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Smart Engagement via Predictive Intelligent Targeting

Smart Engagement via Predictive Intelligent Targeting. AGENDA. Brief PIT Overview Implementing PIT Managing and Optimizing PIT QA. PIT Overview. What is Predictive Intelligent Targeting?.

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Smart Engagement via Predictive Intelligent Targeting

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  1. Smart Engagement via Predictive Intelligent Targeting

  2. AGENDA • Brief PIT Overview • Implementing PIT • Managing and Optimizing PIT • QA

  3. PIT Overview

  4. What is Predictive Intelligent Targeting? • Predictive Intelligence Targeting (PIT) is an analytical tool that determines a visitor’s likelihood to “convert” on a website. • PIT uses several mathematical behavior models to determine a visitors predicted behavior and then scores visitors to ensure that the most relevant customers are targeted and sent an invitation to engage at the optimum time. • The model is constantly learning to ensure it adjusts and improves over time. • The model is updated nightly.

  5. Value Proposition for Predictive Intelligent Targeting • Best target those visitors who will convert if assisted, instead of those who would convert on their own. • Continual learning and adapting over time • Automatically adjusts daily digesting new information and use it if it has predictive value. • The same or better conversion lift. • Fully captures all traffic monitored through a seamless tag across all main sites and channels.

  6. How PIT Works • Predictive Intelligent Targeting uses current and historical session data from Hadoop • Data includes: variables, website activity, visitor profile, geo-location, social media referrals, and chat history. • PIT uses three models to create a unified score to predict a visitors likelihood to convert: • Predict who is likely to chat? • Predict who is likely to convert with chat assistance? • Predict who is likely to convert without chat (self-service)? • Predictive Dialer controls invitations.

  7. Agent Profile Agent Pool Behavioral Processing Engagement Trigger 0.7 0.9 Chat 0.5 Self Serve 0.9 Agent Utilization Model Visitor Intent Model Real-time agent capacity determines engagement triggers 0.4 Monitor,Learn, Apply

  8. Visitor Intent Models – Closer Look Business Goal: Conversion Pending Invite: Based on agent availability Agent Availability: 0 Agent Availability: 1 Kelly San Francisco PC Added Items to Cart Kansas Mobile Referral: Free Promotion On Return Policy Page New York PC Browsed 10 Different Product Pages John Mary Score: 0.5(Predict Self Serve) Score: 0.75 (needs help shopping) Score: 0.2 (low value) Removes item from Cart Score: 0.8 (needs help)

  9. State of the Art Intent Models Social Media Visitor Profile Chat History Search KeyWords Referral Geo CRM Business Specific Events Navigation Patterns Purchase Patterns Self Serve Patterns • Intent to Convert via Chat Assisted Intent to Convert via Self Serve Visitor Intent Model Intent to Accept Chat Individualvisitors who are most likely to convert with chatassistance.

  10. Intelligently Engage Multiple-D Algorithm Predictive: Simplified & automatic 1D Rules Targeting: Complex, tedious, manual updates Rule 2 Rule 3 Rule 1 Rule 4 Rule 1 Rule 2 Rule 3 Rule 4 Rule 6 Rule 5 Rule 7 Rule 8 Rule 5 Rule 6 Rule 7 Rule 8 Rule 10 Rule 9 Rule 11 Rule 12 Rule9 Rule 10 Rule 11 Rule 12 Rule 15 Rule 13 Rule 14 Rule 16 Rule 13 Rule 14 Rule 15 Rule 16 Visitor Most Likely to Convert “Hot Lead”

  11. Implementing PIT

  12. Implementing PIT - Topics • Setting the Stage for PIT • A Phased Approach • Basic Rules for Engagement • Eligibility / Revocation / Invite Rules Overview • Visitor Population Rules & New Targets • Predictive Dialer Configurations

  13. Implementing PIT - Stage setting • No additional customer resources are necessary for the implementation. It is expected that no major changes to the program (creative, labor, etc.) will be implemented during this 4-5 week period. • Predictive Intelligent Targeting and Predictive Dialer work together: • Predictive Intelligent Targeting = Who to invite at a given moment • Predictive Dialer = How many invitations to send

  14. Implementing PIT – A Phased Approach PIT requires data (visitors/traffic) in order to build its model. In addition, most clients are moving from either manual rules or PT1 (or a combination of the two) such that a comparison is required. With these considerations, a phased approach to rollout is recommended. Phase 1: Baseline establishment – this period is where you run the PIT modeling rules behind the scenes, where PIT is gathering data but not controlling invites. The length of this period will be dependent upon traffic/chat volumes. Check with analytics for an estimate of how long this will take, in addition to confirmation of model completion. Phase 2: Implementation validation – during this phase you will run PIT for a segment of your visitor population. Standard for this phase is 10% PIT 90% PT1/rules. This phase is crucial to sanity check the implementation and to ensure proper operation.

  15. Implementing PIT – A Phased Approach (cont) Phase 3: Performance validation – during this phase a 50/50 split between PIT and PT1/PIT is recommended. This phase allows you to compare the performance of PIT vs legacy deployment without committing 100% of the site traffic. Pay close attention to your core conversion metrics as this is what PIT drives to. Phase 4: PIT enablement – this phase consists of moving to 100% PIT. Careful attention should be paid to your core funnel metrics to ensure proper implementation. Validation of this phase can take from a few days to several weeks dependent upon your volumes. Phase 5: PIT Optimization – this phase is a continuous cycle of optimization to your PDs to ensure optimum performance.

  16. Implementing PIT – Basic Rules for Engagement • PT-EligibleForChat • Set to no when visitor enters site • Set to no in revocation rules • Set to yes in eligibility rules • PT-EligibleInSession • Set to yes when PT-EligibleForChat is set to yes • Used in visitor population rules, to be leveraged in staffing calculators and reporting targets • PT-Convert • Set by rules (see example)

  17. Implementing PIT – Eligibility / Revocation / Invite Rules Used to set who is eligible and ineligible to chat. Also sets your invites and defines which PD should be leveraged.

  18. Implementing PIT – Visitor Population Rules and Targets Used to provide staffing calculators and to report on PIT performance in the button and proactive pipeline reports.

  19. Implementing PIT – Predictive Dialer Configuration Live Walkthrough

  20. Managing & OptimizingPIT

  21. KPIs to review after PIT • Chat-assisted conversions • Revenue • Chats per labor hour • Conversions per labor hour • Revenue per labor hour • Incremental revenue per labor hour • Avg wait time • Abandonment rate

  22. Mastering the Predictive Dialer

  23. Q&A

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