AI Automated Inbound - Project Details / Task List
Tag: ai-inbound
Total Hours: 65h
Structure: Multi-Milestone (>50h)
Milestone 1: AI Automated Inbound - 1. Discovery, Design & Integration
Tag: ai-inbound
Description: Stakeholder discovery, playbook design, and technical integration setup for AI-powered inbound engagement platform.
Hours: 45h
Task List: (AI Automated Inbound) 1. Discovery & Playbook Design
Contains: Parts 1-2
| Task | Est | Description |
|---|---|---|
| 1. Conduct Stakeholder Discovery Session | 2.5h | Meet with Marketing, Sales, and RevOps leadership to align on inbound engagement goals and define success metrics. End state: Documented goals for MQL-to-SQL conversion, speed-to-lead targets, and meeting booking rates. • Schedule 60-90 minute discovery session with Marketing, Sales Ops, and Sales leadership • Define primary inbound engagement goals (e.g., 2X meetings booked, <5 min speed-to-lead) • Document current MQL-to-SQL conversion rate as baseline • Identify key buyer segments and their typical on-site behaviors • Clarify budget and timeline constraints for tool selection • Capture stakeholder expectations for AI vs. human handoff scenarios |
| 2. Audit Current Inbound Workflows | 2.5h | Assess existing inbound processes, website visitor data, and qualification criteria to identify gaps and opportunities. End state: Gap analysis showing current state vs. desired state with specific improvement areas. • Map current lead capture mechanisms (forms, demo requests, contact pages) • Pull speed-to-lead metrics from CRM (time from form submission to first response) • Document existing qualification criteria (BANT, MEDDIC, or custom framework) • Identify high-traffic pages where inbound intent signals are strongest • Review current routing rules and SLA compliance rates • Quantify missed opportunities (e.g., "40% of demo requests never get follow-up within 24 hours") |
| 3. Evaluate and Select AI Inbound Tool | 3h | Compare AI inbound platform options against client's tech stack, requirements, and budget. End state: Tool selected (e.g., Qualified.com, Drift) with procurement approved. • Document client's current tech stack (CRM, MAP, website platform, existing chat tools) • Evaluate options: Qualified.com, Drift, Intercom, HubSpot Conversations • Compare on: CRM compatibility, AI capabilities, meeting booking, analytics depth, cost per seat • Assess integration complexity with existing systems • Present recommendation with ROI projections to stakeholders • Get budget approval and initiate procurement/contract process |
| 4. Map Buyer Segments and On-Site Behaviors | 3h | Define key buyer personas and the on-site behaviors that indicate buying intent for each segment. End state: Documented buyer segment map with intent signals and qualification criteria per segment. • Identify 3-5 primary buyer segments (e.g., enterprise vs. SMB, by industry, by role) • Map high-intent behaviors per segment (pricing page visits, demo page, security pages) • Define qualification criteria for each segment using existing framework • Document account signals (company size, industry, tech stack) that indicate fit • Create segment-specific routing rules (e.g., enterprise → AE, SMB → SDR) • Validate segment definitions with Sales leadership |
| 5. Design Conversational Playbooks | 4h | Create AI chat playbooks with qualification questions, value prompts, and objection handling for each buyer segment. End state: Complete conversational flow documents ready for tool configuration. • Draft 3-5 conversational playbooks aligned to buyer segments and intent levels • Define opening messages based on page context (pricing vs. blog vs. product pages) • Create qualification question sequences (3-5 questions per flow) • Write value prompts and benefit statements for key objections • Define escalation triggers for human handoff (complex questions, high-value accounts) • Include meeting booking CTAs at optimal points in conversation flow • Document fallback responses for out-of-scope questions |
| 6. Define Routing Rules and Escalation Logic | 3h | Establish routing rules for hot leads, existing customers, target accounts, and non-fit visitors. End state: Complete routing matrix with owner assignments and SLA targets. • Create routing matrix: segment × intent level × owner/queue • Define rules for existing customers (route to CSM or dedicated queue) • Set up ABM-specific routing for target accounts (priority queue, specific AE) • Establish non-target visitor handling (resource offer, nurture path, graceful exit) • Define SLA targets for each queue (e.g., hot leads <2 min, standard <5 min) • Document after-hours routing logic (meeting booking only vs. queue for morning) |
Task List: (AI Automated Inbound) 2. Integration & Configuration
Contains: Parts 3-4
| Task | Est | Description |
|---|---|---|
| 7. Connect AI Platform to CRM | 3h | Establish bidirectional connection between Qualified.com (or selected tool) and CRM with proper API permissions. End state: AI platform connected to CRM with leads/contacts syncing correctly. • Configure OAuth connection to Salesforce or HubSpot • Grant required API permissions (read/write leads, contacts, accounts, activities) • Map AI platform fields to CRM standard and custom fields • Set up lead/contact creation rules (create new vs. update existing) • Configure account matching logic for known visitors • Test bidirectional sync with sample records • Document integration settings for client handoff |
| 8. Set Up Data Enrichment Integration | 3h | Connect data enrichment tools to enable real-time visitor identification and account scoring. End state: Enrichment flowing into AI platform for personalized, data-driven conversations. • Connect enrichment tools (Clearbit, ZoomInfo, 6sense, or native enrichment) • Configure reverse IP lookup for company identification • Set up contact enrichment for known visitors (title, seniority, department) • Define enrichment triggers (on page load vs. on engagement) • Map enriched data to AI platform variables for personalization • Test enrichment accuracy with sample visitors |
| 9. Integrate Marketing Automation Platform | 3h | Connect AI platform to MAP for lead scoring sync and nurture workflow triggers. End state: Leads scored correctly with automated nurture enrollment based on AI interactions. • Connect to HubSpot, Marketo, or Pardot via native integration or API • Configure lead score sync from MAP to AI platform (for prioritization) • Set up activity logging from AI platform to MAP (conversation events) • Define nurture enrollment triggers based on AI qualification outcomes • Configure lead source/campaign tracking for attribution • Test end-to-end flow: visitor → AI chat → CRM lead → MAP nurture |
| 10. Configure AI Chatbot Foundation | 3.5h | Set up core AI chatbot configuration including appearance, behavior settings, and base AI training. End state: AI chatbot deployed on website with foundational settings in place. • Configure chatbot appearance (colors, logo, positioning) to match brand • Set up bot personality and tone of voice aligned with company brand guidelines • Configure AI training with company-specific context (product info, pricing tiers, competitors) • Set up knowledge base connections for accurate responses • Define bot behavior by page type (aggressive on pricing, passive on blog) • Configure mobile vs. desktop experience differences • Set initial AI confidence thresholds for escalation |
| 11. Implement Conversational Playbooks | 4h | Build out the designed conversational flows in the AI platform with all qualification paths and routing logic. End state: All playbooks configured and ready for testing. • Build each conversational playbook in the platform • Configure conditional branching based on visitor responses • Set up qualification data capture (company size, use case, timeline, budget) • Implement routing logic per playbook (trigger assignments, queue selections) • Configure meeting booking integration (calendar connections, availability rules) • Set up real-time alerts for high-priority visitors (Slack, email, SMS) • Add personalization tokens using enrichment data |
| 12. Configure Meeting Booking Experience | 3.5h | Set up real-time meeting booking with calendar integrations and availability rules. End state: Visitors can book meetings directly from AI conversations with correct rep calendars. • Connect rep calendars (Google Calendar or Outlook) to AI platform • Configure availability windows and buffer times per rep • Set up round-robin or weighted distribution logic • Define meeting types (15 min intro, 30 min demo, 60 min deep dive) • Configure confirmation emails and calendar invites • Set up rescheduling and cancellation workflows • Test booking flow end-to-end with multiple rep calendars |
| 13. QA and Test All AI Experiences | 4h | Conduct comprehensive testing of all conversational flows, routing, and integrations before launch. End state: All flows tested, issues resolved, and system ready for pilot launch. • Test each playbook flow manually (happy path and edge cases) • Verify routing delivers to correct owner/queue for each scenario • Test CRM record creation and field mapping accuracy • Verify enrichment data appearing correctly in conversations • Test meeting booking across all rep calendars and time zones • Validate mobile experience functionality • Test after-hours behavior and fallback scenarios • Document any issues and resolve before pilot |
Milestone 2: AI Automated Inbound - 2. Rollout & Optimization
Tag: ai-inbound
Description: Pilot launch, team training, full rollout, and ongoing optimization with performance monitoring.
Hours: 20h
Task List: (AI Automated Inbound) 3. Rollout & Optimization
Contains: Parts 5-6
| Task | Est | Description |
|---|---|---|
| 14. Launch Pilot with Select Rep Group | 3h | Deploy AI inbound to a subset of traffic/reps to validate performance before full rollout. End state: Pilot running with initial data on engagement, meeting booking, and rep feedback. • Select 3-5 reps for pilot group (mix of SDR and AE if applicable) • Configure traffic routing to limit AI exposure (e.g., 25% of traffic) • Brief pilot reps on what to expect and how to handle AI-sourced leads • Monitor first 48-72 hours closely for issues • Collect rep feedback on lead quality and handoff experience • Track pilot metrics: engagement rate, qualification rate, meetings booked • Identify and resolve any issues before scaling |
| 15. Train Sales and Marketing Teams | 2h | Conduct training sessions for Sales and Marketing on using AI platform insights, notifications, and chat handoff. End state: Teams trained and confident using the new system. • Schedule 45-minute training session with full Sales team • Cover: how AI qualifies leads, real-time notification handling, chat takeover process • Train on using AI platform dashboard for visitor insights • Demonstrate how to access conversation transcripts in CRM • Create quick-reference guide for common scenarios • Train Marketing on monitoring AI engagement analytics • Record training session for onboarding new reps |
| 16. Launch Full Rollout | 2h | Expand AI inbound to all traffic with full routing to all reps. End state: AI chatbot and meeting booking live across website with all reps receiving leads. • Expand traffic routing to 100% • Enable all reps in routing pool • Configure monitoring dashboards for real-time performance tracking • Set up daily/weekly automated reports to stakeholders • Establish Slack channel for issue escalation and feedback • Communicate launch internally with expectations and SLAs |
| 17. Establish Performance Monitoring Dashboards | 3h | Build dashboards tracking key AI inbound metrics for ongoing optimization. End state: Dashboards live showing engagement, conversion, and speed-to-lead metrics. • Create AI platform native dashboard with key metrics • Build CRM reports for AI-sourced lead conversion tracking • Set up speed-to-lead measurement (form submit to first response) • Configure meeting booking funnel metrics (booked → held → converted) • Create comparison view: AI-sourced vs. traditional form leads • Set up automated weekly report delivery to stakeholders |
| 18. Conduct 30/60/90 Day Reviews | 4h | Review AI inbound performance at regular intervals and refine playbooks based on data. End state: Documented optimizations implemented with measurable improvement. • Schedule 30-day review meeting with stakeholders • Analyze: which playbooks perform best, where visitors drop off, routing efficiency • Identify underperforming segments or flows for optimization • Review AI response accuracy and escalation patterns • Adjust qualification questions based on Sales feedback • Refine routing rules based on conversion data • Document changes and expected impact • Repeat at 60 and 90 days with deeper analysis |
| 19. Hand Off to Client | 3h | Transfer ownership, documentation, and ongoing optimization playbook to client team. End state: Client self-sufficient with admin access, runbooks, and clear optimization process. • Transfer admin credentials to client RevOps/Marketing Ops • Deliver documentation package (configuration settings, playbook logic, integration details) • Create optimization runbook for ongoing refinement • Document troubleshooting procedures for common issues • Train client admin on making configuration changes • Schedule 90-day check-in for questions and advanced optimization • Close out project with final performance summary |
Summary
- Total Milestones: 2 (45h + 20h)
- Total Task Lists: 3 (consolidated from 6 Parts)
- Total Tasks: 19 (one per Step)
- Total Hours: 65h
- Generated from: playbook_ai-automated-inbound.md
- Generated on: 2025-12-31