1. Prospecting
A data-driven perspective

2. Data Strategy / Acquisition
• Customers, Sign-Ups, Others
• Consumer Compiled
• Vertical Lists and Data
Data Management
• Persistent ID Creation
• Data Hygiene
• NCOA, Advanced / Proprietary NCOA
• Data Enhancement, Model Scoring
• Merge-Purge, Advanced Segmentation
Program Execution
• Campaign Execution
• Direct Mail
• Email Delivery
• SMS/MMS Delivery
• Key Word / Banner Display Ads
Program Evaluation
• Response Analysis
• Creative Testing
2www.lscdigital.com29 January 2015
The Best Acquisition Strategy
Is a great retention program

3. 3www.lscdigital.com29 January 2015
Data
Do Your Homework

4. 4www.lscdigital.com29 January 2015
Know Your Customers
Survey Your
Customers
• Web
• Phone
• Bouncebacks
Utilize Your Vendors
• Brokers, Co-ops
• Card Decks
• FSI’s

5. 5www.lscdigital.com29 January 2015
Lifestyle Data & Appends
Correlate Attributes to Response
Informational /
Directional
Marketing
Database
Prospect
Database
Total Rentals 2,117,900
Total Responses 19,110
Response Rate 0.90%
Attributes Ranked from Best to Worst Circulation
Customer
Matches
% of
Circulation
Response
Rate
Variance Lift
Score 1-5 Apparel Senior Fashion 45,340 680 2.1% 1.50% 0.60% 66.22%
Score 1-5 Young & Hip 36,420 480 1.7% 1.32% 0.42% 46.06%
Score 6-10 Gifts 39,970 520 1.9% 1.30% 0.40% 44.18%
Age 55+ 534,600 6,810 25.2% 1.27% 0.37% 41.18%
Apparel 1-5 Gifts 14,220 180 0.7% 1.27% 0.37% 40.29%
Score 6-10 Apparel Senior Fashion 82,240 980 3.9% 1.19% 0.29% 32.07%
Score 11-15 Gifts 93,550 1,110 4.4% 1.19% 0.29% 31.50%
Score 6-10 Plus Sizes 117,170 1,370 5.5% 1.17% 0.27% 29.58%
Score 6-10 Young & Hip 76,830 870 3.6% 1.13% 0.23% 25.50%
Score 11-15 Plus Size 195,250 2,130 9.2% 1.09% 0.19% 20.90%
Score 6-10 Women's Apparel 201,340 2,190 9.5% 1.09% 0.19% 20.55%
Score 1-5 Women's Apparel 179,240 1,920 8.5% 1.07% 0.17% 18.72%
Score 16-20 Plus Size 554,380 5,900 26.2% 1.06% 0.16% 17.95%
Score 11-15 Young & Hip 144,001 1,490 6.8% 1.03% 0.13% 14.67%
Score 1-5 Apparel Senior Fashion 670,660 6,820 31.7% 1.02% 0.12% 12.70%
Age 55-64 259,150 2,580 12.2% 1.00% 0.10% 10.33%
Score 1-5 Plus Size 86,520 850 4.1% 0.98% 0.08% 8.88%
Score 16-20 Plus Size 346,470 3,270 16.4% 0.94% 0.04% 4.60%
Unknown Age 148,260 1,380 7.0% 0.93% 0.03% 3.16%
Female 1,800,340 16,730 85.0% 0.93% 0.03% 2.99%
Score 21 Young & Hip 1,072,670 9,070 50.6% 0.85% -0.05% -6.81%
Unknown Gender 140,370 1,120 6.6% 0.80% -0.10% -11.57%
Score 21 Women's Apparel 675,860 5,310 31.9% 0.79% -0.11% -12.93%
Score 21 Gifts 997,490 7,690 47.1% 0.77% -0.13% -14.56%
Male 177,190 1,260 8.4% 0.71% -0.19% -21.19%
Score 21 Senior Fashion 698,670 4,830 33.0% 0.69% -0.21% 23.38%
Age 18-34 17,770 110 0.8% 0.62% -0.28% 31.40%
Age 45-54 124,040 750 5.9% 0.60% -0.30% 32.99%
Age 35-44 50,210 290 2.4% 0.58% -0.32% 35.99%

6. List Selections and Overlays
“Case Study #1”
Demographic overlays boosted response
by 22% (including co-op names)
Hotlines
“Cast Study # 3”
Reactivation on 24+ month Internet
buyers brought response on par
with non-modeled 13-16 month
buyers
House Leads
“Case Study #2”
Using outside recency selection on older
3-12 month buyer segments increased
sales 26%
Older Leads /
Rollouts
6www.lscdigital.com29 January 2015
Optimize list selections, Don’t be afraid to ask for deals
and information, try augmented exchanges
Better Targeting

7. Models for Best Results
Both Analysis and Validation Samples would be composed of a Target and Comparative Universe.
New Leads
Modeled Samples
(n =30,000)
New Leads
Random Sample
(n = 50,000)
10%/90%
Ratio
Model
Development
(Test)
16,900
Model
Validation
16,900
Model
Development
(Test)
700
Model
Validation
700
7www.lscdigital.com29 January 2015
Know when to fire a prospect, control all media, track
sources and track costs

8. Customer Preference Rules
Model Cum # Cum % # Target %Target %
Group Sample Sample Universe Universe Gain
1 910 5% 263 28.9% 627
2 1,798 10% 389 21.6% 444
3 2,648 15% 479 18.1% 355
4 3,477 20% 520 15.0% 276
5 4,369 25% 551 12.6% 217
6 5,256 30% 574 10.9% 175
7 6,112 35% 597 9.8% 146
8 7,068 40% 611 8.6% 117
9 7,975 45% 625 7.8% 97
10 8,780 50% 640 7.3% 83
11 9,540 54% 648 6.8% 71
12 10,462 59% 658 6.3% 58
13 11,384 65% 668 5.9% 48
14 12,276 70% 679 5.5% 39
15 12,977 74% 682 5.3% 32
16 14,061 80% 692 4.9% 24
17 14,982 85% 697 4.7% 17
18 15,827 90% 699 4.4% 11
19,20 17,600 100% 700 4.0% 0
Mail & Email
Email Only
Test Only
8www.lscdigital.com29 January 2015
Set campaign metrics that select customers based on
their profitability channel preference

9. Geo-Targeting
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Analysis
• Find Trends by County
Action
• Filter & Select
Result
• 5 % Reduction in Circulation
• 9% Increase in Revenue

10. Creative + Promotion
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• Offers
• Variable
Content
• Testing
• Segmentation &
Tracking
• Multi-Channel
Delivery
Message – Timing - Channel

11. Creative + Promotion
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Timing
• Days & Day-Parts
Frequency
• Content Delivery
• Offer Delivery
Message – Timing - Channel

12. Matchbacks
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Directed Results
• You get what you asked for
• Consider order curves and
other influences
Controls and
Treatments
• Evaluate Lift
The Challenges of Matchbacks

13. Matchbacks
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Channel Conflict & Synergy
“Marketing drives 130% of demand”

14. Lifetime Value
14www.lscdigital.com29 January 2015
Beyond
$/Book
Beyond
Keycode
LTV
• By List
• By Channel
• By Margin
What does it really cost to acquire
a customer?

15. Benefits of a Marketing
Database
15www.lscdigital.com29 January 2015
If you don’t operate the database
properly you just might:
• Miss Your Projections
• Make Improper Decisions
• Generate Bad / Inaccurate Reporting
• Miss Important Timing Trends
THANK YOU!