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Automobile Customer Analytics

Advanced Customer Behavior & Sentiment Analysis

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Overall Sentiment Score (Positive)
Customer Satisfaction
Net Promoter Score
Issue Resolution Rate
Customer Sentiment Trend
Sentiment Distribution
💡 AI-Generated Insights
Positive Trend in Electric Vehicle Satisfaction

Customer satisfaction for electric vehicles has increased by 12% over the past quarter, primarily driven by improved battery performance feedback and charging infrastructure satisfaction.

Potential Issue with Model Y Infotainment System

Analysis shows a 23% increase in negative sentiment related to the infotainment system in Model Y vehicles. Consider prioritizing software updates for this model.

Loyalty Program Driving Positive Sentiment

Customers enrolled in the loyalty program show 18% higher satisfaction scores and are 32% more likely to recommend your brand to others.

Dummy Data
Live AI Insights coming soon!
Sentiment by Vehicle Category (Top 5)
Sentiment by Region
Common Topics in Customer Feedback
Total Topics Analyzed: | Total Mentions:
Customer Journey Funnel
Purchase Funnel Conversion
Customer Lifetime Value by Segment
Service Visit Frequency
Under Construction
Coming soon!
Churn Risk by Customer Segment
Predictive Maintenance Alerts 2,855 Vehicles
Satisfaction Forecast
Sales Growth Forecast
Review Volume Trend
Review Sources
Recent Customer Reviews 245 New
"The fuel efficiency of my new sedan is outstanding. I'm getting 15% better mileage than advertised!"
John D. • Model X Sedan • 2 days ago Positive
"Disappointed with the infotainment system. It's slow to respond and the interface is not intuitive."
Sarah M. • Model Y SUV • 5 days ago Negative
"The vehicle performs well overall, but I expected better interior materials for this price point."
Robert T. • Luxury Z Model • 1 week ago Neutral
"Excellent customer service experience at the dealership. They went above and beyond to address my concerns."
Lisa K. • Electric E Model • 1 week ago Positive
Definitions — Methodologies & KPI Examples

Purpose: A concise reference of the analytical methodologies and key performance indicator (KPI) definitions used by the Customer Behavior & Sentiment Analysis dashboard.

Methodologies

  • Data collection: Integrate and harmonize data from surveys, reviews, social media, customer support, CRM, sales/DMS, telematics, and service records. Use IDs (customer ID, VIN) to join tables and produce unified records.
  • Sentiment analysis: Apply NLP classifiers to label feedback as positive, neutral, or negative. Aggregate labels to compute sentiment percentages and trends.
  • Topic extraction: Use text classification and topic modeling to surface common themes and tag feedback by topic and sentiment.
  • Customer journey & funnel analysis: Classify customers into journey stages (Awareness, Consideration, Purchase, Post-purchase, Loyalty) using behavioral rules and event logs. Compute counts and percentages per stage and visualize changes over time.
  • Predictive modeling: Train classification/regression models (e.g., logistic regression, random forest, XGBoost, time-series models like ARIMA/Prophet) for churn prediction, maintenance alerts, satisfaction forecasts, and sales growth forecasting.
  • AI-generated insights: Use statistical tests and model outputs to highlight significant changes, anomalies, or recommended actions.
  • Filtering & interactivity: Ensure all metrics and visualizations recalculate for selected filters (vehicle type, region, data source, customer segment).

Key KPI definitions & example calculations

Overall Sentiment Score

Short definition: Share of feedback that is positive.

Formula:

Positive sentiment (%) = (number_positive_items / total_feedback_items) * 100

Notes

  • These definitions are intentionally compact — they focus on method and calculation so they can be referenced directly by analysts and engineers implementing the dashboard.
  • If you want formulas expanded or one-page examples for a specific KPI (e.g., sample SQL or pseudocode), I can add them as low-risk supplements.