$33K
Additional revenue per quarter
16,600+
Total conversations handled
200+ per day
Conversations at peak volume
About the company
ALVA Auto
ALVA is one of Indonesia's fastest-growing electric motorcycle brands, with a lineup that includes the One, One XP, Cervo, and N3, covering entry-level urban commuters through to longer-range commercial riders. The N3, launched at IMOS 2024, delivers a 140km range and targets buyers making the switch from petrol. Pricing starts at around Rp 15.5 million, with battery leasing options that lower the barrier further. Every sale begins the same way: a test ride. Getting a prospect from first inquiry to confirmed test ride appointment is where most EV brands leak buyers. ALVA decided to automate that step.
The Challenge
Growing faster than your sales team can handle is a good problem. It does not feel like one when test ride requests are going unanswered.
01
Demand was outpacing the team at 200+ conversations a day.
At 200+ conversations daily, a rep-dependent model meant slower replies, inconsistent qualification, and test ride requests that expired before anyone followed up.
02
Seven models, and buyers who do not know which one they need.
A delivery rider and a daily commuter will ask the same opening question but need different bikes. Without qualification upfront, the wrong model gets recommended and a mismatched test ride does not convert.
03
The test ride is the entire conversion event.
If a prospect books and completes a test ride, the close rate is high. If they do not get a timely response to their inquiry, they consider another brand or stay with petrol.
No engagement channel
ALVA had no automated channel to reach tens of thousands of leads from prior events. Every contact required a rep.
200+ conversations/day
At peak, inbound volume exceeded what a rep-dependent model could process reliably or at speed.
No after-hours coverage
Buyers researching at midnight got no response until the next day — by which point most had moved on or were considering another brand.
No re-engagement
Leads who inquired but didn't book were never followed up. Every unbooked conversation was a permanently lost test ride.
What Covena Built: A Buyer Qualification and Test Ride Booking Agent on WhatsApp
Covena handled the build, training, and deployment end-to-end. ALVA's team did not write a single prompt.
Rider Profile Qualification Before Model Recommendation
The AI asks about daily use case, range requirements, and cargo needs before surfacing a model. A South Jakarta commuter and a Gojek delivery rider leave with different, accurate recommendations from ALVA's seven-model lineup.
Test Ride Appointment Closing
Once matched to the right model, the buyer books a test ride at the nearest ALVA showroom — location, date, and slot confirmed in the same thread. No handoff required.
After-Hours Buyer Coverage
ALVA's buyers research at midnight. The AI handles range questions, charging infrastructure, battery leasing, and model comparisons at 11:30pm with the same accuracy as 11:30am. No inquiry expires unattended.
Warm Lead Re-Engagement Sequence
Buyers who inquired but did not book receive a follow-up with a side-by-side model comparison and a renewed test ride offer. The AI tracks the thread from first contact to confirmed appointment with no rep involved.
Multi-Model Specification Q&A
Range, charging time, payload capacity, and leasing options across all seven ALVA models answered accurately — including the N3's 140km range and battery subscription options — without a rep in the thread.
The AI in Action
See how the agent qualifies a buyer, recommends the right model, and closes the test ride booking — all without a rep.
Upload image for "Daily Commuter — Model Recommendation"
How We Got to Live in 12 Weeks
Weeks 1–2
Discovery & Buyer Journey Mapping
All seven EV models documented, rider use cases mapped, test ride flow designed, and lead database audit completed with ALVA's sales team.
Weeks 3–6
Agent Build & Qualification Engine
Rider profile qualification logic, model recommendation system, and test ride booking integration built and trained on ALVA's full catalog.
Weeks 7–9
WhatsApp Integration & Lead Re-engagement Setup
Connected to ALVA's WhatsApp Business account. Warm lead re-engagement sequences configured and tested against the existing lead database.
Weeks 10–11
Testing & Calibration
Conversation testing across all seven model scenarios and edge cases. ALVA's sales team reviewed outputs for recommendation accuracy.
Week 12
Go Live & Iteration
Full inbound traffic handed to the agent, with both teams monitoring and refining in real time.
The Impact
Same team size, materially more pipeline. ALVA's reps now focus entirely on the close.
$33K
Additional Revenue per Quarter
Revenue driven through AI-handled conversations with no rep in the thread.
16,600+
Conversations Handled
Total volume managed since go-live.
200+/day
Conversations at Peak Volume
Handled consistently without adding headcount.
0
Additional Headcount Required
The lead database now runs itself.
Metric
Before
After
Scalable engagement channel
None
WhatsApp AI agent, live 24/7
Response time
No prior channel
Under 30 seconds
After-hours coverage
None
Full
Follow-up for unbooked leads
None
Automated cadence
Test ride booking process
Manual, rep-dependent
Confirmed in-thread by AI
What's Next
With qualification and test ride booking automated at the top of the funnel, ALVA's sales team focuses entirely on the close: the in-person conversation that happens after the ride. Every new model ALVA launches is immediately searchable and recommendable without retraining the sales team.
Ready to build a test ride pipeline that runs while your sales team sleeps?
See how Covena builds AI agents that qualify buyers, recommend the right product, and book appointments — at any volume, any hour.