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Ata 2010 Steve Brubaker Data Analytics

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InfoCision Chief of Staff Steve Brubaker shared this presentation about data analytics and business intelligence during a session at the 2010 ATA Convention & Expo

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Ata 2010 Steve Brubaker Data Analytics

  1. 2. Intelligent Interactions Improve Response Rates by Getting to Know Your Customers Through Data Analytics Steve Brubaker Chief of Staff InfoCision Management Corp. www.infocision.com
  2. 3. <ul><li>Agenda </li></ul><ul><ul><li>The impact of modeling on acquisition </li></ul></ul><ul><ul><li>Using business intelligence to drive results </li></ul></ul><ul><ul><li>Online lead generation </li></ul></ul><ul><ul><li>Multi channel marketing using business intelligence </li></ul></ul>
  3. 4. Top trends in the contact center industry 10. Cell phones – erosion of landlines 9. Trend back to the phone call – technology is driving down call center costs while paper and postal costs are increasing direct mail costs. 8. VOIP – Voice Over Internet Protocol
  4. 5. Top trends in the contact center industry 7. Salaried contact center agents 6. Highly/Specially trained agents with ability to free flow conversations and not always work off a script 5. Skill based inbound customer service – impacts up-selling and cross-selling. Inbound doesn’t make $. By up-selling and cross-selling you can make $.
  5. 6. Top trends in the contact center industry 4. Social Media monitoring in the call center 3. Work at Home Agents/Virtual Contact Centers 2. Multimedia communication channels – blending email, chat, phone. Agents are expected to interact at different levels.
  6. 7. Top trends in the contact center industry 1. The use of data analytics to develop a multichannel approach to reach out to a wide variety of consumers in the most personalized and effective way. Tweet questions or comments with hashtag #ATAdata
  7. 8. <ul><li>Traditional direct marketing often was like trying to force a square peg into a round hole. </li></ul><ul><li>Today, a customized solution is the only cost effective approach. </li></ul>
  8. 9. The Implementation and Impact of Predictive Modeling on Telemarketing Acquisition Case Study
  9. 10. <ul><li>Many clients traditionally use rental or exchange lists for acquisition efforts </li></ul><ul><li>A 20% success rate is typical </li></ul><ul><li>The goal is to develop and use a predictive model to improve results utilizing rental lists </li></ul>
  10. 11. <ul><li>First step: </li></ul><ul><ul><li>Apply the model to rental lists to develop segmentation strategies </li></ul></ul><ul><ul><li>Improve performance and drive down costs </li></ul></ul><ul><li>Second Step: </li></ul><ul><ul><li>Improve performance and drive down costs through dynamic request strategies </li></ul></ul>
  11. 12. <ul><li>First step: </li></ul>Tweet questions or comments with hashtag #ATAdata 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
  12. 13. <ul><li>First step: </li></ul>Psychographic Demographic Transactional
  13. 14. <ul><li>First step: </li></ul><ul><ul><li>Analyze current customer base and define key demographic and psychographic attributes: </li></ul></ul><ul><ul><ul><li>Age </li></ul></ul></ul><ul><ul><ul><li>Education Level </li></ul></ul></ul><ul><ul><ul><li>Home Value </li></ul></ul></ul><ul><ul><ul><li>Income </li></ul></ul></ul><ul><ul><ul><li>Family Position </li></ul></ul></ul><ul><ul><ul><li>Gender </li></ul></ul></ul><ul><ul><li>Create “Model” donor </li></ul></ul><ul><ul><li>Overlay model onto response list and score prospects </li></ul></ul>
  14. 15. The Implementation and Impact of Business Intelligence on Telemarketing Acquisition
  15. 16. <ul><li>Second step: </li></ul><ul><ul><li>Now that the audience is scored and segmented </li></ul></ul><ul><ul><ul><li>How do we now impact the offer? </li></ul></ul></ul><ul><ul><li>Analyze various affluence indicators and their relationship to offers </li></ul></ul><ul><ul><li>Apply this information to develop a dynamic offer utilizing variable scripting technology </li></ul></ul>Tweet questions or comments with hashtag #ATAdata
  16. 17. <ul><li>Findings: </li></ul><ul><ul><li>Household income displayed the highest correlation to gift amounts </li></ul></ul><ul><ul><li>Household incomes were then broken into five income bands ranging from low to high </li></ul></ul><ul><ul><li>Each income band was given a specific gift ask </li></ul></ul><ul><ul><li>The key metrics we were looking to influence were: </li></ul></ul><ul><ul><ul><li>Response rate </li></ul></ul></ul><ul><ul><ul><li>Average gift </li></ul></ul></ul><ul><ul><ul><li>Dollars per call </li></ul></ul></ul><ul><ul><ul><li>Efficiency </li></ul></ul></ul>
  17. 18. <ul><li>Dynamic GRC results against control: </li></ul><ul><ul><li>Revenue per call increased by 27% </li></ul></ul><ul><ul><li>Response rate increased by 16% </li></ul></ul><ul><ul><li>Average gift increased by 11% </li></ul></ul><ul><ul><li>Also showing an increase were credit card rates at 12% </li></ul></ul><ul><li>Not only were gross conversions impacted but stick rate and ROI dramatically improved </li></ul>
  18. 19. Superior Lead Generation through Real Time Scoring and Targeted Routing Online Application Study
  19. 20. Tweet questions or comments with hashtag #ATAdata
  20. 21. Here’s how R3 works: Fast Response A request comes in from your website Quick Routing An InfoCision communicator promptly contacts the lead Intelligent Transfer Calls are transferred to agents or counselors if needed
  21. 22. <ul><li>Step 1: Potential customer clicks on online ad or webpage and is directed to online application </li></ul><ul><li>Step 2: Customer fills out form and presses “contact me” option </li></ul><ul><li>Step 3: Self reported data is “pinged” against the consumer database to append additional demographic information </li></ul>
  22. 23. <ul><li>Step 4: Customer data is then scored against pre-built model </li></ul><ul><li>Step 5: Offer is customized and/or altered based on score </li></ul><ul><li>Step 6: Call is directed to appropriately skilled communicator and an outbound call is generated and routed </li></ul><ul><li>Step 7: Calls are transferred to agents or counselors if needed </li></ul>Tweet questions or comments with hashtag #ATAdata
  23. 24. 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

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