects fall out of a multi-step funnel and quantify each step’s conversion.
Experience
Store vs Online Satisfaction
Compare satisfaction across physical and digital channels side by side.
Channel Preference
Identify which channels each segment prefers for browsing, buying, and support.
Touchpoint Analysis
Rate satisfaction and importance at each touchpoint to find priority fix-points.
Service Delay Impact
Quantify how wait times and delays affect satisfaction and retention.
Strategy
What to sell, at what price, and how to position?
Pricing
Price Sensitivity Meter
Van Westendorp PSM — find the acceptable price range and optimal price point from survey data.
Gabor-Granger
Estimate demand and revenue across price points to locate the revenue-maximizing price.
Optimal Price Finder
Combine willingness-to-pay with cost to recommend a profit-maximizing price.
Choice Modeling
Conjoint Analysis
Decompose product choices into part-worth utilities for each attribute and level.
MaxDiff
Best-worst scaling — rank features or messages by relative importance from trade-off choices.
AHP
Analytic Hierarchy Process — derive priority weights from pairwise comparisons with a consistency check.
Market Share Simulator
Simulate how share shifts as you change product features or price.
Brand
Brand Funnel
Track awareness → consideration → preference → purchase → loyalty conversion at each stage.
Perception Map
Position brands on a 2-D map of key attributes to reveal competitive whitespace.
Brand Equity Tracker
Measure and trend brand equity across awareness, associations, and loyalty.