Out of 140 total interactions without requiring customer service team involvement
The RTR Customer Service companion is successfully deflecting 80% of customer inquiries, handling 112 out of 140 interactions without requiring customer service team involvement. This represents a significant reduction in email volume and CS workload, with the bot autonomously managing FAQs, product questions, quote collection, and return information.
Key Performance Indicators
1
Total Customer Interactions:
140 interactions over 18 days (7.8 per day average)
2
Customer Service Deflection:
112 interactions (80%) handled without CS team involvement
3
Escalations to Team:
28 interactions (20%) requiring human assistance
4
AI Adoption:
65% of customers chose AI-powered "Ask Anything" mode
5
Email Volume Reduction:
~336 email exchanges avoided (assuming 3 exchanges per inquiry)
What the Bot Successfully Handles
The bot is autonomously managing the following inquiry types without CS involvement:
FAQ Self-Service
27 interactions
Customers navigate structured FAQ menu to find answers about policies, shipping, warranties, and processes.
AI-Powered Assistance
70 interactions
GPT provides detailed answers about products, specifications, fitment, and general inquiries.
Quote Information Collection
8 forms
Bot collects customer details, vehicle information, and installation preferences for the sales team.
Return Policy Guidance
3 inquiries
Provides return policy details, eligibility requirements, and process steps.
What Still Requires Human Touch (20%)
28 inquiries were escalated to the CS team. Analysis of these escalations reveals consistent patterns:
Product Availability (Primary)
"Are Tech 7 wheels available in bronze?"
"Do you still make the F150 front skid plate?"
"When will [discontinued item] be back in stock?"
Spec Model Technical Details
"What's included in Spec 5 vs standard Dark Horse?"
"Spec 5 Mustang S650 powertrain differences?"
"Can I upgrade my current Mustang to RTR Spec 5?"
Replacement Parts & Damage
"Need passenger side decals after accident"
"Replacement components for 2024 Spec 2"
Direct Contact Requests
"What's your phone number?"
"I need to speak with a live person"
"Customer service contact info"
Activity Patterns & Trends
Daily Volume
Peak activity days during production period:
Sep 28: 28 interactions
Oct 09: 15 interactions
Oct 13: 14 interactions
Oct 07: 11 interactions
Oct 03: 10 interactions
Oct 10: 9 interactions
Oct 02: 8 interactions
Hourly Distribution
Peak hours align with West Coast business hours:
15:00 - 15 interactions
13:00 - 15 interactions
09:00 - 14 interactions
12:00 - 13 interactions
07:00 - 11 interactions
Phase 2: Product Catalog Integration
Opportunity: The primary escalation driver is product availability questions. Integrating real-time product catalog data will directly address this bottleneck.
Expected Impact with Product Catalog
Higher Deflection Rate
Target: 85-90% (up from 80%) Answer availability questions without human lookup
Reduced Escalations
Eliminate #1 escalation reason Bot can check inventory and discontinued items in real-time
Proactive Recommendations
Smart product suggestions When items unavailable, suggest alternatives automatically
Better Customer Experience
Instant answers vs waiting No more "let me check and get back to you" delays
Implementation Priorities
01
Product specifications and fitment data
02
Related product recommendations
03
Price and availability for wheel/tire bundles
04
Spec model component breakdowns
Return on Investment
Current Impact (18 days of production):
Inquiries handled: 112
Estimated emails avoided: ~336 (3 exchanges per inquiry)
CS team time saved: ~16.8 hours (assuming 3 min per email)
Deflection rate: 80%
Projected Annual Impact:
Projected annual interactions: ~2,842 (based on 7.8/day average)
Annual deflection: ~2,274 inquiries
Annual emails avoided: ~6,822
Annual CS hours saved: ~341 hours
Note:These projections are conservative based on soft launch data. With Phase 2 product catalog integration, deflection rates could increase to 85-90%, further amplifying the impact.
Conclusion & Next Steps
The RTR Customer Service Bot is delivering strong results with an 80% deflection rate, successfully handling the majority of customer inquiries without CS team involvement. The bot has proven particularly effective at FAQ navigation, AI-powered assistance, and information collection for quotes and returns.
The clear opportunity for Phase 2 is product catalog integration. With 20% of escalations driven by availability questions, connecting the bot to real-time inventory data will directly address the primary bottleneck and push deflection rates toward 85-90%.
Immediate Next Steps
1
Finalize Phase 2 product catalog integration plan
2
Define API requirements for product data
3
Prioritize Spec model and wheel fitment data
4
Set target launch date for enhanced bot
5
Establish metrics tracking for ongoing optimization