This document discusses how calculating and increasing customer lifetime value (CLV) is important for retail success. It outlines 4 steps to increase CLV using customer data: 1) start with goals for CLV, retention rates, and share of wallet to determine data and campaign needs, 2) collect necessary customer data, 3) use data science to power predictive models, and 4) automate personalized campaigns. The presentation provides examples from L'Oreal of using technology to better understand customers and automate recommendations, replenishment, and rewards to increase CLV. Attendees will learn the business importance of CLV and how new technologies allow marketers more control over the customer experience.
3. By the end of this session, you will know…
• How to Calculate Your CLV
• How Retention Rates, CLV, and AOV Interact
• 4 Steps Required to Grow CLV
• Innovation is Putting Marketers in Control
10. This segment has been built and will be available in Salesforce within approximately 24 hours.
This segment has been built and will be available in Salesforce within approximately 24 hours.
This segment has been built and will be available in Salesforce within approximately 24 hours.
11. This is how AOV rises with Retention
The
Natural
State
of
the
Happy
Customer
13. If You’re Not Driving CLV and Retention, You’re Losing
• The State of Retailing Online 2015 (by NRF)
• AOV for repeat customers - $199
• % of sales from repeat customers - 61%
• Leading Retention Rates:
• Bonobos – 50% (via NY Times)
• Zappos – 75% (via econsultancy)
• Amazon – upwards of 90%
14. Ok… But How do I Increase CLV?
4 Phases to Increase CLV Using Data
(** Demand This of Your Technology Vendors **)
15. 1.
Knowledge
Begin
with
the
End
in
Mind
(Work
Backwards
from
End
Goals)
1. CLV,
RetenQon
Rates,
Share
of
Wallet
2. What
Campaigns
Should
I
Run?
3. What
Do
I
Need
to
Know?
4. What
Data
Do
I
Need?
5. Where
Do
I
Get
It?
28. Valuable Data Fields
• CLV (# of dollars)
• Recency (most recent order)
• Frequency (# of orders)
• First order date
• Purchase history, by:
• Product
• SKU
• Store
• Category
• Interest
• Last Purchase (same)
• Address: city, state, zip
• Predictive:
• Replenishment
• Recommendations
• Substitutes
• Complements
• Churn Dates
• Custom Fields
• Loyalty Number
• Birthday
• Skin Type / Color
29.
30.
31. What’s Planned – Marketer is in Control
• Predictive Data Science
• Replenishment Dates
• Churn Date
• Cross-Sell Hair Styling <> Hair Care
• Product Recommendations
• Substitutes
• Complements
• Reward Best Customers
32. This Ain’t Your Mother’s CRM
Technology has shifted the playing field.
You can do this better, faster, cheaper.
33. The Old Way
• Hard to reach
• Expensive
• Untrusted
• Monopoly Breeds Complacence
• Non-responsive
• They are in control
34. The New Way
• Drivers Compete for Ratings
• Friendly
• Responsive
• Convenient
• To Find
• To Pay
• To Rate
• Data Drives Better
Experience
• You Are In Control
36. “5 vendors were brought in.
No one had the offering that
Windsor Circle had.
The other vendors had people
but they did not have the technology”
37. Old School Vs. New Style
Old
School
New
Style
Cost
$100K
-‐
$10M
Capital
Expenditure
$10K
-‐
$500K
SoYware
SubscripQon
Time
1-‐3
years
Weeks
-‐
months
Ownership
IT
MarkeQng
Skillset
Data
ScienQst,
Programmer
Marketer,
Strategist
Data
Science
Data
ScienQsts
Technology
Pla]orm
38. • Game has changed
• CLV is the New Black
• Technology has put the marketer in
control
• #Start, #Test, #Scale, #Win