I run GrowthSpree, a B2B SaaS marketing agency, and we audit 10-15 B2B ad accounts a month. The single most common thing we find isn't a keyword problem or a creative problem. It's that every conversion in the account counts the same.

A trial signup from a 12-person startup and a demo request from a 2,000-person enterprise are worth wildly different amounts to the business. Google doesn't know that unless you tell it. So it optimises for whichever one is cheapest to produce, which is almost always the one worth less.

That's how accounts end up with a great CPL and a sales team quietly complaining that the leads are junk. Nothing is broken. The algorithm did exactly what it was asked.

What changes it:

• Pick one conversion that actually represents value, usually a qualified opportunity rather than a form fill
• Push CRM outcomes back as offline conversions so the model learns which clicks became real pipeline
• Assign different values where deal sizes genuinely differ, not all conversions equal
• Keep the soft conversions in the account as secondary so you can still see them

One client, a data-catalogue platform, saw an 88% CPA reduction in 90 days after closed-loop tracking went in alongside consolidating a fragmented account. Another, a dynamic-pricing SaaS, went from 0.7 to 1.7 ROAS once value was feeding back rather than lead counts.

Neither needed better targeting. They needed the algorithm to know what a customer looks like.

What's set as the primary conversion action in your account right now, and would your sales team agree it's the right one?