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Going Beyond Loyalty
Programs for Retaining
Your Customers
https://www.linkedin.com/in/yoavsusz/
Yoav_s@Optimove.com
Yoav Susz leads Optimove’s New York-based business development team,
where he is playing a major role in Optimove’s successful expansion into the
US market. Yoav specializes in helping retail brands build emotionally-
intelligent retention marketing strategies that focus on leveraging each
brand’s core identity. In his position, Yoav focuses on building relationships
with partners across the Americas. Prior to joining Optimove, Yoav served as
a corporate litigator for Israel’s leading law firm, where he represented some
of the world’s leading technology companies. Yoav holds an LLB from The
Interdisciplinary Center and an MBA from the Stern Business School at NYU.
03
More information is available at
www.optimove.com
Science-first Customer Marketing Hub
Customer
Loyalty
04
The Holy Grail in a Digital World
05
The Aim of Customer
Marketing is to Foster
Loyalty to Increase LTV
The Ultimate in
Customer Marketing
• Start a conversation
• An emotionally intelligent one
• Do so at the speed of your customers
06
What does it Take to Reach the
Ultimate in Customer Marketing?
Precision Speed
07
08
Techniques You Need to Master
• Org built for speed!
• Data science
• Experiments Design
• Catering to the customer journey
09
Org Built for Speed
• The ‘assembly line’ doesn’t work!
• We need quick turnover from ideation to execution
• CRM A-team
10
Data Science
Organizing, manipulating, modeling and
analyzing customer data is the ultimate way
to really get to know your customers
11
Data Science
Invest in the foundations - have a true single customer view as part of your marketing tech
Time
12
Data Science
First level of acquaintance – divide and conquer
Segments CohortsClusters
13
Data Science / First level of acquaintance – divide and conquer
Migration is actually the biggest part of segmentation
From / To
Registered
Only
New Active One Timers Churn
Churn One
Timers
Dormant
Registered Only
New
Active
One Timers
Churn
Churn One Timers
Dormant
80.5%
0%
0%
0%
0%
0%
0%
11.5%
60.0%
0%
0%
0%
0%
0%
0%
8.2%
89.0%
3.5%
5.6%
1.5%
1.5%
0%
31.8%
0%
89.0%
0%
0%
0%
0%
0%
11.0%
0%
92.0%
0%
0%
0%
0%
0%
7.5%
0%
91.5%
0%
8.0%
0%
0%
0%
2.4%
7.0%
98.5%
14
Data Science / Predictive models
As humans, in our day to day, we do ‘predictive’ all the time by factoring in our past experiences
In many cases, simple heuristics will do the trick unless you are sensitive to performance
PPC example - Optimize on first purchase Vs. an LTV model
When you do build a model, things to remember:
• They are as good as the raw data they seat upon
• They require customization
• One needs a ton of talent and experience to build
a proper model
15
One interaction with one message
One interaction with a few messages
Communication streams
Experiments Design
16
One interaction with one message
Scientific uplift measurement
17
The Basic Test vs Control
18
One Interaction With a Few Message Alternatives
The basic A/B test
19
One Interaction With a Few Message Alternatives
The self-optimizing campaign
20
Competing strategies
Communication Streams
• The problem of hidden cannibalization (what if I only got
revenue sooner, but did not impact LTV?)
• How can I prove that I’m really getting an uplift? (Maybe
what I was doing before Optimove was just as good…)
• The concept of “forever control” – the only way to
measure this scientifically
21
Communication Streams
22
Communication Streams
23
Communication Streams
24
Catering to the Customer Journey / The static journey
"Life is what happens while you are busy making other plans."
–John Lennon
25
Catering to the Customer Journey / The dynamic journey
Questions?

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Going Beyond Loyalty Programs to Retain Your Customers – Optimove - GrowCommerce 2017

  • 1. Going Beyond Loyalty Programs for Retaining Your Customers
  • 2. https://www.linkedin.com/in/yoavsusz/ Yoav_s@Optimove.com Yoav Susz leads Optimove’s New York-based business development team, where he is playing a major role in Optimove’s successful expansion into the US market. Yoav specializes in helping retail brands build emotionally- intelligent retention marketing strategies that focus on leveraging each brand’s core identity. In his position, Yoav focuses on building relationships with partners across the Americas. Prior to joining Optimove, Yoav served as a corporate litigator for Israel’s leading law firm, where he represented some of the world’s leading technology companies. Yoav holds an LLB from The Interdisciplinary Center and an MBA from the Stern Business School at NYU.
  • 3. 03 More information is available at www.optimove.com Science-first Customer Marketing Hub
  • 5. 05 The Aim of Customer Marketing is to Foster Loyalty to Increase LTV
  • 6. The Ultimate in Customer Marketing • Start a conversation • An emotionally intelligent one • Do so at the speed of your customers 06
  • 7. What does it Take to Reach the Ultimate in Customer Marketing? Precision Speed 07
  • 8. 08 Techniques You Need to Master • Org built for speed! • Data science • Experiments Design • Catering to the customer journey
  • 9. 09 Org Built for Speed • The ‘assembly line’ doesn’t work! • We need quick turnover from ideation to execution • CRM A-team
  • 10. 10 Data Science Organizing, manipulating, modeling and analyzing customer data is the ultimate way to really get to know your customers
  • 11. 11 Data Science Invest in the foundations - have a true single customer view as part of your marketing tech Time
  • 12. 12 Data Science First level of acquaintance – divide and conquer Segments CohortsClusters
  • 13. 13 Data Science / First level of acquaintance – divide and conquer Migration is actually the biggest part of segmentation From / To Registered Only New Active One Timers Churn Churn One Timers Dormant Registered Only New Active One Timers Churn Churn One Timers Dormant 80.5% 0% 0% 0% 0% 0% 0% 11.5% 60.0% 0% 0% 0% 0% 0% 0% 8.2% 89.0% 3.5% 5.6% 1.5% 1.5% 0% 31.8% 0% 89.0% 0% 0% 0% 0% 0% 11.0% 0% 92.0% 0% 0% 0% 0% 0% 7.5% 0% 91.5% 0% 8.0% 0% 0% 0% 2.4% 7.0% 98.5%
  • 14. 14 Data Science / Predictive models As humans, in our day to day, we do ‘predictive’ all the time by factoring in our past experiences In many cases, simple heuristics will do the trick unless you are sensitive to performance PPC example - Optimize on first purchase Vs. an LTV model When you do build a model, things to remember: • They are as good as the raw data they seat upon • They require customization • One needs a ton of talent and experience to build a proper model
  • 15. 15 One interaction with one message One interaction with a few messages Communication streams Experiments Design
  • 16. 16 One interaction with one message Scientific uplift measurement
  • 17. 17 The Basic Test vs Control
  • 18. 18 One Interaction With a Few Message Alternatives The basic A/B test
  • 19. 19 One Interaction With a Few Message Alternatives The self-optimizing campaign
  • 20. 20 Competing strategies Communication Streams • The problem of hidden cannibalization (what if I only got revenue sooner, but did not impact LTV?) • How can I prove that I’m really getting an uplift? (Maybe what I was doing before Optimove was just as good…) • The concept of “forever control” – the only way to measure this scientifically
  • 24. 24 Catering to the Customer Journey / The static journey "Life is what happens while you are busy making other plans." –John Lennon
  • 25. 25 Catering to the Customer Journey / The dynamic journey