How evo used data-driven personalization to acquire more traffic and retain more customers
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Transcript of How evo used data-driven personalization to acquire more traffic and retain more customers
Seattle | Portland | evo.com
evo.com Stocks a Wide Variety of Brands
Andrew Pearson
Windsor Circle
VP of Marketing
@arjpearson@windsorcircle
www.windsorcircle.com
Repeat buyers = 8% of site visitors, but 41% of revenue
Source: Adobe Loyal Shopper’s Report April 2013
Source: Adobe Loyal Shopper’s Report April 2013
Enterprise Data Feeds:
Data updated continuously into custom fields or relational tables in your email software
and more
Guaranteed eCommerce-to-ESP Integrations:
and more
Our Agenda
Acquire Engage Retain
Old School Marketing: A 1st Time Buyer’s Path
Customer makes
1st purchase
Receives a
welcome email
Receives mass-
marketing emails
Never makes a 2nd
purchase, & unsubscribes
evo.com
Social PLADirectPaidOrganic Store
Email Sign-Up
Welcome #1 Welcome #2 Welcome #3
Email Sign Up Welcome Program
Joe – Win him back!
Welcome email
Brand recommendation
1
15
5 Post purchase thank you
Product Education Series67
Product Recommendation135
Best customer email
(sent after trigger)215
402nd purchase
$560 – Ski Boots
803rd purchase
$50 - Socks
1404th purchase
$240 - Jacket
01st purchase
$75 Goggles
Days
No purchases
Welcome email1
5 Post purchase thank you
Product recommendation10
Brand recommendation25
Win-back email 1
Win-back email 2
Win-back email 3
80
92
125
1352nd purchase
$120 - Jacket
Days
01st purchase
$240 – Jacket, Gloves
Sally – Recommend & Reward!
How Data Can Drive Personalized Lifecycle Marketing
Survey110
Utilizing Purchase History to Retain
Customers & Lift Revenue
58%
25%
Open Rates
Click Rates
1. Guide to Trying on Your Boots
Email subject:
Ski Boot Guide – Part 1
Open rate: 67.8%
Click rate: 38%
Why this works:
Relevant Image
Clear CTA
2. How-to VideoEmail subject:
Ski Boot Guide – Part 2
Open rate: 56%
Click rate: 25%
Clear header
Strong image
Simple text
including link to
information from
Email 1
Clear CTA
3. Ski Boot Guide – Part 3Email Subject:
Ski Boot Guide – Part 3
Open rate: 49%
Click rate: 8%
Mentions purchased
product
Use of engaging image
Clear CTA
Why this works:
How we do it
Data Drives Results
3.2
9.6
Times theOpen Rates
Times theClick Rates
30
Precision TimingHow evo Saw 3.2 Time the Opens & 9.6 Times the Clicks with Automated How-to Guides
WindsorCircle.com/LiftYourRevenue
Initialization Optimization Retention Automation
Win by: • Volume • Content • Data
Key Metrics: • List Size• Send Volume
• Opens• Clicks
• Conversions• Engaged Subscribers• Churn
Key Activities: • Build list• Send frequently
• Frequent Sends• Content Creation• Dashboard and Reporting
• Contact Strategy• RFM Analysis• Market Basket Analysis
ESP Selection: • Cost • Better Feature Sets • Cost• Integration• Segmentation• Automation
Segmentation: • None • Available but Limited • Advanced• Purchase history• Web history
Automation: • None • None • Post Purchase Welcome Series• Win Back Campaigns• Cross Merchandizing• Reviews
The 3 Stages of Email Marketing
Welcome #1 Welcome #2 Welcome #3
Purchase
Post Purchase
Post Purchase #2
Post Purchase #3
Marketing Calendar
From Welcome to Purchase 1 to Purchase 2
Non Purchasers
Category
Brand Affinity
Regional
Segmented Promotions:
Brand Recommendation
Contest
Review Request
Social Comms
RFM Segments
RFM
R1M1F1: Best Customers
RxFxM1: Big Spenders
R1F4M1: New Spenders
Win Back #1
Win Back #2
Win Back #3
R4F1M1: Churning Customers
Purchase
RFMPurchase
Marketing Calendar
Automatic Segmenting by Customer Score
Understanding Customer Latency – evo.com
Average Latency
(All Customers)
2011: 153 Days
2012: 174 Days
2013: 194 Days
Median Latency
2011/12 Season
All customer: 25 days
Best customers: 33 days
2012/13 Season
All customer: 25 days
Best customers: 20 days
2013/14 Season
All customer: 30 days
Best customers: 46 days
9 Pillars of Customer Retention
ANALYZE
CONNECT THANK
REWARD
GET MORE
WIN BACKEVANGELIZE
LISTEN
ACQUIRE
Contests:• Email acquisition• Brand loyalty• Co-marketing
Social Media:• Highlight “evoCollective”• Core Values• Culture
evoCollectivespotlights include gear affinity
APPENDIX
44
Retention,
Perfectly
Brewed
How CoffeeForLess makes $1MM+ a year
from Data-Driven Lifecycle Emails
45
Retention, Perfectly Brewed
Working Person’s Store
makes over $1MM a year
by personalizing product
recommendation emails
Heavy Duty
Personalization
46
Smooth SegmentationSkinMedix sees over 50x ROI by
segmenting weekly emails and
automating customer retention
47
MILLION DOLLAR CIRCLEDriving Real ROI from Retention Automation
50x ROI
Congratulations to these 3 retailers making over
$1MM a year from Retention Automation
66%125%
increase in opens
increase in clicks
3x the opens
48
Download the Case Studies Today
www.windsorcircle.com/onemillion
49
How-To GuidesWindsorcircle.com/resources#how-to-guides