Three dealership AI journeys in one experience: convert enquiries into test-drive opportunities, simplify service-booking requests, and identify exchange or upgrade opportunities from existing and new customers.
The automation starts after an enquiry arrives—where response delays, inconsistent qualification and missed follow-ups can create leakage.
Start a conversation when the enquiry is received instead of waiting for manual first contact.
Capture vehicle interest, purchase timeline, finance, exchange and preferred location.
Create a structured lead summary so the sales team knows whom to call and why.
Switch between Sales, Service and Exchange. As you answer, watch the operational card on the right build in real time.
Use third-party examples as market context—not as DigiMarketMoz client results. Replace these cards with your own verified pilot data once available.
A third-party published case study describes an automotive dealership network using automation around lead response, qualification and test-drive conversion.
Important: third-party example. Results and dealership identity must be independently verified before quoting specific performance numbers in a client presentation.
Automotive AI providers in Mumbai market conversational agents for enquiry handling, lead qualification and test-drive scheduling—showing a clear local use case for this category.
This is market context, not a DGM performance claim. Pilot KPIs should establish the business case using the dealership's own baseline.
First response, FAQs, qualification, reminders and structured data capture.
Consultation, vehicle experience, negotiation, finance, exchange and closing.
Response visibility, lead prioritisation, pending actions and conversion analysis.
Start with one location, one agreed lead source and one conversion objective: qualified test-drive opportunities.