Dimansh: $1.73 for lead in the international employment niche

Dimansh is a company that helps citizens of Central Asian countries legally find employment in Europe and the UK.

Primary focus — men aged 20–60 who are looking for jobs abroad with guidance, guarantees, and minimal risk.

The client positions themselves as a reliable employer with a low rejection rate. Their communication is built around support, trust, and a simple application process.

The client came to us with a request to launch Google Ads campaigns — with one main goal:

Ensure a steady flow of employment leads without interruptions or account bans, even if the cost per lead would be slightly higher than average.

Before working with us, they ran ads independently, but there was no stability — accounts were getting blocked, campaigns paused, and tracking only partially worked. As a result, every pause meant a loss of traffic and time.

Our task was to build a system that would keep working despite risks and budget instability. Specifically:

• Set up stable Google Ads campaigns from scratch
• Achieve a cost per lead within $1–1.3
• Minimize downtime with backup solutions
• Gradually scale in effective countries
• Build a controlled system with no “crashes” after pauses

We knew this project couldn’t rely on standard approaches. Risks of account bans, frequent budget interruptions, and limited analytics capabilities required manual control and a flexible system that could handle pressure.

Step 1. Audit & Preparing for Unstable Conditions

• We checked the ad account, tags, and analytics — UTM parameters weren’t passed to the CRM, so the click-to-lead connection didn’t work.
• Set up manual conversion tracking via on-site events and Google Tag Manager.
• Prepared a backup ad account and payment methods in case of bans or policy violations.

Step 2. Geo Strategy: Launching with the Strongest Markets

• Reviewed past data: Kazakhstan had the lowest cost per lead ($0.8) — so we started there.
• Then gradually added Kyrgyzstan, Uzbekistan, and Tajikistan to test offer performance across regions.
• Each campaign was built separately per GEO — for more control over budgets and bids.

Step 3. Launching Initial Campaigns: Start with What Works

• Launched search campaigns first — the most predictable and stable format.

  We split them into two types:

Test campaigns — to validate hypotheses and explore new markets

Core campaigns — to scale proven solutions

• Ad copy was localized and focused on user motivation: legal work, simplicity, support, and guarantees.

Step 4. Manual Campaign Management

• Due to frequent budget pauses (7+ times per month), we avoided CPA strategies — they didn’t have time to adapt.
• We managed everything manually: adjusted bids ourselves and reviewed performance daily.
• Only after campaigns became stable, we gradually switched to “Maximize Conversions” — which cut lead costs by 50%.

Step 5. Optimization & Scaling

• Monitored traffic quality by region and allocated budgets only to stable-performing GEOs.
• Added Performance Max as a diversification tool — in case search campaigns underperformed temporarily.
• Continuously updated negative keywords, adjusted bids, and paused low-performing queries.

Despite external limitations — unstable budgets and technical challenges — we successfully launched a stable and controllable lead generation system that withstood pressure and delivered results in the very first month.

📈 Key Metrics:

• Leads generated (June 23–29): 80
• Cost per lead: $1.73
• Website conversion rate: 10.78%
• Average CPL reduction after optimization: 2×
• Budget after scaling: $50/day (up from initial $30)

💡 What’s Especially Valuable:

• We maintained efficiency even after multiple ad pauses
• Gradual transition to automated bidding (Maximize Conversions) delivered better results without CPL spikes
• Kazakhstan proved to be the strongest market — $0.80 per lead, becoming the anchor point for scaling

These results didn’t come from a “lucky bid” or a large budget — they were the result of systematic work, real-world adaptability, and continuous control of every campaign stage.

This project is a clear example of how stability can matter more than scale.

We didn’t chase flashy numbers — instead, we built a system that worked in a risky, constrained, and unpredictable environment:

• Without full analytics — but with manual tracking in place
• Without a big budget — but with smart GEO-based allocation
• Without guaranteed campaign uptime — but with a backup plan for every scenario

When campaigns were paused — we didn’t start from scratch, we had a system to return to.

When automation didn’t work — we switched to manual bidding.

When creatives weren’t available — we launched through search and adapted as we went.

This isn’t a story about loud wins — it’s about consistency, structure, and experience.

And sometimes, that’s exactly what drives long-term results — especially in industries where everything can change in a day.