One change in Google Ads — ROMI up 45 pp in 3 months

Volodymyr Petrychenko (Володимир Петриченко)

Marketer, analyst, ex-CMO focused on the Google ecosystem (Ads, Merchant Center, GA4, GTM). Google Partner. 150+ projects, 100+ positive reviews on Freelancehunt, 12+ countries.

Telegram channel YouTube Freelancehunt

• I work directly, with no account managers or subcontractors
• I measure results in sales, not in-platform conversions
• Maximum expertise in the Google ecosystem — instead of “PPC, social ads and SEO, all in one”

Where it all started

There is one scenario found in almost every reasonably serious online store. Google Ads records a conversion at checkout. But checkout is not a sale. Some orders are canceled after the manager’s call. Some are returned. Some turn out to be spam or an accidental click.

And Smart Bidding learns from all this junk data. For the algorithm, every “placed order” is equal — whether it actually closed or brought any margin at all. The result is predictable: the system chases cheap leads, not profitable customers.

That is exactly the picture I saw in this project. Technically, the ads “worked”. ROAS looked fine. But a look at the real margin made it clear that the algorithm had been optimizing in the wrong direction for years.

What we did

We built a system that sends offline conversions directly from the CRM to Google Ads. Not one event, but two separate signals:

• Actual purchase (revenue) — the confirmed amount of an order that actually happened
• Margin profit (margin) — the actual margin on the deal

Now, instead of “someone clicked a button on the website”, Google Ads gets information that the deal is closed and how much it brought. Smart Bidding relearns on real data and starts looking for exactly these customers, not just anyone.

The switch happened in April 2026.

What the numbers showed

Before and after — in one line

For every hryvnia invested, the store started earning 2.74 UAH of margin profit instead of 2.29 UAH. And note that the average monthly budget even decreased slightly. More money, lower costs. This is what proper optimization looks like.

About June — and why it matters

In June the budget was deliberately limited: spend dropped to ₴97,067 ($2.2K), the lowest level of the whole period analyzed. Margin fell proportionally, to ₴265,743 ($5.9K). But ROMI stayed at 174% — practically where it was in the best months.

The Pearson correlation coefficient between spend and margin over 7 months is r ≈ 0.71. A strong direct relationship. The system scales efficiency in proportion to the budget in both directions — up and down. This means the advertising can be managed, not just observed.

An important clarification: a correlation of 0.71 is strong but not deterministic. Roughly half of the variation in margin is explained by spend; the rest comes from seasonality, traffic mix and the human factor in lead handling. But the main point is different: after switching to real CRM data, the relationship between spend and results became predictable. And that is the foundation for scaling.

Conclusion

We did not change the campaign structure. We did not rewrite the ads. We did not increase the budget. We simply gave the algorithm true data instead of raw website orders.

The next step is a controlled budget increase and checking whether efficiency holds up when scaling.

For how results like these are presented to the client every month — orders, revenue, cancellations and conclusions — see the article on expert Google Ads reporting.

The same principle, but for businesses without a CRM — in the case on offline conversions through a web interface.

Another example of the CRM showing the real picture instead of ad account conversions: in the mattress store case, only 134 of 249 Google Ads conversions reached the CRM as orders.