How an AI SMS Chatbot Generated $865K in Revenue
An AI-powered SMS chatbot helped handle call surges, reduce abandoned calls, and generate vehicle quotes without expanding call center capacity.
At a Glance
The client needed to handle sudden call surges without increasing call center capacity. Maruti Techlabs introduced an AI-powered SMS chatbot that helped callers generate vehicle quotes through text.
Industry
Automotive
Function
Customer Communication
Solution
AI SMS Chatbot
Engagement
Chatbot Development
The Client
The client is a US-based used car selling company with a nationwide network of licensed buyers. Its platform provides sellers with instant vehicle offers using price prediction algorithms and real-time bids.
The Challenges
Call Surges Created Long Queues and Lost Opportunities
The client's cloud call center handled 5,000 to 8,000 calls daily, but peak periods created long queues that caused callers to abandon calls or seek competitors.
Call Volumes Exceeded Agent Capacity
Peak hours and seasonal spikes created more incoming calls than available agents could handle.
Long Queues Led to Abandoned Calls
Some callers waited up to 10 minutes for an available representative, increasing the likelihood of call abandonment.
Scaling Agents for Short Spikes Was Inefficient
The client needed extra capacity for only a few hours, not throughout the day.
Lost Calls Meant Lost Revenue
Call abandonment prevented potential sellers from completing the vehicle quoting process.
Keep customers engaged when call volumes spike.
Give callers an automated way to continue the vehicle quoting process without waiting for an available agent.
The Solution
Turning Overflow Calls Into Automated Conversations
Maruti Techlabs introduced an AI-powered SMS chatbot to handle callers waiting in the queue. Calls unanswered for more than two minutes triggered an IVR option that let callers continue the quoting process through SMS.
Calls waiting for more than two minutes were redirected through IVR to an SMS chatbot, helping callers continue the vehicle quoting process without waiting for an agent.
Calls waiting for more than two minutes were redirected through IVR to an SMS chatbot, helping callers continue the vehicle quoting process without waiting for an agent.
The Journey
Queues to Automated Quotes
Business Outcomes
More Quotes With Fewer Abandoned Calls
$865K Revenue Generated
The chatbot generated $865,000 in realized revenue through automated vehicle quoting.
65% Increase in Quotes
Total quotes generated increased by 65%, reaching 9,100 quotes.
14,000 Monthly Engagements
The chatbot handled 14,000 engagements per month.
500 Fewer Abandoned Calls
Monthly abandoned calls decreased by 500 as callers gained an automated alternative to waiting.
Scalable Peak-Hour Support
The chatbot helped absorb temporary call surges without requiring the client to increase call center staffing.
Conclusion
The AI chatbot gave callers an alternative to waiting in long queues, increasing engagement and helping the client convert more quoting opportunities.
Tech Stack
Turn peak call volumes into automated customer conversations
Use AI-powered SMS chatbots to handle overflow demand, reduce abandoned calls, and keep customers moving through critical workflows.
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Frequently Asked Questions
The call volume spikes were temporary and occurred mainly during peak hours and specific periods. An SMS chatbot provided additional capacity without requiring the client to maintain additional agents throughout the day.
The chatbot used NLP to recognize misspelled model names and suggest possible corrections. This helped users confirm the correct vehicle information before continuing the quote process.
The chatbot was trained to recognize common synonyms and slang terms and map them to the corresponding vehicle names. For example, it could interpret "Chevy" as "Chevrolet."
The chatbot maintained context across the conversation and identified whether the user had provided the vehicle make, model, or both. It then moved to the next required question instead of repeating information requests.
The SMS workflow required explicit user permission before the quoting conversation could begin. Users had to actively respond with "START" to initiate the process.
The IVR offered the caller an option to continue the vehicle quoting process through SMS. If the caller accepted, the call ended, and the SMS chatbot provided instructions to begin the process.
Yes. NLP and contextual understanding can help chatbots interpret variations in user responses while still following a defined conversation flow. This is especially useful when users don't provide information in the expected format.