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The client came to us with an existing ad account previously managed by another team and clear benchmarks: a budget of about $500 a month split across four areas — solar stations, sales department vacancies, equipment kits and heat pumps. Their goal was at least 5 stations sold every month.
Our task went beyond simply running ads. We needed to take over the account, make sense of previous reporting, build a transparent lead tracking system and, most importantly, stay focused on the client's real business results, not just pretty numbers in the ad account. The latter, as it turned out very quickly, became the main challenge of the whole project.
The first peculiarity of this case: from the very start, the client didn't give us access to their CRM and consistently didn't disclose sales or ad ROI data. In other words, we could see how much a lead cost, but couldn't directly track how many of those leads actually became customers.
Instead of working blind or insisting on the impossible, we built an alternative tracking setup: passing leads through a Telegram bot and Google Sheets, with weekly (every Monday) and monthly reporting. This gave us at least some structure when we had no direct CRM integration and none was planned.
Next came systematic work with lead generation tools. We went from an external quiz service at the start to native Meta lead forms, and in 2026 deliberately returned to a quiz funnel — it delivered higher-quality leads, not just cheaper ones.
In parallel, we weren't afraid to revise the structure of the business lines: we removed the ineffective “kits” line and launched backup power stations instead, which later became the cheapest and most stable source of leads in the entire account.
The creative approach also evolved iteratively: from static banners to video, then to real customer testimonials and, finally, to inexpensive “lead magnet” offers (for example, an inverter or panel at a symbolic price) that gave the sales team a larger volume of leads to qualify themselves.
But the real solution was the answer to the project's main barrier — the lack of visibility into lead quality. We formalized our own MQL/SQL framework (qualified lead / lead ready for a deal) and started calculating the cost of a qualified lead separately from the cost of a lead in general. This was a way to compensate for the lack of end-to-end analytics: if a client isn't ready to share deal data, the agency builds its own proxy metrics and persistently, regularly asks for feedback on lead quality. Of course, this didn't close the gap completely, but it narrowed it significantly.
The numbers show that a systematic approach works even with limited visibility. Backup power stations, launched in December 2025, quickly became the cheapest and most stable line, often under $1 per lead, and they were what pulled the account's overall cost trend down.
Solar stations remained consistently the most expensive line relative to the client's KPI (target ≤$3.15/lead): in weaker weeks the cost rose to $6.7–10, although in the best periods (August 2026) it dropped to $2.2. The total monthly budget roughly doubled over the collaboration — from $500–700 at the start to $1,100–1,350 in 2026 — and August 2026 became one of the cheapest months of the entire collaboration: 609 leads for $625, an average cost per lead of $1.02.
But the most important number isn't the cost per lead — it's lead quality. The share of leads that converted into signed contracts grew from about 2% in April 2026 to about 6% in June–August 2026. That's three times better conversion, achieved without direct CRM access purely thanks to proxy metrics and systematic work with feedback.
So a cheap lead doesn't equal a business result, and this is the most common trap in B2C niches with a long and expensive deal cycle — in our case, solar stations, heat pumps and similar products. An ad account can show an excellent cost per lead while remaining completely blind to what's actually happening at the deal stage.
When a client deliberately limits access to data, the agency has a choice: accept the uncertainty or build its own system of proxy metrics and consistently, month after month, push for transparency. We chose the second path, and that's exactly what allowed us not only to maintain a long-term relationship with the client, but also to achieve a measurable, if gradual, improvement in lead-to-deal conversion.
