The Challenge: Fragmented Service
Our client, a prominent local retailer in Northern Virginia with five physical locations, faced a critical challenge: fragmented customer service. As their brand grew, so did the volume of inquiries across Instagram, email, and phone calls.
Staff were overwhelmed managing in-store customers while trying to answer repetitive questions about inventory and store hours. This resulted in an inability to handle after-hours inquiries, directly leading to lost sales opportunities and frustration among their loyal customer base.
Pain Point
Over 40% of customer inquiries were coming in after store hours, with zero response capability until the next business day.
The Solution: Intelligent Agents
XDATA deployed a custom Natural Language Processing (NLP) Chat Agent trained specifically on the retailer's historical data and live inventory feed.
Unlike basic chatbots, this agent understands context. It can check real-time stock levels at specific locations, reserve items for pickup, and answer stylistic questions using the brand's unique tone of voice.
- 24/7 Automated Responses
- Real-time POS Integration
- Seamless Human Handoff
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Implementation Process
Data Audit & Integration
Week 1
We connected to the client's existing POS API and scraped historical email/chat logs to understand common customer intents.
Model Training
Week 2-3
Fine-tuning the NLP model to recognize inventory queries, sizing questions, and return policies specific to the boutique.
Testing & Launch
Week 4
Soft launch at one location followed by full rollout. Staff were trained on how to handle escalations from the AI.
Measurable Results
Within 90 days of launch, the impact was clear. The boutique saw immediate improvements in both operational efficiency and revenue.
Satisfaction
+25%
Increase in CSAT scores from after-hours support.
Sales
+15%
Boost in online conversions via chat prompts.
Efficiency
600+
Hours of support time saved annually.