sample customer clusters q5 division, llc 1. overview used to describe the work that q5 division,...

Sample Customer ClustersQ5 Division, LLC

1

Overview

• Used to describe the work that Q5 Division, LLC did for the client and what will be discussed in the cluster report.

2

Overall Cluster Distributions and PenetrationCustomers

18%

214%

38%

48%

57%

68%

79%

812%

910%

108%

118%

Prospects 1

5% 213%

321%

411%

55%

616%

72%

85%

98%

105%

119%

3

Penetration

1

2

3

4

5

6

7

8

9

10

11

-80 -55 -30 -5 20 45 70 95 120 145 170 195 220 245 270 295 320

• The Customer Clusters divide the current customers into relatively uniform size segments of people.

• The prospects within the areas where the stores are located are not quite as uniform with significantly less people in clusters 7, 8 and 10 and more people in 3,4,and 6.

• This difference in distribution allows us to see how well example 1 is penetrating the population for each cluster.

• Example 1 is penetrating cluster 7 significantly more than any other cluster. This signifies that example 1 has a very strong appeal to individuals in this cluster.

• There is also a high penetration in clusters 8,10,5 and 1, but to a lesser degree.

• At this time, Sample appears to have challenges attracting people in clusters 3, 4 and 6.

• Example 1 is attracting only it’s fair share of all of the other clusters (2, 9 and 11).

Value Distribution Across Clusters1. Cluster 5 is made up individuals with the

highest customer value for people with Activity A only and the second highest Activity A and Activity B combined activity.

2. Cluster 3 is made up individuals with the highest customer value for people with Activity B only and the first highest Activity A and Activity B combined activity.

3. Clusters 8 and 10 are made up individuals with the lowest customer value for people with Activity A only and Activity A and Activity B combined activity.

4. Clusters 2 and 10 are made up of individuals with the lowest customer value for people with Activity B only.

4

1

12

3

3

42

FileMatch Cluster

Customers% of

Customers

Act A & Act B Combined Total Value

(M)

% of Act A & Act B Combined

Value

Act. A & Act. BCombined

Average Value

1 64,962 3.94% $9 2.37% $1392 112,216 6.81% $17 4.36% $1483 71,334 4.33% $16 4.19% $2234 74,235 4.50% $15 4.04% $2075 59,412 3.60% $15 3.85% $2476 67,580 4.10% $13 3.30% $1867 61,917 3.76% $13 3.34% $2058 93,906 5.70% $10 2.52% $1029 79,871 4.85% $14 3.63% $17310 93,010 5.64% $10 2.52% $10311 72,907 4.42% $13 3.48% $182

851,350 51.66% $143 37.59% $1681 24,403 1.48% $2 0.61% $962 60,453 3.67% $5 1.32% $833 42,894 2.60% $7 1.88% $1674 46,180 2.80% $6 1.56% $1285 45,563 2.76% $5 1.42% $1196 39,621 2.40% $5 1.19% $1157 39,024 2.37% $4 1.14% $1118 49,910 3.03% $5 1.25% $959 35,363 2.15% $4 1.12% $12110 42,761 2.59% $3 0.86% $7611 49,871 3.03% $6 1.50% $115

476,043 28.88% $53 13.86% $1111 25,567 1.55% $13 3.48% $5182 41,381 2.51% $21 5.49% $5053 22,078 1.34% $19 4.91% $8454 26,194 1.59% $18 4.81% $6995 23,449 1.42% $19 4.94% $8016 23,299 1.41% $14 3.59% $5867 26,275 1.59% $18 4.68% $6788 39,111 2.37% $14 3.79% $3689 29,630 1.80% $18 4.71% $60510 38,787 2.35% $15 3.95% $38711 24,968 1.51% $16 4.22% $644

320,739 19.46% $185 48.56% $5761,648,132 100.00% $381 100.00% $231

c. Pawn and Retail TotalGrand Total

a. Activity A Only

a. Pawn Only Total

b. Activity B Only

b. Retail Only Total

c. Act. A & Act. B

Cluster Prioritization Summary

5

Cluster PenetrationAct. A Only

Act. B Only

Act. A and Act. B

Combined Priority Comments/ Assessment Highest Priority Models

1 46 $139 $96 $518 LowCluster 1 could become a concern because they are attracted to Example 1, but they are below average value customers in all categories. If you want to market to these, we should leverage the value predictive models for customer and prospect campaigns to identify the highest potential prospects within this group.

Customer Act. A Value, Customer Act. B Value

2 10 $148 $83 $505 LowCluster 2 could become a concern because Example 1 is bringing in their fair share of this cluster, but they are below average value customers in all categories. If you want to market to these, we should leverage the value predictive models for customer and prospect campaigns to identify the highest potential prospects within this group.

Customer Act. A Value, Customer Act. B Value

3 -64 $223 $167 $845 HighCluster 3 has great potential, but Example 1 does not appear to be attracting as many of these individuals as we would want to. If you want to market to these, we should leverage Example 1 customer clone predictive models for customer and prospect campaigns to identify the highest potential prospects within this group

Act. A Customer Clone, Act. B Customer Clone,

Act. A and Act. BCustomer Clone

4 -30 $207 $128 $699 HighCluster 4 has great potential, but Example 1 does not appear to be attracting as many of these individuals as we would want to. If you want to market to these, we should leverage Example 1 customer clone predictive models for customer and prospect campaigns to identify the highest potential prospects within this group.

Act. A Customer Clone, Act. B Customer Clone,

Act A & Act BCustomer Clone

5 50 $247 $119 $801 HighCluster 5 has a strong value with a higher than average appeal. It seems to be a good candidate for the creation of programs that will attract individuals from the prospect universe that look like them.

All should be tested

6 -49 $186 $115 $586 MediumCluster 6 is a very average performer. If we are to market to this cluster, we should leverage the customer clone and

the value predictive models for targeting.All are needed

7 307 $205 $111 $678 Very HighCluster 7 has a strong value and has such a high appeal that it seems to be a good candidate for the creation of programs that will attract individuals from the prospect universe that look like them.

All should be tested

8 116 $102 $95 $368 Very Low

Cluster 8 is a concern because they are highly attracted to Example 1, but they are low value customers in all categories. Finding a way of suppressing these from future campaigns may be a strategy to reduce low value foot traffic in the stores. If you want to market to these, we should leverage the value predictive models for customer and prospect campaigns to identify the highest potential prospects within this group

Customer Act. A Value, Customer Act B. Value

9 23 $173 $121 $605 MediumCluster 9 is a very average performer. If we are to market to this cluster, we should leverage the customer clone and


10 80 $103 $76 $387 Very Low

Cluster 10 is a concern because they are highly attracted to Example 1, but they are low value customers in all categories. Finding a way of suppressing these from future campaigns may be a strategy to reduce low value foot traffic in the stores. If you want to market to these, we should leverage the value predictive models for customer and prospect campaigns to identify the highest potential prospects within this group.

Customer Act. A Value, Customer Value

11 -13 $182 $115 $644 MediumCluster 11 is a very average performer. If we are to market to this cluster, we should leverage the customer clone and


Descriptive Statistics

DescriptionOverall Average

Cluster Average

% Female 48.19% 91.16%Individual Age 45.12 47.40

HH Income $45k $24kHH Net Worth $151k $92k

% w Net Worth lt $25k 40.53% 80.15%Marital Status -Single 57.00% 80.15%

# of Adults in HH 2.06 1.47Presence of Children 47.67% 3.27%

Credit Active 19.95% 10.34%# of Credit Cards - One 15.48% 8.56%

Est. Cnsmr low Prft Mrgn 9.97% 16.59%Eth - Hispanic 21.80% 7.94%

Eth - African American 18.51% 22.44%Religion - Protestant 64.66% 77.08%

Religion - Catholic 31.11% 18.19%State - Florida 9.33% 9.09%

State - Ohio 7.61% 9.47%State - Tennessee 6.90% 2.28%

State - Texas 27.48% 28.48%

Activity A Transactions


Cluster Average

# of Shops Visited 1.41 1.39# of Visits 9.32 9.93

Customer Value $253 $250% Cmra, Bnclr, Tlscp Actv 6.16% 6.58%

% Electronics Actv 38.73% 43.76%% Firearms Actv 3.31% 1.94%

% Home Equipment Actv 4.35% 4.80%% Jewelry Actv 37.77% 43.30%

% Miscellaneous Actv 3.35% 3.47%% Music Inst Actv 5.48% 4.51%

% Sporting Goods Actv 4.76% 3.99%% Tools Actv 14.64% 11.12%

6

Activity B Transactions


Cluster Average






Who is in Cluster 1?

• They are low income single females. They represent 7.7% of the customers and 5 % of prospects.

• They make a very low income but are doing what they can to build a nest egg.

• They don’t tend to be very active as it relates to credit card usage.

• They are a bit more likely than average to do X than Y if they are Activity A customers.

• If they are Activity B customers, they are less likely than average to do X.

Strategic Assessment:

• Example 1 is attracting these individuals at a higher rate than average, but they are generally not high value customers for Activity A or Activity B.

• We need to be very strategic and targeted in the way we communicate and market to them.

Activity A Vs. Activity B

Cluster 1



Cluster Average










State - Texas 27.48% 11.05%


7



Cluster Average







• They are big families that are very responsive to mail. They represent 14% of the customers and 13% of prospects.

• They have a lot of credit activity in the way of credit card usage.

• They are more than likely living in Ohio and Tennessee.

• They are participating in Activity A and buying everything at a rate that is very proportionate to the averages for the customer base.


• Example 1 is attracting these individuals at a slightly higher rate than average, but they are generally not high value customers for Activity A or Activity B.

• This group could become a money pit if we are not incredibly strategic and targeted in the way we communicate and market to them.


Cluster 2


Cluster Average









Cluster Average










State - Texas 27.48% 36.30%



Cluster Average







8



Cluster Average







• Cluster 3 are couples with adult children living at home. They tend to be early adopters and have incomes that are significantly higher than their peers. They represent 7.8% of the customers and 21% of prospects.


• They are more than likely living in Texas.

• They are more likely than average to be participating in Activity A and buying firearms and musical instruments.

Strategic Assessment

• Example 1 is attracting these individuals at a rate that is significantly lower than average, but they are generally very high value customers for Activity A or Activity B.

• This group has tremendous potential but the prospect pool is so large that it is critical to leverage Example 1 customer clone models and Activity B customer clone models to target the people with the highest likelihood to be interested in becoming an Example 1 customer.


Cluster 3



Cluster Average










State - Texas 27.48% 25.19%



Cluster Average







9



Cluster Average







• They are older couples that are very traditional and tend to be offline. They have built up a positive nest egg on a very moderate income. They represent 7.8% of the customers and 11% of prospects.


• They are more than likely to be living in Tennessee.

• They are more likely than average to be participating in Activity A and buying firearms and musical instruments.


• Example 1 is attracting these individuals at a rate that is significantly lower than average, but they are generally very high value customers for Activity A and Activity B.

• This group has tremendous potential but the prospect pool is so large that it is critical to leverage Example 1 customer clone models and Activity B customer clone models to target the people with the highest likelihood to be interested in becoming a Example 1 customer.


Cluster 4



Cluster Average








Religion - Catholic 31.11% 100%State - Florida 9.33% 3.35%


State - Texas 27.48% 65.32%



Cluster Average







10



Cluster Average







• They are large Hispanic Catholic families with a significant amount of debt.

• They live in small homes and have lived where they are for many years.

• They make up 7.3% of the customers and 5% of prospects.


• They are more than likely to be living in Texas.

• They are more likely than average to be participating in Activity A and buying everything.


• Example 1 is attracting these individuals at a rate that is significantly higher than average and they are generally very high value customers for Activity A and Activity B.

• This group has tremendous potential. It represents one of two high priority clusters. Although it is recommended that we test targeting models for this cluster, creating programs for this group as a whole should be relatively low risk.


Cluster 5



Cluster Average










State - Texas 27.48% 26.75%



Cluster Average







11



Cluster Average







• These are senior singles that are very conservative.

• They opt for debit cards with rewards programs over credit cards.


• They are more likely than average to be participating in Activity A.

• They are more likely than average to be buying firearms, musical instruments, sporting goods and tools.


• Example 1 is attracting these individuals at a rate that is a bit lower than average and they are average value customers for Activity A and Activity B.

• This group has potential if we are very targeted with who we market to and what we market to them. It is a cluster that has the greatest need for predictive models for targeting profitably and success-ability.


Cluster 6



Cluster Average










State - Texas 27.48% 55.56%



Cluster Average







12



Cluster Average







• They are young Hispanic individuals making a modest income.


• They have less than average credit activity and credit card usage.

• They are more than likely to be living in Texas.

• They are more likely than average to be pawning jewelry, cameras, binoculars and telescopes and buying everything but firearms.


• Example 1 is attracting these individuals at a rate that is significantly higher than average and they are generally very good value customers for Activity A and Activity B.

• This group has tremendous potential. It represents one of two high priority clusters. Although it is recommended that we test targeting models for this cluster, creating programs for this group as a whole should be relatively low risk.


Cluster 7



Cluster Average










State - Texas 27.48% 17.21%



Cluster Average







13



Cluster Average







• These are high mobility, tech savvy, single males. They represent 11.8% of the customers and 5 % of prospects.

• They are making a very modest income, have contributed very little to savings thus far, and have little to no credit activity.

• They are living everywhere but are less likely than average to be living in Texas.

• They are participating in Activity A and Activity B.


• Example 1 is attracting these individuals at a higher rate than average, but they are generally very low value customers for Activity A and Activity B.


• We should consider suppressing this group from programs until we are ready to test in a targeted manner to potentially reduce the volume of low value traffi.


Cluster 8



Cluster Average










State - Texas 27.48% 13.24%



Cluster Average







14



Cluster Average







• These are middle aged single women making modest incomes.

• They are likely to be living in suburbia.

• They have lower than average credit activity.


• They are more likely than average to be participating in Activity A, everything but firearms, musical instruments, sporting goods or tools.

• They are more likely than average to be buying jewelry.


• Example 1 is attracting these individuals at a rate that is a bit higher than average and they are average value customers for pawn and retail.

• This group has potential if we are very targeted with who we market to and what we market to them. It is a cluster that has the greatest need for predictive models for targeting profitably and successfully.• The fact that they are buying jewelry and they are single

women infers a high potential marketing campaign to this group for jewelry sales:

• They are probably buying it for themselves

• They probably can’t afford to pay full retail based on their income

• They probably don’t have someone to buy it for them


Cluster 9



Cluster Average










State - Texas 27.48% 28.10%



Cluster Average







15



Cluster Average







• These are the youngest people on the customer base. They are couples with kids and single moms barely making ends meet and just getting by day to day. They represent 8.3% of the customers and 5% of prospects.

• They are making a very low income, have contributed very little to savings thus far, and have lower than average credit activity.

• They are living everywhere but are more likely than average to be living in Ohio.

• They are most likely participating in Activity A and buying electronics.


• Example 1 is attracting these individuals at a higher rate than average, but they are generally very low value customers for Activity A Vs. Activity B.


• We should consider suppressing this group from programs until we are ready to test in a targeted manner to potentially reduce the volume of low value traffic in the stores.


Cluster 10



Cluster Average










State - Texas 27.48% 14.01%



Cluster Average







16



Cluster Average







• These are families with children living in suburbia.

• They make an income that is 50% more than the average household and have a net worth that is 49% higher than average.

• They have much higher than average credit activity.

• They make up 8.2% of the customers and 9% of prospects

• They are more likely than average to be buying everything but jewelry.


• Example 1 is attracting these individuals at a rate that is a bit lower than average and they are average value customers for Activity A and Activity B.

• This group has potential if we are very targeted with who we market to and what we market to them. It is a cluster that has the greatest need for predictive models for targeting profitably and successfully.


Cluster 11

Initial Marketing Strategy Matrix

Cluster Singles Wealthier Kids GenderCredit Usage Hispanic Age Hi Tech

1 Yes No No Female No23 Yes Yes Yes Yes4 Yes Yes Older No5 Yes Yes6 Yes No Male Oldest No7 Yes No Female Yes Young8 Yes No No Male No Young Yes9 Yes No Female No

10 No Yes Young Yes11 Yes Yes Yes

This matrix can be used when creating marketing programs. For example, if you want to create a program that would increase email capture or move people to an online channel you would start with clusters 3, 8, 10 and 11 because they tend to be more hi tech oriented.

If you want to create a program to Hispanic individuals, you would use clusters 5 and 7.

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Next Steps

• Finish up POC model(s) for one cluster to determine the value of modeling by cluster.

• Finish up the example 1 cluster analysis.

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19

Thank you

sample customer clusters q5 division, llc 1. overview used to describe the work that q5 division,...

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activity b combined

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b onlyact

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