No doubt about it: CLV is the north star metric of any retailer. However, it is also one of the most misunderstood, neglected, and ignored KPI. As we're collectively saying RIP to cookies, there are 3 jobs to be done by eCommerce leaders: 1.  Nail acquisition: Acquire the right customers at a decent CAC 2.  Nail conversion: Ethically convert customers by matching them with the right products, using the right narrative 3.  Nail retention: Onboard and nurture the right customers so that you make them come back and promote you All of these 3 activities fall into a broader methodology, called Customer Value Optimization

1. How to increase CLV & decrease CAC
Valentin Radu | 8th of December 2021

2. 01
02
03
04
05
The eCommerce Growth Formula
What affects the CLV
Customer Segmentation
How to Improve CLV
The CVO Impact

3. There Are Only Two
Ways To Grow Any Business
A. Acquire more customers
B. Get each customer to buy from you more & more
often

4. The common growth eCommerce formula

6. The actual growth eCommerce formula

7. Acquiring
customers is more
expensive than ever

8. *Source: Wordstream state of Facebook Advertising, eMarketer and Statista
Since 2013, Facebook CPC has grown 8 times,
while retail eCommerce sales worldwide have
increased by 158%
Retail eCommerce Sales worldwide 2013 -2021 (158% growth)
Average Facebook CPC 2013 - 2021 (800% growth)
More customers: Traffic

9. eCommerce Growth Formula
http://bit.ly/eCommerceGrowthFormula

10. Acquisition Conversion Retention
+ +
Customer Value Optimization
Customer research >
Better targeting
Better creatives
Better ROAS
Customer research >
Better UX & LPs
More relevant messaging
Better conversion rate
Customer research >
Better Onboarding
Better Remarketing
Better customer retention

11. Growth
Growth
Generating
Factors

12. 2015
$11M
Annual
revenue
11
countries
90
employees

13. Initial Symptoms
+95% <20%
Revenue Customer Retention
-20% <40
YoY CLV NPS

14. 2019
20X less
revenue
1
country
<10
employees

15. "For many events, roughly 80% of
the effects come from 20% of the
causes"
True in eCommerce, as well.
Vilfredo Pareto

16. Not all the customers are
created equal.
Some are better than the
others.
The best ones =
Ideal Customer Profile (ICP)

17. 1 ICP generates margin
as much as
376 low-value customers.
It’s not fair smart to treat
everyone the same.

18. R F M
How to improve CLV & decrease CAC
using RFM Segmentation

19. RFM Analysis
30%
After 30% of the revenue is
generated by returning
customers, you have to do RFM
segmentation

20. RFM is an acronym for:
RFM Customer Segmentation
RFM segmentation is a method to identify the most important type of customers by grouping them according scores to
their recency, frequency & monetary values.
That allows companies to target specific clusters of customers with more relevant for their particular behavior – and thus
generating higher rates of response, increased loyalty and better customer lifetime value.
“How recently did the
customer purchase?”
“How often do they
purchase?”
“How much do they spend?”
ECENCY REQUENCY ONETARY
R F M

21. RFM Groups
Soulmates
Your most frequent buyers, have placed the highest number of
orders and of the highest value.
Ex-Lovers
They used to be True lovers, but have abandoned buying from
your website.
Lover
Active, have placed a good amount of orders or significant value.
Potential lover
Potential to become active customers, have placed more orders
than Flirting.
Flirting
Have placed more than 3 orders of high value.
Passionate new ones
Have placed their second order, with a high monetary
value.
Platonic friend
Active, have placed a moderate amount of orders or moderate
value.
About to dump you
Rather inactive; have placed last order more than half a year ago.
Fresh apprentice
Fresh ones, have just placed their first order.
Breakup
Inactive & low value spenders.

22. Depending on the client base one can define fewer or more of the RFM groups exemplified above. For small client bases there’s no
need to have a large number of groups. The idea is to have manageable chunks of people that share a particular behaviour in
relation to your company.
Soulmates
These customers bought:
> Most recently
> Most often
> Highest monetary values
R F M
5
= 5
= 5
=
Share of Customers: 3,21%
Share of Revenue: 12,42%

23. Total lifetime of the shop
5.6% of the customers
24.6% of the revenue
Last Month
20.2% of the customers
19.9% of the revenue

24. RFM Analysis
RFM analysis reveals data
anomalies that allows eCommerce
managers to understand which are
the most important groups of
customers when they balance the
customer acquisition cost with the
margin they generate.
“Soulmates” customer
group is one of the
smallest, but the most
profitable.

25. Last month
Lifetime
Next steps
1. Monitor their customer experience in real-time
2. Treat their objections in real-time
3. Research the ICP and build look-a-like audiences
Main Goal
Keep them happy & acquire more like them
1.7% 10.1%
Customers Revenue
20.1%
Customers Revenue
19.1%

26. Last month
Lifetime 1.6% 1.8%
Customers Revenue
18.4%
Customers Revenue
24%
Next steps
1. Surprise & Delight them
2. Run Cohort A/B testing to identify how to
onboard the next ones better
3. Run tailor-made campaigns
Main Goal
Persuade them to place the2nd order

27. Next steps
1. Treat their objections in real-time
2. Run tailor-made campaigns
3. Acquire more like them
Main Goal
Transform them in Soulmates
Last month
Lifetime 5% 25%
Customers Revenue
12%
Customers Revenue
14%

28. Ex-Lovers
These customers bought:
> Many times
> A long time ago
> High monetary values R F M
1
= = =
5 5
Depending on the client base one can define fewer or more of the RFM groups exemplified above. For small client bases there’s no need to have a
large number of groups. The idea is to have manageable chunks of people that share a particular behaviour in relation to your company.

29. Last month
Lifetime 20% 29%
Customers Revenue
0%
Customers Revenue
0%
Next steps
1. Find what stopped them from buying
2. Treat their objections
3. Tailor-made campaigns
Main Goal
Re-engage them

30. Don Juan
These customers bought:
> A long time ago
> Only once
> Big monetary values
R F M
1
= = =
1 5
Depending on the client base one can define fewer or more of the RFM groups exemplified above. For small client bases there’s no need to have a large
number of groups. The idea is to have manageable chunks of people that share a particular behaviour in relation to your website.

31. It is crucial to monitor the user experience and the
customer experience

32. Next steps
1. Find what stopped them from buying
2. Treat their objections
3. Tailor-made campaigns
Main Goal
Re-engage them
Last month
Lifetime 20% 29%
Customers Revenue
0%
Customers Revenue
0%

33. Revenue by segment
Revenue by RFM Group

34. CLV by RFM Group

35. How to improve
CLV
& decrease
CAC

36. 1. Change the company mentality

37. Customer-centric
2 Types of companies
● They realize that the main driver of demand is customer
behavior.
● They know that customer behavior can be monitored and
influenced by analyzing the data.
● Success for them means CX, CLV, Customer retention
● Their departments are all orchestrating a fluent customer
journey
● Have a unique source of truth around their customers.
● They segment, monitor, understand and nurture their
customers with the latest technologies.
● Think that the demand just happens out of the
blue
● Communicate mainly features, price or discounts.
● Define success by looking only at things like
traffic, CPC, or revenue.
● Their departments are silos that run separately
and treat customers without understanding the
previous and the next touchpoint in their
customer journey.
● Vulnerable to competition & market changes
Product-centric

38. 2. Monitor what matters

39. CAC Customer Acquisition Cost
NPS Net Promoter Score
CLV Customer Lifetime Value
M Margin
RR Customer Retention
DBT Days Between Transactions
CLV Customer Lifetime Value

40. Chances to place the next order
Source: Omniconvert Reveal, aggregated data from 2231 stores
https://www.omniconvert.com/customer-lifetime-value-ecommerce-benchmark/

41. Chances to place the next order
Source: Omniconvert Reveal, aggregated data from 151 stores

42. 1 2
2 3
3 4
order order
order order
order order
Chances to place the next order
23.6%
38.1%
47.2%
61% higher
101% higher!!!
Source: Omniconvert Reveal, aggregated data from 151 stores

43. 1
order
After 24 days...
Chances to place the next order
80%
Source: Omniconvert Reveal, aggregated data from 151 stores
After 193 days...
chances
20%
chances

44. 3. Qualitative Research

45. Add the customer voice in the mix to correlate the customer feedback with the
quantitative data
The Qualitative research will reveal customer groups’ reasons to buy and the barriers in relation to Products
and Services.
These will be translated into insights that will help define the Ideal Customer Profile.

46. Soulmates
Lovers
Ex Lovers
Flirting
About to dump
Breakup
Fresh
Platonic Friends
Don Juans
# of recipients
3334 (3.21%)
8486 (8.17%)
3722 (3.58%)
571 (0.55%)
25,728 (24.78%)
25,761 (24.81%)
807 (0.78%)
2011 (1.94%)
103 (0.10%)
NPS Demographics Reasons won Main Barriers Reasons lost
JTBD

47. Qualitative research
Insights
Products issues
Quality
Features
Price
Brand
Services issues
Delivery time
Delivery cost
Client Service
Return policy
JTBD data
Struggling moments
Jobs
Triggers
Forces of progress

48. 4. Improve Customer Acquisition
> Conversion > Retention

49. https://bit.ly/CVOstrategy

51. http://bit.ly/free-CVO-course

52. Thank you!
valentin.radu@omniconvert.com
Linkedin.com/in/valentinradu/