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KAZAKHSTAN · ALMATYAUTO DEALERSHIP · MULTI-BRANDGOOGLE ADS · YANDEX DIRECTCALL TRACKING2025–2026

Auto dealer: CPL down 47% and test-drive bookings up ×2.3

−47%
COST PER LEAD IN 4 MONTHS
×2.3
TEST-DRIVE BOOKINGS
+61%
QUALIFIED CALLS FROM ADS
300
CARS SYNCED INTO AD FEEDS
Car dealership: CPL −47%, test-drive bookings ×2.3
PROBLEM

Budget was leaking across generic campaigns and invisible phone calls

The dealership was spending across search campaigns that grouped dozens of models into broad ad sets, while most high-intent conversions happened by phone and never reached analytics. With 300 cars in stock changing weekly, ads often promoted outdated offers and the sales team could not tell which campaigns generated real buyers.

CPL had climbed to ₸34,000 with large swings week to week;
300 cars in stock were not connected to live ad feeds or model-level campaigns;
Over 50% of leads came by phone, but calls were not attributed to ads;
Sales saw leads in CRM, but had no source-level view of which ads sold cars.
SOLUTION · 4 MONTHS

Rebuild the account around inventory, intent and closed-loop attribution

We replaced campaign sprawl with a feed-driven structure for available cars, separated high-intent model queries from broad research traffic, and connected calls and CRM outcomes back to ad platforms. The goal was not just cheaper leads, but clear visibility into which campaigns produced booked test drives and sold vehicles.

WEEKS 1–2
Tracking and attribution base
Implemented call tracking, GA4 events, CRM source mapping and offline conversion imports so calls, forms, test-drive bookings and sales could be tied back to Google Ads and Yandex Direct.
WEEKS 3–4
Campaign rebuild by intent
Split campaigns by brand, model, used vs new, financing and dealer-intent queries; removed wasteful broad traffic and rebuilt ad copy around price, monthly payment and stock availability.
MONTHS 2–3
Feed-based inventory ads
Connected a live vehicle feed for 300 cars, launched inventory-driven ads with model, year, price and availability, and synchronized landing pages with in-stock units to reduce dead-click traffic.
MONTHS 3–4
Optimization by sales quality
Shifted bidding from raw leads to qualified calls and test-drive bookings, excluded low-value search terms, reallocated budget to top-selling models and built weekly dashboards for marketing and sales.
RESULT · 4 MONTHS

Paid traffic became measurable, cheaper and closer to actual sales

METRICBEFOREAFTERCHANGE
Cost per lead ₸34,000 ₸18,000 −47%
Test-drive bookings / month 39 90 ×2.3
Qualified calls from ads / month 74 119 +61%
Cars promoted in live feeds 0 300 NEW SYSTEM
Share of leads with source-level attribution 18% 93% +75 PP
“Before Pifagor, we knew how many leads we bought, not which ads sold cars. In 4 months, we cut CPL by 47% and finally gave sales a dashboard they trust.”
Marketing Director AUTO DEALERSHIP · ALMATY
FAQ

Frequent questions

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How do you know which ads actually sold cars, not just generated clicks?
By connecting call tracking, GA4 events and CRM outcomes back to Google Ads and Yandex Direct, including offline conversion imports for phone leads. For this Almaty dealership, that took source-level attribution from 18% of leads to 93%, so budget could shift toward campaigns producing qualified calls and test-drive bookings.
How long did it take to bring down cost per lead?
Within 4 months, cost per lead dropped 47%, from ₸34,000 to ₸18,000. Test-drive bookings more than doubled in the same period, from 39 to 90 per month, as budget shifted from broad research traffic to feed-driven, model-specific campaigns.
Does the ad rebuild need ongoing manual work, or does the feed update itself?
The vehicle feed updates automatically as stock changes, so listings and landing pages stay in sync without manual edits. What still needs regular attention is campaign optimization, reallocating budget toward top-selling models using the weekly dashboards built for marketing and sales.
What was the hardest part of fixing lead tracking for a car dealership?
Attribution was the hardest part: over half of leads came in by phone and were invisible to analytics before the project. Adding call tracking and CRM source mapping raised source-level attribution from 18% to 93% of leads.
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