Ata 2010 Steve Brubaker Data Analytics

Intelligent InteractionsIntelligent Interactions

Improve Response Rates by Getting to Know Your Improve Response Rates by Getting to Know Your Customers Through Data AnalyticsCustomers Through Data Analytics

Steve BrubakerSteve BrubakerChief of StaffChief of Staff

InfoCision Management Corp.InfoCision Management Corp.

www.infocision.comwww.infocision.com

Agenda

•The impact of modeling on acquisition

•Using business intelligence to drive results

•Online lead generation

•Multi channel marketing using business intelligence

Top trends in the contact center Top trends in the contact center industryindustry

10. Cell phones – erosion of landlines 10. Cell phones – erosion of landlines

9. Trend back to the phone call – technology is 9. Trend back to the phone call – technology is driving down call center costs while paper and driving down call center costs while paper and postal costs are increasing direct mail costs. postal costs are increasing direct mail costs.

8. VOIP – Voice Over Internet Protocol 8. VOIP – Voice Over Internet Protocol


7. Salaried contact center agents 7. Salaried contact center agents

6. Highly/Specially trained agents with ability to 6. Highly/Specially trained agents with ability to free flow conversations and not always work off a free flow conversations and not always work off a script script

5. Skill based inbound customer service – impacts 5. Skill based inbound customer service – impacts up-selling and cross-selling. Inbound doesn’t make up-selling and cross-selling. Inbound doesn’t make $. By up-selling and cross-selling you can make $.$. By up-selling and cross-selling you can make $.


4. Social Media monitoring in the call center 4. Social Media monitoring in the call center

3. Work at Home Agents/Virtual Contact Centers3. Work at Home Agents/Virtual Contact Centers

2. Multimedia communication channels – blending 2. Multimedia communication channels – blending email, chat, phone. Agents are expected to email, chat, phone. Agents are expected to interact at different levels.interact at different levels.


1. The use of data analytics to develop a 1. The use of data analytics to develop a multichannel approach to reach out to a multichannel approach to reach out to a wide variety of consumers in the most wide variety of consumers in the most personalized and effective way.personalized and effective way.

Tweet questions or comments with hashtag #ATAdata

Traditional direct marketing often was like trying to force a square peg into a round hole.

Today, a customized solution is the only cost effective approach.

The Implementation and Impact of PredictiveThe Implementation and Impact of Predictive

Modeling on Telemarketing Acquisition Modeling on Telemarketing Acquisition

Case StudyCase Study

•Many clients traditionally use rental or exchange lists for acquisition efforts

•A 20% success rate is typical

•The goal is to develop and use a predictive model to improve results utilizing rental lists

•First step:

•Apply the model to rental lists to develop segmentation strategies

• Improve performance and drive down costs

•Second Step:

• Improve performance and drive down costs through dynamic request strategies

Define the current customer

base with profiling

Apply the model to rental list and

segment prospects

Model the current customer base to target for

acquisition

•First step:


•First step:

Psychographic

Demographic Transactional

•First step:• Analyze current customer base and define key

demographic and psychographic attributes:• Age• Education Level• Home Value• Income• Family Position• Gender

• Create “Model” donor• Overlay model onto response list and score prospects

The Implementation and Impact of BusinessThe Implementation and Impact of Business

Intelligence on Telemarketing AcquisitionIntelligence on Telemarketing Acquisition

•Second step:

•Now that the audience is scored and segmented

• How do we now impact the offer?

•Analyze various affluence indicators and their relationship to offers

•Apply this information to develop a dynamic offer utilizing variable scripting technology


•Findings:• Household income displayed the highest correlation to gift

amounts

• Household incomes were then broken into five income bands ranging from low to high

• Each income band was given a specific gift ask

• The key metrics we were looking to influence were:

• Response rate

• Average gift

• Dollars per call

• Efficiency

•Dynamic GRC results against control:

•Revenue per call increased by 27%

•Response rate increased by 16%

•Average gift increased by 11%

•Also showing an increase were credit card

rates at 12%

•Not only were gross conversions impacted but

stick rate and ROI dramatically improved

Superior Lead Generation through Superior Lead Generation through

Real Time Scoring and Targeted RoutingReal Time Scoring and Targeted Routing

Online Application StudyOnline Application Study

Here’s how R3 works: Fast Response

A request comes in from yourwebsite

Quick Routing

An InfoCision communicatorpromptly contacts the lead

Intelligent Transfer

Calls are transferred to agentsor counselors if needed

•Step 1: Potential customer clicks on online ad or

webpage and is directed to online application

•Step 2: Customer fills out form and presses

“contact me” option

•Step 3: Self reported data is “pinged” against the

consumer database to append additional

demographic information

• Step 4: Customer data is then scored against pre-built

model

• Step 5: Offer is customized and/or altered based on score

• Step 6: Call is directed to appropriately skilled

communicator and an outbound call is generated and

routed

• Step 7: Calls are transferred to agents or counselors if

needed


Market Applications:

EducationStudent requests

information about specific campus or educational

program

FinancialProspect requests more

information about a specific type of loan or

offer

CommercialCustomer expresses interest in a specific

product line or service

Calls are routed to Agents or Counselors who are trained and knowledgeable on

those specific products and markets

Ata 2010 Steve Brubaker Data Analytics

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