This document summarizes an eCommerce metrics webinar that will teach companies what metrics to track. It includes an agenda covering introductions, segmenting data, key metrics to track including order, marketing, and customer metrics. It features a case study on Diamond Candles and discusses how Retention Science uses machine learning to predict customer behavior and automate retention campaigns. The webinar discusses ways to segment data by source, product, time, device, and customer type and defines metrics like average order value, conversion rate, customer lifetime value, and more.

1. eCommerce Metrics Webinar
Learn what every eCommerce company needs to track.
Live Tweet Hashtag
#eCommerceMetrics
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Click here to view the webinar

2. Agenda
Introductions
Segmenting your data
What metrics to track
Order Metrics
Marketing Metrics
Customer & Advanced Metrics
Insider information
Diamond Candles case study

3. Diamond Candles
Diamond Candles is on a mission to make home fragrance
fun. They combine the scents of premium 100% soy candles
with an exciting and fun RINGREVEAL™ experience. Their
candles are handmade in Durham, NC and we release fresh,
fruity, floral and exotic scents all year long.
Justin Winter
CEO and Co-founder
Diamond Candles
Diamondcandles.com

4. Retention Science
Retention Science is the best way to target, engage, and
retain your customers. Our marketing platform uses machine-
learning algorithms to predict customer behavior and
automate 1-to-1 retention campaigns. We make advanced
data science accessible to all marketing teams.
Ryan Lee
Customer Success Manager
Retention Science
Retentionscience.com

5. Segmenting Data

6. Ways to segment your data
Traffic source and channel
• Direct, referral, organic, PPC,
other advertising
Product & category affinity
• Brands, types of products, styles,
etc.
Time based cohorts
• Hours, days, weeks, holiday
periods
Device
• Browser, OS, desktop, mobile,
tablet, screen size
Customer Type
• Discount, high value,
subscription, hybrid, etc.

7. Key metrics to track

8. Order Metrics
Average Order Value
What does an order mean to you?
Calculation: (Total Sales / Orders)
Example: [$35,000 total sales]/[800 orders] = $43.75
Average Business Margin
Do you know if you’re making money?
Calculation: (Sale Price – Product Cost) / Sale Price
Example: ([$45 sale ]– [$30 cost])/[$45 sale] = 33.3% margin
Average Order Profit
How much money are you actually
making? (minus discounts)
Calculation: (AOV x Margin)
Example: [$43.89 AOV] x 33.3% margin = $14.57 Avg. Profit

9. Marketing Metrics
Cost per acquisition
How much is each customer costing you?
Calculation: (Marketing & Sales Spend / Customers)
Example: [$20,000 spend]/[575 customers] = $34.78 CPA
Conversion rate
How efficient is your website? Different types
of conversion rates
Calculation: (Orders / Website Visitors)
Example: [95]/[4500 visitors] = 2.1% CR
Repeat customer rate
Are customers coming back?
Calculation: (Repeat Customers / Total Customers)
Example: [550 repeats]/[1200 total] = 45.8% RCR
Revenue per visit
Are you making the most of every visitor?
Calculation: (Total Sales / Total Visitors)
Example: [$480,000 total sales]/[1.2m visitors] = $.40 RPV

10. Customer & Advanced
Metrics
Customer lifetime value
How much is each customer worth over
their lifetime?
Calculation: (AOV x Order Frequency) x Predicted lifetime
Example: ([$45 AOV] x [2.5 orders/mo.]) x [18 mo.] = $2025
Likelihood to purchase
What is the probability that an individual
customer will make a purchase?
Calculation: predictive data science model
Propensity to churn
What customers are in danger of churning?
Calculation: predictive data science model
Customer satisfaction rate
Are your customers happy with you?
Calculation: Regular customer survey or Net promoter score

11. Insider Information

12. Challenge:
How can you tell what channels
and campaigns are driving the
most bottom-line revenue?

13. Questions