Google Ads Automation Issues? What Smart Bidding Really Optimises
Google Ads automation issues
By SimplyGJ
•
Monday, February 2, 2026

Google Ads automation problems are probably to blame if your costs are going up, your results are unstable, or the quality of your leads is going down. People often get Smart Bidding wrong, but it's not broken. especially when you think about the other digital optimization strategies we offer at SimplyGJ that help paid performance match up with bigger marketing goals. This blog will explain what Google Ads automation really does, why performance drops when you switch to Smart Bidding, and how to take back control in 2026 without having to fight the algorithm.
Smart Bidding did not “kill” your performance. It exposed weak signals.

Google Ads automation does exactly what it is told. The issue is rarely the bidding system itself. The issue is the inputs feeding it.
Smart Bidding optimises for:
the conversion action you define
the quality and consistency of signals
the volume and stability of historical data
Google explicitly states that automated bidding strategies learn from historical conversion data and real-time signals to predict the likelihood of a conversion, as outlined in Google’s documentation on how Smart Bidding works.
If performance dropped after automation, the algorithm did not suddenly change priorities. It followed instructions more literally than before.
What Smart Bidding is actually optimising for

Smart Bidding does not optimise for revenue, pipeline quality, or business outcomes unless you explicitly teach it to.
By default, it optimises toward:
The easiest conversion to generate
The fastest signal feedback
The highest probability of repetition
If your conversion action is a form submission, Smart Bidding will find people who submit forms easily, not necessarily people who buy.This behaviour aligns with how Google defines conversions as success signals unless differentiated by value, as explained in Google’s guidance on using conversion values in bidding strategies.
This is the most common cause of declining lead quality after switching to automated bidding.
For broader strategic thinking about balancing automated and human-driven signals across your digital ecosystem including content performance and search visibility refer to our article on SEO vs GEO and how AI is reshaping search visibility at SimplyGJ.
The difference between conversion volume and conversion value
Many advertisers treat conversions as equal. Google does not.
If all conversions have the same value:
low-intent leads
accidental submissions
price shoppers
students or researchers
are treated as equally successful outcomes.
Smart Bidding learns patterns from these signals and scales them.
That is how automation increases volume while harming quality.
Signal loss is the hidden automation killer
Automation relies on signals. When signals degrade, optimisation degrades.
Where signal loss happens in real accounts
WhatsApp clicks not tracked
Phone calls counted inconsistently
CRM outcomes never fed back
Form spam treated as success
Multiple lead types merged into one goal
From the algorithm’s perspective, this creates noise. From the business perspective, it looks like “Smart Bidding stopped working”.
In reality, Smart Bidding is working with incomplete information.
Why manual bidding sometimes “felt” better
Manual bidding does not optimise. It enforces limits.
When accounts were manual:
Budgets were capped more tightly
Poor traffic took longer to scale
Mistakes were slower
Automation removes those friction points. It accelerates both good and bad signals.
That is why automation often appears to “break” accounts that were barely holding together before.
Algorithm goals do not equal business goals
Google Ads optimisation goals are mechanical.
The system asks:
What action should I maximise?
Under what constraints?
With what probability?
It does not ask:
Was this lead qualified?
Did this turn into revenue?
Did the salesperson follow up?
If you do not align algorithm goals with business goals, performance divergence is inevitable.
When Smart Bidding works extremely well
Automation excels under specific conditions:
high and stable conversion volume
clear intent separation
consistent lead quality
accurate conversion definitions
feedback loops from sales outcomes
In these environments, Smart Bidding often outperforms manual control.
Most SME accounts do not meet these conditions by default.
Why Performance Max amplifies the problem
Performance Max uses the same automation logic, but with fewer controls.
When signal quality is weak:
it expands into low-intent inventory
it optimises toward cheap conversions
it hides search term visibility
If Smart Bidding feels uncontrollable, Performance Max often feels opaque.
This does not make it unusable. It makes it unforgiving.
How to diagnose automation damage properly
Before switching bidding strategies again, answer these questions:
What exact conversion action is marked as Primary?
Does this conversion represent a real business win?
Are different lead qualities separated?
Is offline outcome data available?
Has intent been segmented at the campaign level?
If you cannot answer these clearly, automation is operating blind.
Fix 1: Redefine what “success” means in the account
Start by tightening conversion definitions.
Remove micro actions from Primary conversions
Separate enquiry types where possible
Track calls, WhatsApp, bookings explicitly
Exclude spam and internal submissions
This alone often stabilises Smart Bidding within weeks.
Fix 2: Segment intent before letting automation learn
Automation should optimise within intent, not across it.
High-intent search behaviour should not compete with exploratory behaviour in the same campaign.
Segment by:
brand vs non-brand
high-intent queries vs research
returning users vs new users
Automation performs better when intent context is clean.
Fix 3: Introduce value signals, not just volume
If your sales cycle allows it, import offline conversions.
Even simple signals like:
qualified lead
proposal sent
deal closed
dramatically improve optimisation quality.
When Smart Bidding learns what actually becomes revenue, behaviour changes.
Fix 4: Give automation time, but not blind trust
Smart Bidding needs learning periods. It does not need unquestioned loyalty.
Watch for:
rising cost per qualified lead
declining close rates
unstable daily spend
expansion into irrelevant queries
Automation should be supervised, not abandoned or worshipped.
Why many agencies blame Google instead of fixing the system
It is easier to say “Google changed something” than to audit:
tracking integrity
lead flow quality
CRM alignment
intent structure
Automation exposes weak foundations. It does not create them.
This is why automation failures cluster in accounts that lack end-to-end ownership.
What to expect once automation is fixed
When signals, intent, and feedback loops are aligned:
spend stabilises
lead quality improves
cost per acquisition becomes predictable
optimisation decisions become data-driven again
Automation stops feeling dangerous and starts feeling boring.
That is usually a good sign.
Conclusion
Google Ads automation did not kill your performance. It optimised exactly for what you gave it. In 2026, Smart Bidding works when conversion quality, intent structure, and feedback loops are treated as part of one system.
If you want automation that scales outcomes instead of noise, speak to SimplyGJ.
Build signals the algorithm can trust.
FAQs About Google Ads Automation Issues
Why did my results drop after switching to Smart Bidding?
Because the algorithm optimised for the easiest conversions based on your existing signals, not for business quality.
Is Smart Bidding bad for small accounts?
It struggles with low or inconsistent conversion volume. Manual control can help temporarily until signals improve.
Should I switch back to manual bidding?
Only if you are fixing signal quality at the same time. Otherwise the problem returns later.
Does Performance Max replace Search campaigns?
Not safely without strong conversion signals and clear intent segmentation.
How long does it take to fix automation performance?
Early stabilisation often appears within weeks. Strong optimisation requires consistent signals over time.