case studyBanking & Finance

Credit Card Cross-Sell

Business ChallengeA major regional financial services company conducted an enterprise-wide CRM analysis, which showed that its current credit card penetration within the bank customer base was less than 10%— significantly below the industry average. Merkle was asked to lead the charge to develop a strategic solution to cross-sell credit cards to the existing retail bank customer base.

ApproachGuided by a shared vision for growth, Merkle constructed a strategic roadmap to determine the key steps for creating a comprehensive cross-sell program. Short-term and long-term acquisition plans clearly articulated the strategic theme for each step, from audience selection to targeting, messaging to offer tailoring, and pricing to media and channel optimization. The ultimate business goal was to deepen portfolio penetration while optimizing risk and revenue trade-offs.

Goa

lsSt

rate

gic

Them

e

Audience & Modeling

Targeting & Optimization

Channel & Frequency

Measurement & Reporting

Creative, Offer & Message

Acquire Accounts Manage Risk Increase Profitability

Init

iati

ves

Identify profit potential model for non-card households

Build product-specific response models for consumer & small business post random campaign mailing

Build segmentation tool to identify likely transactor & revolver for consumers & small business

Build ITA models based on insights from original prescreen solutions

Measure the impact of profit & segmentation models

Measure impact of product offer, frequency, cadence & key profit driver tests (incentives, creative, etc.)

Build baseline performance for transactor & revolver segment offers

High-level monthly reporting focused on the following:- Applications- Accounts- CPIA, CPIHQuarterly deep dive

Random mailing across consumer & small business to support building product response models

Validate TRIP segment with random mailing account performance

Test media & channel mix by segment

Test impact on performance during typical holiday periods

Test frequency & cadence by segment

Use PURLs to deliver offer-driven landing pages that motivate response & capture customer behavioral data

Customer-centric, highly offer-driven communications by segment

Bonus points are the primary offer for currently enrolled customers

Test offers by marketing segment:- Revolver- Transactor- Student - Small business

Sample Credit Card Cross-Sell Strategy Map

Merkle, a customer relationship marketing (CRM) firm, is the nation’s largest privately-held agency. For more than 20 years, Fortune 1000 companies and leading nonprofit organizations have partnered with Merkle to maximize the value of their customer portfolios. By combining a complete range of marketing, technical, analytical and creative disciplines, Merkle works with clients to design, execute and evaluate connected CRM programs. With more than 1,700 employees, Merkle is headquartered near Baltimore in Columbia, Maryland with additional offices in Boston; Denver; Little Rock; Minneapolis; New York; Philadelphia; Pittsburgh; San Francisco; Hagerstown, MD and Shanghai. For more information, contact Merkle at 1-877-9-Merkle or visit www.merkleinc.com.

Will BordelonSr. Vice President & GM, Banking & Finance 443.542.4009wbordelon@merkleinc.com

Today, many credit issuers adopt a standard payments behavior segmentation framework, splitting cardholders into four key categories: transactor, revolver, inactive and paydown (also known as TRIP). However, the industry has stopped short with this internal, one-sided, behavior approach. Merkle has developed a total payments framework to not only evaluate internal “on-bank” TRIP behavior, but also predict external “off-bank” TRIP behavior. Such an approach is critical for tailoring offers and messaging to meet the right customer needs.

After initial in-market testing, net booking models can be built to optimize future campaign targeting and communications strategies.

Pha

se 1

Pha

se 2

Existing credit card portfolio

diagnostics

Mail random test campaign

Identify key retail-bank attributes

Modeling:Predict

transactor & revolver accounts

Profile on TRIP & value segmentation

Campaign Performance:

Collect response data

Predictive Modeling:

Profit & TRIP behavior model

Integration Campaign Solutions:Efficiently targeting high-profit

cross-sell households with a credit card that enables predicted card behavior

Balance Targeting:Profitable

revolvers & Transactors

In order to acquire the most desirable prospects, Merkle developed an advanced statistical modeling solution to predict prospects’ profit potential. The model is based on a combination of various customer attributes, such as retail bank product ownership, transactional behavior, risk profile from the credit bureau, industry-wide segmentation, demographic data and other third-party consumer intelligence, such as Merkle’s wealth index and estimated home value.

Merkle also built a linear regression model to predict potential credit card profit. The outcome will facilitate prioritization for campaign selection. However, selecting the right target was only half the solution. In addition to the profit model solution, Merkle also developed a transactional behavior determination based on a multinomial segmentation model to predict a prospect’s payments pattern.

OutcomeMerkle’s predictive models enabled the bank to target the most valuable prospects and extend the most relevant offers. With the right combination of their internal financial and behavioral data, credit bureau and market-wide customer intelligence, the predictive model solution scored a significant lift in identifying potential prospects who are more likely to be higher profitability accounts.

Model Performance: Actual Versus Predicted

Modeling Sample

Expe

cted

Pro

fit

$80300

220

173

129

8255

3517

4 -15

320

$60 240

$40 150

$20 80

$0 0

$20 -80Actual Predicted Index

1 3 5 7 92 4 6 8 10

Lift

Inde

x