A solar client's investor was willing to keep funding advertising as long as we could get solar leads for less than $25. That condition gave us room to scale the engagement to roughly $50,000 a day in advertising spend at its peak. The operation required a team to manage split tests and the supporting systems.
The relationship began with a normal solar customer. Our results led the client to bring us further into their operations, and their investor relationship changed how much advertising we could fund. We were managing acquisition with a standing cost condition rather than working through a fixed advertising allowance.
The $50K figure describes peak managed ad spend. It doesn't establish daily sales, installation value or profit.
A frozen account interrupted one of our best sources of leads
One of our best ad accounts froze for a few hours. Lead volume dipped enough that the investor started pressing the client, and the client was furious. The operation could generate leads at scale, yet a short interruption in one account still had a visible effect.
I had spread the work across multiple campaigns and accounts partly to manage risk. We could adjust a weak campaign. An unavailable account interrupted the campaigns inside it together, so campaign-level decisions couldn't address the whole problem.
Performance depends on which campaigns and tests work, but continuity also depends on whether the account carrying them stays available. Multiple campaigns can share that same dependency. Our structure gave us more places to manage performance without removing the consequences of an account freezing.
Each account covered a region, and we tested at the ad-set level
Each ad account covered a different region of the country. Campaigns within those accounts targeted different areas, demographics and cohorts. We conducted our tests at the ad-set level, below the campaign.
That hierarchy separated decisions that would otherwise get mixed together. A regional account grouped the work for that geography. Campaigns divided the audiences and areas within it. The team compared variations at the ad-set level. Looking only at a combined total would hide which part of that structure produced the result.
We also needed to compare data across the accounts. Splitting the work allowed us to operate in parallel, but it left the information in separate places. I had to bring the account data into a single interface so the team could examine the work together.
At this spend each ad account can fail on its own: one top account froze for a few hours, total leads took a massive dip, and the investor called the same day.
We combined account data with Airtable, Google Sheets and Zapier
I had a technical team supporting me by this stage. We used a mix of Airtable, Google Sheets and Zapier to aggregate the information into a single interface. It was a crude system, built around what we were willing to spend on the reporting infrastructure.
I wouldn't present that tool combination as an ideal stack to copy today. My recollection of the automation bill is mostly frustration with its cost. Reporting needs to let the people managing regional accounts compare their performance.
Spend peaked near $50K a day, then ran around $10K to $15K a day
The operation reached roughly $50,000 a day in advertising spend at peak. We later scaled it down to around $10,000 to $15,000 a day and operated in that range while the opportunity remained available.
The investor's funding made the scale possible, subject to the condition that solar leads cost less than $25. The financing opportunities behind the arrangement eventually ran out.
The daily figures don't establish a monthly total, the duration of the peak, or installation revenue and profit. A lead-cost condition explains when the investor was willing to fund advertising. Evaluating the customer's overall economics would also require evidence of what happened after those leads entered the sales process.
Regional reporting supports a more specific budget decision
We could examine each region's performance separately. A budget discussion could refer to a particular region and the campaigns and tests inside it. Aggregating the data made those separate operations available for comparison.
A region's lead cost still answers only part of an expansion decision. Consider an illustrative comparison, separate from this client's results. One region produces cheaper inquiries, but fewer of them become completed installations. Another costs more per inquiry and converts more of them into installed jobs. Lead cost alone can't settle where the next advertising dollar should go.
A service operator needs the later sales and fulfillment results beside the advertising data to make that comparison. This case establishes how we organized the advertising work. It doesn't provide the installation and margin figures needed to declare which region created the most business value.
One frozen account could interrupt several campaigns
I thought spreading the work across campaigns and accounts was a sensible way to manage risk. The freeze showed me the limit of that thinking. We also had to manage performance and exposure at the account level, where an interruption could affect several campaigns together.
A team expanding this kind of operation should be able to identify which account carries each important source of leads. Regional reporting then has another use: it helps distinguish a performance decline in a test from an interruption affecting an account. Those situations call for different responses.
Our best-performing work could still become unavailable. The investment decision has to allow for that possibility alongside the lead-cost condition, particularly where an investor expects acquisition to keep running.
This structure suits regional services that already close deals
This engagement is relevant to solar providers and other regional services that already close deals and are deciding where to expand. It has less to offer a business still trying to establish whether its offer sells at all. The starting point here was an existing customer relationship that earned a larger operating role.
My recommendation is to make the expansion decision specific enough to inspect. Name the region receiving the budget, the condition under which funding continues, and the people responsible for comparing the tests. Establish whether the sales and installation teams can handle the resulting work. That last question is a requirement for the next operation, not a measured outcome I can claim from this one.
The investor's willingness to fund inexpensive leads opened the opportunity. Anyone applying this case should also identify what happens when that willingness, the financing behind it, or an important ad account becomes unavailable. An expansion plan needs an answer before it depends on any of them.