Customer Analytics

Customer Analytics provides insights into who your customers are, how they behave, and how much value they bring to your business.

What Customer Analytics Reveals

Understanding your customers helps you:

• Increase retention — Identify at-risk customers before they leave
• Boost order value — Recognize patterns in high-value purchases
• Improve targeting — Segment customers for personalized marketing
• Optimize inventory — Stock products your best customers prefer
• Enhance experience — Identify pain points in the customer journey

Key Metrics

Customer Lifetime Value (CLV)

The total revenue you can expect from a customer over their relationship with your business:

CLV = Average Order Value × Purchase Frequency × Customer Lifespan

Benchmarks by business type:

Purchase Frequency

How often customers return:

Purchase Frequency = Total Orders ÷ Unique Customers (in period)

Target improvement: Increase frequency by 10% = 10% revenue growth (without new customers)

Customer Segments

Automatic segmentation based on behavior:

Popular Items by Segment

See which products different customer types prefer:

Champions prefer:
- Premium Steak ($32)
- Wine Selection ($45)
- Dessert Platter ($18)

New Customers prefer:
- Daily Special ($12)
- Soft Drinks ($3)
- Starter Combo ($8)

Analytics Dashboard

Customer Overview

┌───────────────────────────────────────────────────────────┐
│ Customer Summary (Last 30 Days)                           │
├────────────────┬─────────────────┬────────────────────────┤
│ Total Customers│ 1,240           │ ▲ 8% vs last month     │
│ New Customers  │ 156             │ ▲ 12% vs last month    │
│ Returning Rate │ 42%             │ ▲ 3% vs last month     │
│ Avg Order Value│ $28.50          │ ▲ $1.20 vs last month  │
└────────────────┴─────────────────┴────────────────────────┘

Hourly Patterns

Understand when your customers visit:

Insight: Lunch rush (10 AM-2 PM) drives 35% of daily traffic—optimize staffing accordingly.

Order Type Preferences

How customers choose to order:

Order Type Distribution:
┌────────────────────────────────────────────────────┐
│ Dine-in     ████████████████████████░░░░░░░░  62%  │
│ Takeaway    ███████████░░░░░░░░░░░░░░░░░░░░░  28%  │
│ Delivery    ████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░  10%  │
└────────────────────────────────────────────────────┘

Using Analytics for Growth

Retention Strategy

1. Identify at-risk customers (haven't ordered in 30-60 days)
2. Create targeted offers — "We miss you" discount
3. Track reactivation — Measure success rate
4. Refine approach — Test different incentives

Personalization Opportunities

Use customer data to personalize:

• Recommendations — "Customers like you also ordered..."
• Timing — Send promotions when they typically order
• Channels — Reach them via their preferred method (app, SMS, email)
• Offers — Champions get exclusive access, new customers get introductory deals

Menu Optimization

Analytics reveal product insights:

• Popular combinations — Create bundles of frequently paired items
• Underperformers — Identify items with low attachment rates
• Price sensitivity — Test how price changes affect different segments
• Seasonal preferences — Adjust menu for different customer moods

Customer Journey Tracking

Funnel Analysis

Track customers through your experience:

Website/App Visit:    1,000 visitors
↓ View Menu:           750 (75%)
↓ Add to Cart:         400 (53% of viewers)
↓ Start Checkout:      280 (70% of cart)
↓ Complete Order:      220 (79% of checkout)

Opportunity: 30% cart abandonment—test reminder notifications.

Cohort Analysis

Track groups of customers over time:

Trend: Improving retention—identify what changed in March.

Privacy and Compliance

Bizaldo handles customer data responsibly:

• Anonymized analytics — Individual behavior aggregated for insights
• Opt-out options — Customers can request data exclusion
• GDPR/CCPA compliance — Data retention policies enforced
• Secure storage — Customer data encrypted at rest

In One Sentence

Customer Analytics segments your customers by behavior and value, revealing patterns that help you retain more customers and increase their lifetime value.

Key Actions

Outputs

The analytics system produces:

• Segment distribution — Customer breakdown by behavior
• CLV calculations — Lifetime value by customer and segment
• Cohort retention — Retention curves over time
• Order patterns — Preferences and timing insights
• Conversion funnels — Journey step completion rates

Related Documentation

• Dashboard Overview — Main dashboard features
• Sales Forecasting — Demand predictions
• Reports — Detailed analytics exports