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Use of SNA and Give-back Ratio
Monitoring to Improve Cost
Effectiveness of your Loyalty
Program
Benjamin Filaferro – filaferro@yahoo.com – May 2013
important target of a Loyalty Scheme can be found
through SNA
2
Disguised Example
34
(0.01%)
26 K
(1.5%)
73 K
(4.3%)
69 K
(4.1%)
670 K
(39.7%)
25 K
(1.5%)
683 K
(40.1%)
137 K
(8.1%)
349
(0.02%)
Out- Degree
In- Degree
Populars
InfluencerExtravert
45
5
455
If an ordinary subscriber has an
iPhone handset, on average 2.4
of its connections have iPhone
as well. However this goes up
to 8.7 if the owner is an
influencer.
If an ordinary subscriber has a
Blackberry handset, on average
1.2 of its connections also have
Blackberry as well. However
this goes up to 5.3 if the owner
is an influencer.
Number of
incoming links
Number of
outgoing
links
Benjamin Filaferro – filaferro@yahoo.com – May 2013
customers and then adjust the Loyalty Program
rules
3
Network Value of A
= (1000) x (10%) +
(200) x (50%) +
(40) x (20%) +
(100) x (15%) +
(200) x (10%)
= 100+100+8+15+20
= 243
10%
C makes 50%
of his total
transactions
to A
Illustrative
ARPU = 1000
B ARPU = 200
C
Interconnection
Revenues = 40
D
ARPU = 100
E
ARPU = 200
F
A
Disguised Example
3.4 K
(0.2%)
21K
(%1.2)
50 K
(3%)
86 K
(5.1%)
177 K
(10%)
12 K
(0.7%)
57 K
(3.4%)
89 K
(5.3%)
100 K
(5.9%)
78 K
(4.7%)
35 K
(2.1%)
93 K
(5.5%)
89 K
(5.3%)
76 K
(4.5%)
44 K
(2.7%)
82 K
(4.9%)
102 K
(6.1%)
74 K
(4.4%)
53 K
(3.2%)
25 K
(1.5%)
204 K
(12 %)
64 K
(3.8%)
35 K
(2.1%)
22 K
(1.3%)
12 K
(0.7%)
Network Value
ARP
441 K
(26.2%)
15.5 K
(0.9%)
34 K
(12.2%)
Avg. Inc. Network Size: 31
Avg. Out. Network Size: 30
Avg. ARPU: 398
Avg. Network Value: 211
Call Dur. Out/Inc: 1.39
Avg. Inc. Network Size: 15
Avg. Out. Network Size: 9
Avg. ARPU: 10
Avg. Network Value: 89
Call Dur. Out/Inc: 0.53
Avg. Inc. Network Size: 0(0*)
Avg. Outg. Network Size: 1(0)
Avg. ARPU: QR 267
Avg. Network Value: QR 0
Call Dur. Out/Inc: 16.5
Benjamin Filaferro – filaferro@yahoo.com – May 2013
Finally SNA can used to prioritize Potential
Churners
4
Network Churn
Risk is calculated
according to the
Churn Score of the
people in the
Network of the
Customer
Disguised Example
Churn Risk
3.2% 5.4% 7.6% 21.6% 100%
HML
H
M
L
NetworkChurnRisk
22.2%
6.4%
2.7%
0.6%
0%
148 K
(8.8%)
60K
(3.5%)
63 K
(3.8%)
46 K
(2.7%)
20 K
(1.2%)
151 K
(9%)
59 K
(3.5%)
67 K
(4%)
45 K
(2.7%)
14 K
(0.9%)
131 K
(7.7%)
63 K
(3.7%)
79 K
(4.7%)
52 K
(3.1%)
13 K
(0.8%)
95 K
(5.6%)
64 K
(3.8%)
92 K
(5.5%)
57 K
(3.4%)
10 K
(0.6%)
41 K
(2.5%)
18 K
(1.1%)
38 K
(2.3%)
34 K
(2%)
225 K
(13%)
Network Churn Risk
1stPriority
2nd Priority
Customer Churn Risk
Benjamin Filaferro – filaferro@yahoo.com – May 2013
Give-Back Ratios of competitors should be tracked
precisely
5
Ooredoo is offering an
Earn/Burn ratio starting from
2.4% going to up to 8%, i.e.
through the program
Customers benefit from at
least the equivalent of a
2.4% discount rate on all their
spending
Tier
Blue Silver Gold
Max Min Max Min
Status points Earning Ratio (per 100 QR) 1 1 1
Status points Tier Eligibility (over 12 months) - 60 300
Nojoom Points Earning Ratio (per 1 QR) 1 1,5 2
Monthly Spending 499 500 2499 2500
Number of points cumulated in one month 499 750 3750 5000
2,4% 3,6% 3,6% 4,8% 0,024 Post-paid Rewards
Min
Point
Commercial
Value (QR)
2,5% 3,8% 3,8% 5,0% 0,025 Pre-paid Rewards
2,5% 3,8% 3,8% 5,0% 0,025 Partner Rewards
3,0% 4,5% 4,5% 6,0% 0,030 Post-paid Rewards
Max3,3% 5,0% 5,0% 6,6% 0,033 Pre-paid Rewards
4,0% 6,0% 6,0% 8,0% 0,040 Partner Rewards
Earn/Burn Ratio
Benjamin Filaferro – filaferro@yahoo.com – May 2013
Redemption Catalogues should be optimized to
guaranty Loyalty/Cost/Competition Efficiency
6
0,0%
1,0%
2,0%
3,0%
4,0%
5,0%
6,0%
7,0%
8,0%
0 5 10 15 20 25 30 35 40 45
Months needed for redemption
Give-back Ratio Benchmark
Competitor Mass Tier
Competitor Top Tier
Scenario #1 Mass Tier
Scenario #1 Silver Tier
Scenario #1 Gold Tier
Scenario #2 Mass Tier
Scenario #2 Silver Tier
Scenario #2 Gold Tier
Disguised Example
Optimization of the time needed to complete the smallest redemption
Optimization of tier effect and of the
point discount on big redemptions
Benjamin Filaferro – filaferro@yahoo.com – May 2013
Benjamin Filaferro – Independant Customer Strategy Advisor
I have been a Strategy Consultant for
the last 10 years at first for Banks and
then for Telecom Operators, and I have
specialized myself in Customer Strategy
over the last 6 years.
I have especially assisted Fixed and
Mobile Operator CMOs on the design
and the implementation of:
• Segment Strategies (ATL, BTL,
Touchpoint Experience, etc.)
• New products
• Retention Strategies (Loyalty
Programs, Winback, etc.)
In the specific field of Loyalty Programs,
my experience covers:
• The design, the implementation,
and the launch of 2 Point
Programs, 2 Affinity Programs, 1
Enterprise Affinity Program
• The supervision of an
outsourced team managing
from end-to-end (Marketing,
Communication, Analytics,
Logistics, & Partnerships) 2
Point Programs and 1 Prepaid
Stimulation Game
7Benjamin Filaferro – filaferro@yahoo.com – May 2013
Benjamin Filaferro – filaferro@yahoo.com – May 2013
Thank you

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Use SNA and Give-Back Ratios to Improve Loyalty Program Cost Effectiveness

  • 1. Use of SNA and Give-back Ratio Monitoring to Improve Cost Effectiveness of your Loyalty Program Benjamin Filaferro – filaferro@yahoo.com – May 2013
  • 2. important target of a Loyalty Scheme can be found through SNA 2 Disguised Example 34 (0.01%) 26 K (1.5%) 73 K (4.3%) 69 K (4.1%) 670 K (39.7%) 25 K (1.5%) 683 K (40.1%) 137 K (8.1%) 349 (0.02%) Out- Degree In- Degree Populars InfluencerExtravert 45 5 455 If an ordinary subscriber has an iPhone handset, on average 2.4 of its connections have iPhone as well. However this goes up to 8.7 if the owner is an influencer. If an ordinary subscriber has a Blackberry handset, on average 1.2 of its connections also have Blackberry as well. However this goes up to 5.3 if the owner is an influencer. Number of incoming links Number of outgoing links Benjamin Filaferro – filaferro@yahoo.com – May 2013
  • 3. customers and then adjust the Loyalty Program rules 3 Network Value of A = (1000) x (10%) + (200) x (50%) + (40) x (20%) + (100) x (15%) + (200) x (10%) = 100+100+8+15+20 = 243 10% C makes 50% of his total transactions to A Illustrative ARPU = 1000 B ARPU = 200 C Interconnection Revenues = 40 D ARPU = 100 E ARPU = 200 F A Disguised Example 3.4 K (0.2%) 21K (%1.2) 50 K (3%) 86 K (5.1%) 177 K (10%) 12 K (0.7%) 57 K (3.4%) 89 K (5.3%) 100 K (5.9%) 78 K (4.7%) 35 K (2.1%) 93 K (5.5%) 89 K (5.3%) 76 K (4.5%) 44 K (2.7%) 82 K (4.9%) 102 K (6.1%) 74 K (4.4%) 53 K (3.2%) 25 K (1.5%) 204 K (12 %) 64 K (3.8%) 35 K (2.1%) 22 K (1.3%) 12 K (0.7%) Network Value ARP 441 K (26.2%) 15.5 K (0.9%) 34 K (12.2%) Avg. Inc. Network Size: 31 Avg. Out. Network Size: 30 Avg. ARPU: 398 Avg. Network Value: 211 Call Dur. Out/Inc: 1.39 Avg. Inc. Network Size: 15 Avg. Out. Network Size: 9 Avg. ARPU: 10 Avg. Network Value: 89 Call Dur. Out/Inc: 0.53 Avg. Inc. Network Size: 0(0*) Avg. Outg. Network Size: 1(0) Avg. ARPU: QR 267 Avg. Network Value: QR 0 Call Dur. Out/Inc: 16.5 Benjamin Filaferro – filaferro@yahoo.com – May 2013
  • 4. Finally SNA can used to prioritize Potential Churners 4 Network Churn Risk is calculated according to the Churn Score of the people in the Network of the Customer Disguised Example Churn Risk 3.2% 5.4% 7.6% 21.6% 100% HML H M L NetworkChurnRisk 22.2% 6.4% 2.7% 0.6% 0% 148 K (8.8%) 60K (3.5%) 63 K (3.8%) 46 K (2.7%) 20 K (1.2%) 151 K (9%) 59 K (3.5%) 67 K (4%) 45 K (2.7%) 14 K (0.9%) 131 K (7.7%) 63 K (3.7%) 79 K (4.7%) 52 K (3.1%) 13 K (0.8%) 95 K (5.6%) 64 K (3.8%) 92 K (5.5%) 57 K (3.4%) 10 K (0.6%) 41 K (2.5%) 18 K (1.1%) 38 K (2.3%) 34 K (2%) 225 K (13%) Network Churn Risk 1stPriority 2nd Priority Customer Churn Risk Benjamin Filaferro – filaferro@yahoo.com – May 2013
  • 5. Give-Back Ratios of competitors should be tracked precisely 5 Ooredoo is offering an Earn/Burn ratio starting from 2.4% going to up to 8%, i.e. through the program Customers benefit from at least the equivalent of a 2.4% discount rate on all their spending Tier Blue Silver Gold Max Min Max Min Status points Earning Ratio (per 100 QR) 1 1 1 Status points Tier Eligibility (over 12 months) - 60 300 Nojoom Points Earning Ratio (per 1 QR) 1 1,5 2 Monthly Spending 499 500 2499 2500 Number of points cumulated in one month 499 750 3750 5000 2,4% 3,6% 3,6% 4,8% 0,024 Post-paid Rewards Min Point Commercial Value (QR) 2,5% 3,8% 3,8% 5,0% 0,025 Pre-paid Rewards 2,5% 3,8% 3,8% 5,0% 0,025 Partner Rewards 3,0% 4,5% 4,5% 6,0% 0,030 Post-paid Rewards Max3,3% 5,0% 5,0% 6,6% 0,033 Pre-paid Rewards 4,0% 6,0% 6,0% 8,0% 0,040 Partner Rewards Earn/Burn Ratio Benjamin Filaferro – filaferro@yahoo.com – May 2013
  • 6. Redemption Catalogues should be optimized to guaranty Loyalty/Cost/Competition Efficiency 6 0,0% 1,0% 2,0% 3,0% 4,0% 5,0% 6,0% 7,0% 8,0% 0 5 10 15 20 25 30 35 40 45 Months needed for redemption Give-back Ratio Benchmark Competitor Mass Tier Competitor Top Tier Scenario #1 Mass Tier Scenario #1 Silver Tier Scenario #1 Gold Tier Scenario #2 Mass Tier Scenario #2 Silver Tier Scenario #2 Gold Tier Disguised Example Optimization of the time needed to complete the smallest redemption Optimization of tier effect and of the point discount on big redemptions Benjamin Filaferro – filaferro@yahoo.com – May 2013
  • 7. Benjamin Filaferro – Independant Customer Strategy Advisor I have been a Strategy Consultant for the last 10 years at first for Banks and then for Telecom Operators, and I have specialized myself in Customer Strategy over the last 6 years. I have especially assisted Fixed and Mobile Operator CMOs on the design and the implementation of: • Segment Strategies (ATL, BTL, Touchpoint Experience, etc.) • New products • Retention Strategies (Loyalty Programs, Winback, etc.) In the specific field of Loyalty Programs, my experience covers: • The design, the implementation, and the launch of 2 Point Programs, 2 Affinity Programs, 1 Enterprise Affinity Program • The supervision of an outsourced team managing from end-to-end (Marketing, Communication, Analytics, Logistics, & Partnerships) 2 Point Programs and 1 Prepaid Stimulation Game 7Benjamin Filaferro – filaferro@yahoo.com – May 2013
  • 8. Benjamin Filaferro – filaferro@yahoo.com – May 2013 Thank you