Your customers — do you really know them?
Customer Insight Lab turns scattered customer data into decisions.
01 · CUSTOMERS
Who are your customers?
Segment your customers, measure their value, and build detailed profiles.
Identify distinct customer groups with LCA segmentation, build AI-generated personas, and quantify every segment's economic value with CLV/LTV, CAC vs LTV, and profit migration analysis.
SUMMARY
5 distinct segments identified
LCA segmentation · 2,847 customers · RFM-based
Average CLV
$538
Across all segments
Top Segment
28%
Champions
At-Risk
18%
Require action
LTV:CAC
3.4×
Average ratio
Customer Segments · Share
CLV vs CAC by Segment
| Segment | Avg CLV | CAC | LTV:CAC |
|---|---|---|---|
| Champions | $1,240 | $180 | 6.9× |
| Loyal | $840 | $160 | 5.3× |
| At Risk | $320 | $155 | 2.1× |
| New | $210 | $165 | 1.3× |
| Lost | $80 | $155 | 0.5× |
PERSONA PROFILES
One card per segment
AI-generated from behavioral and demographic patterns
low recency days · 199
low avg order value · 179
high lifetime value · high frequency · 126
high recency days · 96
02 · LOYALTY
Why do they stay or leave?
Measure satisfaction, predict churn, and understand why customers leave.
Track NPS, CSAT, and CES in one dashboard. Predict which customers will churn before they do. Analyze open-ended feedback with sentiment analysis, topic modeling, and complaint detection.
NPS Score
+42
industry avg +28
CSAT
78%
satisfied
Churn Rate
8.3%
monthly
Win-back
22%
success rate
Cohort Retention Heatmap
Churn Risk Distribution
ML model · 30-day prediction window
⚠ 512 customers flagged as high risk
Recommended: Win-back campaign + Next Best Action
PER-SEGMENT BREAKDOWN
Mean CSAT, top-box & bottom-box
The aggregate score often hides segment-level deterioration
| Segment | N | Mean | Top-box | Bottom-box |
|---|---|---|---|---|
| VIP | 159 | 4.20 | 43% | 0% |
| Regular | 538 | 3.94 | 28% | 0% |
| New | 186 | 3.61 | 16% | 1% |
| At Risk | 117 | 3.01 | 7% | 3% |
03 · BEHAVIOR
How do your customers behave?
Track the customer journey, identify drop-off points, and understand channel preferences.
Follow customers from first touch to repeat purchase with RFM analysis, basket analysis, and drop-off funnels. Understand where they prefer to engage — store, online, or mobile.
Avg Frequency
3.2×
purchases/mo
Cart Abandon
66%
of carts
Online Share
62%
vs in-store 38%
Basket Size
$84
avg order value
Drop-off Funnel
RFM Score Distribution
STAGE DETAILS
Users per stage & drop from previous
Late large-percentage drops are usually easier to fix
| Step | Stage | Users | % of start | Drop |
|---|---|---|---|---|
| 1 | completed_purchase | 260 | 100.0% | – |
| 2 | payment_step | 314 | 120.8% | -20.8% |
| 3 | started_checkout | 390 | 150.0% | -24.2% |
| 4 | added_to_cart | 535 | 205.8% | -37.2% |
| 5 | viewed_product | 1,224 | 470.8% | -128.8% |
| 6 | visited | 2,000 | 769.2% | -63.4% |
04 · STRATEGY
What to sell and at what price?
Optimize pricing, model customer choices, and track brand health.
Find the optimal price point with Van Westendorp and Gabor-Granger. Model customer choices with Conjoint, MaxDiff, and AHP. Track brand health from awareness to advocacy with the brand funnel.
Optimal Price
$32
Van Westendorp
Awareness
82%
brand funnel
Advocacy
14%
promoters
Top Attribute
Cost
conjoint
Brand Funnel
Price Sensitivity · Van Westendorp
Optimal price point: $32
PRICE POINTS AND MEANING
Each price point answers a different pricing question
PMC and PME bracket the acceptable range
| Point | Price | Meaning |
|---|---|---|
| PMC (Point of Marginal Cheapness) | $20.00 | Lower acceptable bound — below this, quality concerns dominate |
| OPP (Optimal Price Point) | $22.77 | "Too cheap" pressure equals "too expensive" pressure — least rejection |
| IPP (Indifference Price Point) | $20.00 | Equal share consider it cheap and expensive — typical perceived market price |
| PME (Point of Marginal Expensiveness) | $22.77 | Upper acceptable bound — above this, affordability concerns dominate |
ALL IN ONE LAB
Everything Customer Insight Lab does.
40 methods across Customers, Loyalty, Behavior, and Strategy.
Segmentation
Customer segments, LCA segmentation, and data-driven personas.
Customer value
CLV / LTV, CAC vs LTV, high-value & profit segments, value migration.
Satisfaction
Satisfaction dashboard with CSAT and CES detail.
Retention & churn
Churn prediction, cohort retention, lifecycle, win-back, next best action.
Voice of Customer
Sentiment analysis, topic modeling, review insights, complaint detection.
Behavior
Journey, repeat purchase, frequency, RFM, basket, drop-off funnel.
Experience
Store vs online, channel preference, touchpoints, service-delay impact.
Pricing
Price Sensitivity Meter, Gabor-Granger, optimal price finder.
Choice modeling
Conjoint, MaxDiff, AHP, and a market-share simulator.
Brand
Brand funnel, perception map, and brand-equity tracker.
Auto interpretation
Every analysis comes with a plain-language AI reading of the result.
One workbench
40 methods across 4 sections — no switching tools, no re-uploading.
ALSO IN YOUR DATA LAB
More analysis tools.
Every lab is purpose-built for a different type of analysis — same interface, different focus.
Understand your customers.
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