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Referral Analytics ​

Overview ​

Track the performance of your referral program through comprehensive metrics and analytics. Monitor referral sharing, conversion rates, revenue impact, and advocate activity to optimize your program for maximum growth.

Key Metrics ​

Total Coupons Created ​

Total number of Friend discount codes generated.

What It Measures:

  • How many Friends have claimed referral discounts
  • Reach of your referral program
  • Friend engagement with referral offers

Example:

Total Coupons Created: 450
= 450 Friends claimed discount codes

Successful Referral Orders ​

Number of orders placed using Friend discount codes.

What It Measures:

  • Conversion rate from claim to purchase
  • Actual program effectiveness
  • Friend purchase behavior

Calculate Conversion:

Successful Orders: 180
Total Coupons: 450
Conversion Rate: 180 ÷ 450 = 40%

Benchmarks:

  • Excellent: 40%+ conversion
  • Good: 25-40% conversion
  • Needs Improvement: <25% conversion

Total Points Awarded ​

Total points earned by Advocates from successful referrals.

What It Measures:

  • Reward cost of program
  • Advocate earning from referrals
  • Program investment

Example:

Configuration: 500 points per referral
Successful Referrals: 180
Total Points: 180 × 500 = 90,000 points

At 100:1 ratio: $900 in future discounts

Total Coupon Value ​

Total discount value claimed by Friends.

What It Measures:

  • Direct cost of referral program
  • Friend incentive investment
  • Discount liability

Example:

Discount: 25% off
Friend Orders: 180 orders
Average Order: $80
Total Discount: 180 × $80 × 0.25 = $3,600

Money Spent by Customers ​

Total revenue from Friend purchases using referral discounts.

What It Measures:

  • Revenue generated by referral program
  • Program ROI
  • New customer value

Calculate ROI:

Revenue from Referrals: $14,400
Program Cost (Points + Discounts): $4,500
Net Revenue: $9,900
ROI: $9,900 ÷ $4,500 = 2.2× return

Total Views ​

Number of times referral landing page was viewed.

What It Measures:

  • Referral link clicks
  • Initial interest
  • Traffic from Advocates

Calculate Click-Through:

Total Views: 1,200
Total Coupons Claimed: 450
Claim Rate: 450 ÷ 1,200 = 37.5%

Total Referral Clicks ​

Number of times referral links were clicked (across all sharing methods).

What It Measures:

  • Sharing effectiveness
  • Advocate activity
  • Channel performance

Insight:

If Views < Clicks:
- Multiple clicks before landing on site
- Some clicks don't convert to views

Time Series Analytics ​

New Advocate Time Series ​

Track how many new Advocates join the program over time.

Insights:

  • Program adoption rate
  • Growth trends
  • Impact of promotions

Referral Share Time Series ​

Track when Advocates share their referral links.

Insights:

  • Sharing patterns (days/times)
  • Campaign effectiveness
  • Seasonal trends

Referral Click Time Series ​

Track when referral links are clicked.

Insights:

  • When Friends are most engaged
  • Response time to shares
  • Best timing for referral campaigns

Referral Claim/Rejection Time Series ​

Track Friend discount claims over time.

Shows:

  • Claims: Friends who entered email and received discount
  • Rejections: Pop-ups closed without claiming

Calculate Claim Rate:

Claims: 450
Rejections: 550
Total Pop-ups: 1,000
Claim Rate: 450 ÷ 1,000 = 45%

Optimization:

  • Low claim rate? Improve pop-up copy or discount offer
  • High rejection? Test different discount amounts

Campaign Revenue by Day ​

Daily revenue from referral purchases.

Use Cases:

  • Track revenue trends
  • Identify peak days
  • Measure promotion impact
  • Forecast revenue

Accessing Analytics ​

  1. Navigate to Referral > Analytics
  2. View metrics dashboard
  3. Select date range for analysis
  4. Review charts and statistics

Using Analytics to Improve ​

Scenario 1: Low Conversion Rate ​

Data:

Coupons Created: 500
Successful Orders: 75
Conversion: 15% (low)

Analysis:

  • Friends claiming but not purchasing
  • Discount may not be compelling enough
  • Minimum order value too high

Actions:

  • Increase discount amount
  • Lower minimum order requirement
  • Add urgency (discount expiration)
  • Follow up with Friends via email

Scenario 2: High Views, Low Claims ​

Data:

Total Views: 2,000
Coupons Claimed: 300
Claim Rate: 15% (low)

Analysis:

  • Pop-up not converting
  • Offer unclear
  • Too many form fields

Actions:

  • Improve pop-up copy
  • Highlight discount value more clearly
  • Simplify claim process
  • A/B test different pop-up designs

Scenario 3: Few Active Advocates ​

Data:

Total Customers: 10,000
Active Advocates: 150
Participation: 1.5% (low)

Analysis:

  • Customers not aware of program
  • Rewards not compelling enough
  • Sharing is too difficult

Actions:

  • Promote referral program more (email, widget)
  • Increase Advocate point reward
  • Make sharing more prominent
  • Add referral CTA to order confirmation

Scenario 4: Strong ROI ​

Data:

Revenue: $50,000
Program Cost: $8,000
ROI: 6.25× (excellent)

Analysis:

  • Program highly effective
  • Good balance of incentives
  • Strong Advocate engagement

Actions:

  • Maintain current structure
  • Scale program promotion
  • Consider increasing rewards slightly
  • Share success with team

Best Practices ​

1. Monitor Weekly ​

Check analytics regularly:

  • Review key metrics
  • Track trends
  • Identify issues early
  • Adjust as needed

2. Set Benchmarks ​

Establish targets:

  • Conversion rate goal: 35%
  • Claim rate goal: 40%
  • ROI target: 3×+
  • Advocate participation: 5%+

3. Test and Optimize ​

Continuous improvement:

  • Test different discount amounts
  • Try various Advocate rewards
  • Experiment with pop-up copy
  • Adjust cookie lifetime

4. Calculate True ROI ​

Include all costs:

  • Friend discounts
  • Advocate points
  • Lost margin on discounted orders
  • Compare to customer acquisition cost

5. Track Customer Lifetime Value ​

Measure long-term impact:

  • Do referred customers return?
  • Average LTV of referred customers
  • Retention rate comparison
  • Program payback period

Summary ​

Referral Analytics provide comprehensive visibility into your program's performance, from high-level metrics like total revenue and ROI to detailed time series data showing when customers share, claim, and purchase. By monitoring conversion rates, claim rates, and revenue trends, you can optimize your referral program for maximum growth while maintaining healthy economics.

Use these insights to refine discount amounts, Advocate rewards, and program promotion to create a referral engine that consistently brings new customers to your store.