Finding new prospects and customers in the market for business credit has never been more difficult. Even with hyper-personalized and targeted campaigns, marketing response rates can still be stagnant. During this webinar you will learn how to: Get the right message to the right prospect using data beyond traditional marketing firmographics Use analytics to optimize marketing spend Prioritize your outreach by identifying who is likely in the market to buy Watch the recording of this webinar: https://www.experian.com/business-information/webinar-sip-and-solve-ep-16-3-tips-to-increase-response-rates

1. 1 © Experian
Sip and Solve
3 tips to increase response rates
when marketing to businesses
Featuring:
Dan Meder
Vice President, Solutions Consulting
Experian Business Information Services

2. 2 © Experian
In today’s session, you will learn…
• There is data beyond traditional marketing firmographics that will help get the
right message to the right prospect at the right time.
• How analytics are key to finding the segments that will optimize your
marketing spend.
• You can identify who is likely to be in the market which can drive how you
effectively prioritize outreach.

3. 3 © Experian
Trends and challenges
Small businesses are saturated daily with offers!
• Multi-channel environments; media fragmentation
• Heavy competition for small business owner’s “share of wallet”
• Marketing to small businesses rising; targeting at a
“maturation” point
• Personalization technologies have arrived: now what?
• Need more targeted approaches?
As businesses become increasingly customer-centric, an understanding of the small business owner’s attitudes and
preferences become a necessity for delivering on the promise of “communications effectiveness”.

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Customized loyalty campaigns work!
“[Small businesses] also expect banks
to not only have the capability to tailor
their credit solutions specifically for the
small business industry, but also offer
customized solutions for specific
business situations.”
- ABA Journal, October 2018
Emails targeted to customer loyalty programs
have a 40% higher open rate
General Contact
List
Loyalty ProgramOpens

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Keys to a successful marketing program
Email and Social Mobile Household TV OnlineDirect mail
Audience Identification
Profile & Segmentation
Identifying and profiling your
best customers.
Targeting
Data Mining & Modeling
Finding similar people &
growing their value.
Messaging
Contact Strategy
Engaging effectively across preferred
channels with tailored offers.

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The power is in…
Robust reference file
Experian’s commercial database
Increase wallet share/loyalty
Enhanced matching gives you the ability to target your
customer segments at their business and/or home address
Business firmographics
Attributes such as annual sales,
number of employees, and industry
code
Enhance segmentation
Gain insight into the associated
business for additional targeting,
segmentation, and analytics
Credit attributes
Commercial credit attributes including
credit risk score, delinquency metrics,
high credit, and balance
Maximize profitability
Target desirable accounts based on credit activity,
utilization and risk
The Result
1 2
3 4

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Profiling: Process Flow
Data preparation
and audit review files
received from client or
select criteria based population
from Experian database
1
Data append
Experian matches to databases
and appends Experian credit
and firmographic information
2
Data analysis
Decision Sciences performs
analytics using customer and
Experian data
3
Executive summary
and report presentation
4

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Profiling: Identify “look-a-like” prospects
Once a customer profile is determined, criteria can be applied to other prospect lists to identify
businesses with a similar profile.
Number of
trades
> 3
Employees 10 - 100
Years on file > 2
Risk Score > 50
90+ day
delinquencies
None in last
12 months
Apply criteria to
new prospect list
Find “look-alikes”Example Profile

9. 9 © Experian
Custom Response Modeling
Identify “look-a-like” prospects
Based on your prior campaigns, a custom model can be built to predict the likelihood of prospects to respond:
Campaign Data
Offer / Channel
Times Mailed
Commercial Credit
Trades
Balances
High Balance
Inquiries
Derogatory Items
Collections
Liens
Judgments
Firmographics
Time on File
Employee Size
SIC
SIC
Years in Business
Total number of trades with 1-30
DBT
Balance to Limit ratio (utilization)
Number of Inquiries
Input Attributes
Sample Predictive Attributes

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Balancing Campaign Response & Approval
Create a matrix of scores to balance response and acquisition
Percentage of scored
population shown 1-19 20-39 40-59 60-79 80-100
1-19 0.8% 3.1% 6.0% 7.7% 6.4%
20-39 1.1% 3.8% 6.2% 5.9% 3.3%
40-59 1.8% 4.2% 5.4% 4.4% 2.2%
60-79 3.2% 4.9% 5.3% 3.5% 1.7%
80-100 5.0% 5.4% 4.9% 3.0% 1.0%
Likelihood to Approve
LikelihoodtoRespond

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Business Lifecycle Signals
Every business activity creates a signal
• News alerts
• Online activity
• Phone traffic
• Claim listings
• Directories
• Data science
Planning Open Doors
• Register business
• Register domain
• Phone connects
• License/permits
Stable
• Online activity
• Phone activity
• License renewals
• Claim listings
• URL traffic
• Directories
Closed
• Online activity
• Phone activity
• News alerts
• Data science
• Email activity
• User reported

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Intent Data Overview
Source Data Intent Algorithm
(Maximum relevance of offer
& messaging)
Optimize Channel
Response
Content
Download
Social
Media
Activity
Webpage
Visits
Blog
Consumption
Keyword
Searches
Webinar
Registrations

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Case Study
Financial services lender with retail partner - prospect prioritization
Solution: Experian’s custom analytics team worked closely with the financial
services’ marketing and risk teams to analyze and profile their most profitable and
loyal customers. Using the profile attribution and leveraging consumer to business
linkage, we identified four million small business owners who are existing consumer
card holders to intelligently target for an ITA campaign.
• Lookalike / Profile Model
• C2B Linkage
• Firmographic and Risk Attribute Appends
Results: To maximize campaign cost against funding & response rates, the client
split targeting into groups.
• Primary Targets – Targeting the 1M within their most profitable and loyal bands
with diverse engagement across pricey channels like direct mail & in-store direct
sales as well as more inexpensive digital options. Also, will target loyalty drivers
given these are existing consumer card holders and meet profitability thresholds.
• Secondary Targets – Remaining population, marketing through less expensive
channels; email, in-store shopping take-rates, statement offers
Objective: To increase the number of small business cardholders
and to drive loyalty with the associated retail partner
Primary targets
(1 million)
Secondary targets
(remaining
population)
Direct mail
Email
Instore
direct sales
In-store
shopping
take rates
Statement
offers
Inexpensive
digital
options
Targeting Channels

14. 14 © Experian
Thank you!
Have questions or want to learn more about how to increase marketing
response rates?
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