Aashwa Cabs runs local, airport and outstation taxi services across Bangalore. Search demand was there — but the account was bidding on the same generic “taxi” keywords as Ola and Uber, with no way to tell a search into a real booking. We rebuilt the account around routes people actually search for.
Booking enquiries
Return on ad spend
Cost per booking
Call-to-booking rate
Aashwa Cabs
Local & outstation taxi service
Bengaluru
3-month active management
Cab searches in Bangalore are high-volume and high-competition — generic terms like “taxi booking Bangalore” put Aashwa in a bidding war against Ola, Uber and every local operator, at a cost per click most of them couldn’t match. Calls were coming in, but nobody could say which ad, keyword or route brought them. Ad spend was flat across the whole city instead of the routes and areas where Aashwa actually had drivers and pricing edge.
of spend on generic city
wide "taxi" terms
calls tracked back to a
specific ad or keyword
flat citywide campaign
covering every route and area
Rebuilt the account around cost-per-booking, not clicks
Replaced the one citywide campaign with route-based ad groups — airport transfers, popular outstation routes, and high-demand localities — matching what people actually type when they're ready to book.
ROAS
Most bookings happen over a phone call, not a form — so we set up call tracking numbers and call-only ad formats to capture and measure the booking calls that were going untracked.
call-to-booking rate
Built a negative-keyword list from search-term reports to cut spend on driver-job searches, "free cab" queries and other clicks that were never going to book a ride.
cost/booking
Used four weeks of call and route data to move spend away from low-converting city-wide terms and into the routes and times of day that were actually turning into bookings.
bookings
More booking enquiries per month vs. baseline
Return on ad spend, up from under 2x
Average cost per booking, down from ₹120
Call-to-booking rate after tracking went live
Aashwa couldn’t out-bid Ola and Uber on generic taxi keywords — so we stopped trying. Route-specific campaigns caught riders further along in deciding, call tracking finally showed which ads were driving real bookings, and negative keywords stopped the leak.
That’s the model we build for every local service business: campaigns matched to how people actually search and book, tracked all the way to a phone call — not just a click.
That’s the model we build for every clinic client: a strong local presence backed by real reviews, paid campaigns matched to specific treatments, and every booking tracked from search to consultation — not just clicks and rankings.
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