The campaign looks good but the ads aren't profitable

I started the year with an uncomfortable email from a client. If you run Google Ads, you might have had something similar.

I’ve been managing ads for a small law firm for about three months. When we started, we set a $250 target cost per lead. At that price, there was plenty of margin because their typical case was worth upwards of $5,000.

We’d hit the target almost from the beginning. In December, the cost per lead was $208. By every metric I had access to, the account was doing well. So when I opened my client's email and saw how unhappy she was, I felt ambushed.

I’d been asking her for feedback for months. Each time, the answer was that things were OK, but she was too busy to give me the detail I’d requested.

Without lead-level feedback, every lead looked the same to me. So I ended up optimising the campaign to get as many leads as possible under our target cost. And what I was doing was working. But, the client felt like the leads weren’t a good fit.

When a client is unhappy with the results, the first instinct is to jump into the ad account and start changing things:

• We check the search terms for intent.
• We add more negatives.
• We tweak ad copy or landing pages.

But without lead-level feedback, that’s not optimising, it’s guessing.

And I didn’t have lead-level feedback. She wasn’t able to tell me specifically which leads were good or bad, only that they hadn’t made as many sales as they’d hoped for.

After I explained why I needed this level of detail she promoted an assistant to “Chief Lead Reporting Officer.” I’ll work with him to backfill as much data as we can and track what happens with future leads. I’ll use this to optimise the ads for better leads, not just more leads.

The underlying cause is a data gap.

The data exists: I have data about ad performance (impressions, clicks, leads etc). The business has data about outcomes. Which enquiries turned into real cases. Which ones didn’t. How much money they made.

But this data is siloed:

• Ad data lives in Google.
• Business data lives in the office.

I’m stuck in the middle, with no practical way to combine this information into something that supports good decisions.

From what I’ve seen, this is close to a universal problem for people running Google Ads.

There are obviously some exceptions. I have clients where we’ve built robust lead tracking systems or where their CRM captures and exposes genuinely useful data. We’re feeding real business outcomes back into Google and optimising based on that feedback. In those accounts, I’m more confident and they make more money.

But these setups are expensive. They’re technically complex. And they’re hard to justify unless you’re spending hundreds of thousands per month on ads.

This puts a lot of us in an uncomfortable situation. We want to do great work. We have the skills to do great work. We care deeply about our clients. But we don’t have the information we need to make better decisions.

With better data, we’d deliver better results.

But how many clients are willing to roll out a new CRM, retrain staff, and change how their business operates just to make Google Ads easier to manage?

So we optimise with incomplete information. And sometimes we get blamed even though the campaign itself is performing well.

We need a middle layer

The problem is simpler to describe than to solve: something is missing between the ad platform and the business.

A middle layer that:

• Captures every lead.
• Preserves ad platform data about how the lead was generated.
• Records what happened to the lead inside the business.
• Feeds outcome data back to Google so optimisation is based on real business value, not just lead volume.
• Gives ad managers the information we need to make better decisions

I think that can change.

I’ve set aside the next few months to work on a way to close this gap without asking clients to rebuild their entire tech stack just to make Google Ads work properly.

If you manage accounts where you don’t have the data you wish you did, I’d really like to hear from you.

If you’re willing, reply and tell me:

• What data you’re missing.
• What you wish the data could tell you or what questions you wish it could answer.

I’ll share what I learn as I go.

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