Customer Analytics: Strategies for Success John Keyes SoundBite Communications

Contact center analysis Outbound analytics and optimization Agenda Overview of analytics Contact center analysis Outbound analytics and optimization 2

Overview of Analytics Performance Analytics Predictive Analytics Reports that show past performance and trends Predictive Analytics Models that make predictions / forecasts Overview of Analytics Help to answer the following questions: How has my contact center been performing? What has been the best day and time to reach call recipients? When should I change my treatment and/or script strategy? Have recipients been responding across all types, scores, balances, and ages? Help to answer the following questions: Should I contact this account? If so, what should my method of contact be? When and how often should this account be contacted? What is the probability of this account responding? How much should I spend to try to get this account to respond? 3

3 levels of treatment Level Description Statistical Examples Portfolio Level Treat the entire population in the portfolio the same. Data Mining Performance Analytics Segment Level Create sub-groupings of the population and treat each sub-group the same. Clustering Segmentation Record Level Treat each individual in the population as a unique entity. Regression Models What-if Simulations 4

Analytics Progression Category Description Examples Measurement and Reporting Tracking and summarizing campaign results using pre-determined or ad-hoc metrics. Campaign Reports A/B Testing and Measurement Strategic Data Analysis Monitoring and analysis of trends in data to produce conclusions with significant business meaning and strategic inputs. Performance Analytics Trending Analysis Seasonality Analysis Heuristic / Data Driven Segmentation / Scoring Organizing customers into meaningful groups for business management or differential treatments based on business rules / decision trees / clustering techniques. Balance-score Based Segments/Scoring Multi-attributes Data Driven Segments/Scoring Predictive Modeling/Scoring Applying statistical modeling techniques to predict and maximize individual customer behavior. Likelihood to Pay Recovery Score, Action Score Simulated Optimization Using optimization algorithm to assign customer treatments that satisfy defined business objectives and resource constraints. What-if Scenario Simulations 5

Examples: Performance Analytics Contact Center Performance Analytics Hold times by hunt group (including time of day / day of week) Recipient willingness to hold Hold and ring time trends Agent talk time distributions across campaigns Call Recipient Performance Analytics Call pass & device escalation effectiveness Best time of day / day of week Responses across locations (region, state, zip code, area code, time zone, etc) Script hang-up graphs Responses by recipient characteristics (score, balance, etc.) Test and Control performance results (A/B Testing) 6

Integration with analytics partners Client Database Partner: Should this account be called? Analytical Data “Yes” Calling Strategy Optimization Analytics “No” Holdout or Other Treatment 7

Contact Center Analytics 8

Contact Center Service Level Analytics Willingness to Hold 9

Analyzing the Components of Wait Time 4 Seconds 18 Seconds 20 Seconds 8 Seconds 10 Seconds 12 Seconds 50 Seconds 22 Seconds 10

Time of Day in the Contact Center “My average service level is 18 seconds so I don’t need to make any improvements to my contact center.” Tuesday Contact Center Analytics Time of Day Busy % No Answer % Success % Hold Time 9:00 A.M. 18% 1% 62% 48 seconds 10:00 A.M. 6% 0% 78% 22 seconds 11:00 A.M. 2% 3% 92% 16 seconds 12:00 P.M. 15% 72% 28 seconds 1:00 P.M. 77% 2:00 P.M. 87% 12 seconds 3:00 P.M. 10 seconds 4:00 P.M. 14 seconds 5:00 P.M. 7% 76% 21 seconds 6:00 P.M. 11% 68% 37 seconds 11

Skill Group Reporting 12

AVM / Contact Center Analysis 13

Skill Group / Right Party Talk Time Analytics 14

Outbound Analytics and Optimization 15

Calling Time Zone / Time Focus Analysis 16

Call Pass Effectiveness Analysis 25 – 30% Live% 50 – 55% AM 1 Pass Total Inbound: DCs: 30 Callbacks: 22 65 – 75% Live% 15 – 25% AM 3 Pass Total Inbound: DCs: 75 Callbacks: 10 17

Day of Week Analysis 18

Time of Day Analysis 19

Banding Results: By Balance 20

Banding Results: By Age 21

Banding Results: By Score 22

Script Effectiveness 23

Device Escalation Effectiveness Analysis Work, Home, Cell 1.88% Promise % 2.18% Promise % Home, Home, Cell 24

Multi-lingual Scripting Options Add Spanish Option 25

Geographical Analysis-Voice Dialects Country Time Zone Region State Area Code 26

Dashboard / KPI Management 27

Summary Don’t just look at averages Drill to the lowest level Start with contact center performance analytics Outbound performance analytics KPIs and measurement A/B testing Predictive Analytics Don’t just look at averages Drill to the lowest level Measure, Measure, Measure! 28

Thank you! John Keyes SoundBite Communications jkeyes@soundbite.com 781-359-2236