LSC Digital Prospecting

Prospecting A data-driven perspective

April 10, 2023 www.lscdigital.com 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

The Best Acquisition StrategyIs a great retention program


DataDo Your Homework


Know Your Customers

Survey Your Customers

• Web• Phone• Bouncebacks

Utilize Your Vendors• Brokers, Co-ops• Card Decks• FSI’s


Lifestyle Data & AppendsCorrelate 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%


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

Optimize list selections, Don’t be afraid to ask for deals and information, try augmented exchanges

Better Targeting


Models for Best Results

Both Analysis and Validation Samples would be composed of a Target and Comparative Universe.

New LeadsModeled Samples

(n =30,000)

New LeadsModeled Samples

(n =30,000)

New LeadsRandom Sample

(n = 50,000)

New LeadsRandom Sample

(n = 50,000)

10%/90%Ratio

10%/90%Ratio

ModelDevelopment

(Test)16,900

ModelValidation

16,900

ModelDevelopment

(Test)700

ModelValidation

700

Know when to fire a prospect, control all media, track sources and track costs


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

Set campaign metrics that select customers based on their profitability channel preference


Geo-Targeting

Analysis• Find Trends by County

Action • Filter & Select

Result • 5 % Reduction in Circulation• 9% Increase in Revenue


Creative + Promotion

• Offers• Variable

Content• Testing• Segmentation &

Tracking• Multi-Channel

Delivery

Message – Timing - Channel


Creative + Promotion

Timing• Days & Day-Parts

Frequency• Content Delivery• Offer Delivery

Message – Timing - Channel


Matchbacks

Directed Results• You get what you asked for• Consider order curves and

other influences

Controls and Treatments

• Evaluate Lift

The Challenges of Matchbacks


MatchbacksChannel Conflict & Synergy

“Marketing drives 130% of demand”


Lifetime Value

Beyond $/Book

BeyondKeycode

LTV• By List• By Channel• By Margin

What does it really cost to acquire a customer?


Benefits of a Marketing Database

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!

LSC Digital Prospecting

Business

Transcript of LSC Digital Prospecting