“Who's Calling? Customizing the Caller Experience to Feed the Bottom Line”

Who’s Calling? Customizing the Caller Experience to Feed the Bottom Line Ken Dawson Chief Marketing Officer InfoCision Management Corp. www.infocision.com

Agenda Best practices in acquisition…Real-Time Scoring leads Customized offers Multi-channel marketing using business intelligence Use of skills based routing Online lead generation It’s all about the ROI! Run towards the Light!

Predictive Modeling in Telemarketing Acquisition “ Let’s Crawl” A Non Profit Case Study

Challenge Non Profit clients traditionally use rental or exchange lists for acquisition efforts A 20% success rate of these lists is typical creating a tremendous “sunk cost” The goal is to develop and use a predictive model to improve results on rental lists

Solution First step: Apply the model to rental lists to develop segmentation strategies Improve performance and drive down costs by eliminating lower deciles Second Step: Utilize analytics and variable script technology to customize the marketing message and/or the offer for further penetration of list

First Step Demographic Who am I? Transactional What have I done? Psychographic What do I do?

First Step Define the current donors with profiling Apply the model to rental list and segment prospects Model the current donors to target for acquisition

First Step +17% +21% +17% +21%

Second Step Now that the audience is scored and segmented How do we now impact the offer? Auction method? How do we customize the appeal? Prevention or treatment? Analyze various affluence indicators and their relationship to gift amounts Apply this information to develop a dynamic gift ask 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 Second Step

The five income bands used are: The second step was to index these incomes by the Cost of Living Index to normalize data Second Step

The results were conclusive against the control: Second Step

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 Second Step

Lessons Learned Predictive modeling can have a dramatic impact on acquisition results…even on response lists Crafting a message that resonates with the customer can increase both conversion AND retention (lifetime value) Access to analytic tools and clean data paramount to modeling and segmentation True value of this data must be unlocked with technology that allows truly customized offers to the consumer

Utilizing Analytics and a Progressive Multi-touch Marketing Strategy To Reduce Customer “Churn” “ Now We are Walking”

Client Profile: National Communications provider with “millions” of customers Regional competition driving variable offers that are hard to manage Brick and Mortar stores carry significantly higher cost structure and are focused on acquisition NOT retention Multi-Channel

Shrinking retention budgets Increasing mail and postage costs Diminishing response rate to static Direct Mail offers Basic segmentation strategy did not accurately reflect “churn” Challenge

Utilize analytics and modeling to identify likely to “churn” customers Utilize analytics and modeling to unlock variable offers and segmentation Propose a multi-channel and cost-progressive strategy to increase ROI and marketing effectiveness Employ multiple call center strategies to reduce talk time and expense Solution

Control Retention Program: Basic segmentation strategy based on contract expiration Direct Mail offers driven by current plan and usage only Timing starts at 90 days to expiration and continues through 60 days after contract expiration Each customer is mailed multiple times with same or similar offers Drive customer to inbound phone call for contract signing Control

Control Control Campaign (Direct Mail Sent to Every Customer)

Multi-Channel Multi-Channel Customer Retention Strategy

Strategies Employed Business Intelligence Group and Analytical Modeling Variable Scripting and Offers One-to-one Direct Mail/Digital Printing Target Routing/Skill Based Routing IVR Verification Best Time To Call/Bucket Calling Efficiency Based Dialing Strategies Front-end (Starter) / Back-end (Closer) Based Dialing Strategies

Multi-Channel Payment issues 2.225 m customers to be targeted Certain geographies Do not contact 2.25M customers to be targeted Filter out Propensity to churn Over-utilization Contract expiration Old equipment Low usage

Multi-Channel Keep customer away from retail outlet 160k calls 8 % RR Do not text Non- responders E-Verification E-Contract Offer Based on BI Model Offer Based on plan type Phone exclusive offer Filter 225k removed Old equip/ No text capability 160K Calls @ 8% RR

Multi-Channel Do Not Mail E-Verification E-Contract Filter ROI Filter: Usage/ Profitability Bad Addresses Keep customer away from retail outlet 461K Removed Phone Exclusive Offer Personalized Geography Offer Based On BI Model Offer Based On Plan Type Demographic Psychographic Drivers 55K Calls @ 4% RR

Multi-Channel Do Not Call E-Verification E-Contract Filter Respondents to Text or Direct Mail Keep customer away from retail outlet Billing Cycle 405K Contacts Made Offer Based On BI Model Offer Based On Plan Type Phone Exclusive Offer 74K Calls More Stringent ROI Filters 649K Removed

Multi-Channel Control Campaign (Direct Mail Sent to Every Customer)

Multi-Channel Multi-Channel Campaign

Multi-Channel Multi-Channel Campaign Summary

Lessons Learned Analytics and modeling can be used to identify customers likely to “churn” Additional modeling can be used to craft the appropriate offer There must be communication and cooperation among all channels to identify the best approach in order to reduce marketing costs

The Impact of Skills Based Routing With Real Time Scoring “ Off and Running”

Challenge Leading consumer product company is seeing substantial success in new product launch (YES, it’s a good thing) Calls driven by DRTV offers and have significant spikes Incumbent and in-house center have been taking calls for several years Over $700 average sale with no advertised price Current strategy is “answer the calls, stupid”

Solution First, implementing skills based routing to move beyond next available agent methodology Use real-time as well as historical data to make sure the best agents are taking the most calls Second, the application of real-time scoring to further enhance results “ Ping” inbound callers against the pre-scored consumer database Use the real-time scoring to build the call queue and prioritize best leads

Lessons Learned Analytics can be used real-time to determine the best agent to answer calls. You must look at both historical as well as real-time results to prioritize Real-time scoring can be used to create the priority queue as well as drive IVR solutions when needed to enhance overall results Superior customer experience (hold times, one call resolution, abandon rates, etc) HIGHER ROI!

Rapid Response and Real-Time Scoring of Internet Leads

Challenge Following up on internet driven leads quickly Combining self-reported data and real-time scoring to customize offer or message Matching the online lead with the right agent or counselor

Rapid Response Routing Here’s how R3 works: Fast Response A request comes in from your website Quick Routing Data is appended, offer created, Call is routed to Agent for Outbound dial Intelligent Transfer Calls are transferred to agents or counselors if needed

Rapid Response Routing Market Applications Education Student requests information about specific campus or educational program Financial Prospect requests more information about a specific type of loan or offer Commercial Customer 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

Lessons Learned In the classic Crawl, Walk, Run scenario call centers have migrated through the steps to integrate intelligence into our marketing on all levels It’s imperative to have access to the best data in a real-time environment to maximize ROI The best models may not see the light of day without superior technology Don’t be afraid of the infrastructure or budgetary constraints of YOUR organization...find partners that have solutions in place to implement for you YOU CAN DO IT!

“Who's Calling? Customizing the Caller Experience to Feed the Bottom Line”

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