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Cut 30% of ad waste with these 5 automations (+ free scripts)
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Feb 26, 202614 min read

Get 5 proven ad automation workflows to cut wasted spend, protect budget, and save hours each week. Practical scripts and guardrails for paid media teams.

Cut 30% of ad waste with these 5 automations (+ free scripts)

Advanced PPC strategies

Automation in paid media gets talked about like it’s a magic switch. Turn it on, step back, let the algorithms do the work.

Sounds great, but that’s not how it plays out in real accounts.

In our latest webinar, Silvio Perez - founder of AdConversion and ad automation platform Sami.bot - broke down what automation actually looks like inside high-spend B2B accounts. Not the hype around automation - but the actual workflows, the guardrails, and the rules that stop budget leaking quietly in the background.

Here’s the headline stat that set the tone:

50% of your campaigns will fail in the launch phase. Another 25% will die in maintenance.

That’s not a creative problem, or even a targeting problem.

It’s an optimization lifecycle problem.

Most accounts don’t struggle because marketers don’t know what to do. They struggle because there isn’t a system enforcing those decisions consistently, every hour, across every campaign.

And that’s where automation comes in! (When done correctly, of course).

This post breaks down the five automations Silvio uses across $40m+ in managed ad spend - and the specific scripts you can use today to implement them yourself.

Keep reading for the full breakdown, or watch the full session with Silvio here for additional tips and context when it comes to ad automation:

Timestamps:

0:00 - Intro
03:52 - [Poll] Which LLM for PPC in 2026?
06:25 - Session agenda
10:02 - Intro to ad automation: Why campaigns fail
11:20 - The optimization lifecycle
15:58 - How to approach ad automation
19:30 - How to build your own ad automation
22:00 - Automation 1: Budget protection
19:26 - Automation 2: Non-performers
37:10 - Automation 3: Ad scheduling
41:50 - Automation 4: Ongoing maintenance
47:28 - Automation 5: Critical alerts
50:12 - Bonus scripts & resources
51:30 - When automation optimizes against wrong signals
55:08 - Introducing ad automation safely
57:37 - Q&A with Silvio Perez

Automation starts with the optimization lifecycle

Before you automate anything, you need to understand how campaigns actually live and die.

Silvio frames it in three phases:

  • Launch
  • Maintenance
  • Scale

Every campaign moves through this cycle repeatedly.

The launch phase

This is where most campaigns fail.

You launch six campaigns. You let them spend enough to generate statistically meaningful data. Half of them will likely fail before they ever produce a conversion at your target CPA.

For example:

If your acceptable CPL is $500, then your launch threshold might be $500 in spend. If a campaign spends $501 without converting, it’s failed your criteria.

Not “underperforming”, just failed.

But most teams let it run to $700. $900. $1,200+.

That gap between your threshold and reality is waste.

The maintenance phase

Now let’s say three of those six campaigns survive.

Maintenance is where you’re protecting performance. You’re watching CPA, ROAS, conversion rate. You’re making incremental adjustments.

This is where another 25% of campaigns die.

Not because they were bad initially, but because performance drifts and nobody acts fast enough.

The scale phase

The survivors get scaled. Budgets increase. Bids increase. Impression share expands.

Then they cycle back into maintenance again.

The key point: launch isn’t a one-time event. It’s a loop.

And if you’re running 50, 100, 200 campaigns across Google, LinkedIn, Meta and YouTube, that loop becomes operationally heavy.

This is where automation earns its place.

But, there’s a catch:

Define your logic before you automate anything

When automation fails, it’s rarely because the tool is broken.

It’s because the logic wasn’t clear.

Silvio calls this “undocumented logic” - the hidden decision-making rules inside your head that never get written down.

Every time you log into Google Ads and:

  • Increase a budget
  • Pause an ad
  • Adjust a bid
  • Kill a keyword

You’re applying a rule.

The problem is that rule usually isn’t documented. It’s instinct.

Automation forces you to make that logic explicit.

What undocumented logic causes

When you automate without defined thresholds, three things happen:

  1. Conflicting automations
  2. Over-optimisation
  3. Platforms “learning” the wrong thing

For example:

If your target CPL is $500 but you haven’t defined what “too high” actually means, does automation pause at $550? $650? $800?

If you don’t decide upfront, the system can’t decide for you.

And worse, if you’re feeding platform algorithms inconsistent signals - pausing and unpausing manually, changing goals reactively - you train the platform to optimise toward noise.

Silvio’s recommendation is simple: Write down your optimization logic before touching automation.

That includes:

  • Target KPI (CPL, CPA, ROAS, cost per SQL)
  • Minimum data threshold (spend or conversions required before action)
  • Maximum acceptable variance
  • What action should be taken (pause, reduce budget, alert only)
  • Whether human approval is required

Think of it as building your own algorithm.

Because that’s exactly what you’re doing.

Automation doesn’t replace thinking. It amplifies it.

Once that logic is clear, you can apply it consistently.

And that’s where the five high-impact automations come in.

Automation #1: Budget protection

If you only implement one automation, make it this one.

Budget protection isn’t about growth. It’s about preventing silent waste.

Seemingly every performance marketer has a story about overspending:

  • Campaign pacing drifts
  • Google overdelivers against daily budgets
  • PMax chews through spend on low-quality placements
  • End of month arrives and you’re scrambling to pause campaigns

By the time you spot the issue, the money is gone.

Silvio’s view is that this automation acts as insurance.

What budget protection solves:

  1. Overdelivery beyond daily limits
  2. Monthly pacing running ahead of plan
  3. Spend concentrated in low-quality placements or search terms
  4. Human error

And critically, it removes anxiety.

Instead of manually checking accounts several times a day, automation checks hourly.

The scripts to use

If you’re running Google Ads, these scripts are strong starting points:

Here’s how that plays out in practice.

Example: monthly pacing guardrails

Let’s say you manage a $50,000/month Google Ads account.

You can set up automation that:

  • Sends an alert at 80% of monthly spend
  • Automatically pauses campaigns at 100%
  • Resets the next month

Now compare two scenarios:

Manual monitoring

You check the account twice a day. It overspends by 8% before you notice. That’s $4,000 gone.

Automated pacing

The system checks hourly, campaigns pause within minutes of hitting threshold, and overspend is negligible.

Multiply that across five accounts.

Why this matters in B2B

In B2B paid search, especially on Google, wasted spend isn’t always obvious.

Invalid traffic rates on Google Search average around 5%. That sounds small. But on $3m annual spend, that’s six figures of potential waste.

And that’s before you account for:

  • Irrelevant search terms
  • Poor placements
  • Duplicate targeting across campaign types

Budget protection automation gives you visibility and control before losses compound.

It won’t make your campaigns more creative, or fix yourmessaging.

But it will stop money leaking quietly while you’re focused elsewhere.

And that’s the foundation every performance marketer needs before moving into deeper optimization.

 

Automation #2: Kill non-performers without emotion

This is where most of the 30% waste lives.

Not in dramatic blow-ups, or in catastrophic overspend.

But instead in the slow bleed of ads, keywords and products that just don’t work - but never quite get paused.

Silvio calls this out directly in his post on “pausing ads that burn cash” . The issue isn’t that marketers can’t spot bad performance. It’s that we hesitate.

We get attached to the copy.

We want more data.

We tell ourselves it’s “just a temporary dip”.

Automation removes that hesitation.

The math:

Let's go back to the $500 CPL example.

If your launch rule is:

'Spend $500. If no conversion, pause.'

Then every dollar spent beyond $500 without a conversion is wasted against your own criteria.

The same logic applies in maintenance:

If your acceptable CPL is $500 and performance drifts to $700, that $200 delta isn’t “optimization time”, it’s leakage.

Now multiply that across:

  • 50 keywords
  • 20 ads
  • 6 campaigns
  • 3 platforms

This is where the spillage adds up.

Campaign averages hide the problem

One of the biggest mistakes we see in B2B accounts is campaign-level decision making.

Example:

Campaign CPA = $620.

Target CPA = $500.

At campaign level, it looks like everything is slightly off.

But when you drill down:

  • 2 ads are driving conversions at $420
  • 4 ads are driving nothing

Those underperforming ads are inflating the average and starving the winners of budget.

Automation at the ad or keyword level fixes this.

Scripts to implement now

When it comes to Google Ads, these are practical starting points:

These don’t replace strategy, but rather enforce hygiene.

For example:

Set a rule:

If CTR < 0.8% and impressions > 1,000 → pause.

Or:

If spend > 2x target CPL with zero conversions → pause.

You can also run alert-only versions if you want human approval before action.

The key is consistency - and remembering that emotion doesn’t scale, but rules do.

Automation #3: Smarter ad scheduling

“You’re not the same person at 3AM as you are at 9AM. Neither are your prospects.”

Most B2B accounts still run ads 24/7.

Not because it’s optimal. Because it’s easy.

If you’re working with a constrained budget - which most B2B marketers are - spreading spend evenly across low-intent hours dilutes impact.

The consolidation effect

Let’s say you have:

$3,000/month budget

30 days

That’s $100/day.

Now remove 10 historically low-performing days.

Same budget across 20 days → $150/day.

You’ve just increased daily firepower by 50% without increasing spend.

Now narrow further:

If performance data shows strong conversion rates between 8am–6pm, why fund midnight clicks?

Concentrating budget increases:

  • Auction competitiveness
  • Impression share during high-intent windows
  • Conversion density

When Smart Bidding is enough

Google’s Smart Bidding does account for time-of-day performance, but that doesn’t mean you shouldn’t sanity-check it.

A simple workflow:

  1. Export hourly performance data
  2. Feed into an LLM
  3. Ask for pattern detection
  4. Compare high and low intent windows

We’ve created an ad scheduling prompt to get you started, but feel free to have a play around with this and modify your own to suit your needs.

If you see clear peaks and troughs, test schedule restrictions in a controlled way.

Start small:

  • Apply to one campaign
  • Or test in one region
  • Monitor impact on CPA and volume

And remember that ad scheduling isn’t about micromanagement, but rather about making sure your limited budget works hardest where intent is strongest.

Automation #4: Ongoing maintenance without the grunt work

Maintenance is unglamorous, but it’s where accounts either stay healthy or decay slowly.

Negative keywords, broken URLs, quality score drift, structural conflicts…

These aren’t growth levers, but they are hygiene factors.

But neglect them and performance deteriorates quietly.

The scripts that save time

Key maintenance automation scripts:

These do three important things:

1. Prevent irrelevant spend
2. Surface structural issues early
3. Free up hours per week

If you’re manually reviewing search terms every Friday afternoon, that’s time you’re not:

  • Reviewing funnel progression
  • Analysing pipeline quality
  • Testing new creative
  • Challenging positioning

Automation handles the repetitive checks, while you focus on commercial impact.

Silvio made an important point in the webinar:

If you’re an agency, telling clients “we check accounts regularly” isn’t compelling - but telling them “your campaigns are checked hourly, 24/7” is.

Automation #5: Critical alerts (without too much noise)

Automated alerts can be incredibly useful, but most accounts tend to overdo them.

If Slack is pinging every 10 minutes, you’ll probably just ignore it.

The rule Silvio uses is simple:

Will my behaviour change if I receive this alert?

If the answer is no, don’t automate it.

The alerts that matter

High-value alert examples:

  • Impressions = 0 in last 24 hours
  • CPA spike > 50% over baseline
  • Frequency high + CTR dropping (ad fatigue)
  • Ad disapprovals

Relevant scripts include:

Concrete example:

If your highest-spend search campaign stops serving for 24 hours, that’s not a metric issue. That’s pipeline loss.

On the other hand, a 3% CTR fluctuation likely doesn’t warrant a Slack panic.

Alerts should trigger action, not anxiety.

When platform automation learns the wrong lesson

Here’s the uncomfortable truth.

Platforms get paid whether you win or not.

As campaigns become more automated - PMax, Advantage+, AI Max - control decreases and signal quality becomes critical.

If you feed the algorithm junk, it scales junk.

In B2B, this often shows up as:

  • Cheap leads from PMax
  • Form fills that never progress
  • Bot or spam submissions
  • Inflated perceived performance

The system sees low CPL and doubles down.

But if those leads never become MQLs or revenue, the algorithm is optimising toward the wrong outcome.

As automation increases, clean signals matter more.

If 5-8% of your traffic is invalid, that distortion compounds at scale.

That’s why platform automation should be paired with:

  • Clear offline conversion tracking
  • CRM-integrated optimisation
  • Traffic quality monitoring

Automation without clean inputs amplifies inefficiency.

How to introduce automation safely

If you’ve ever turned on automation and watched CPA spike, you know the fear.

The solution isn’t to avoid automation. It’s to control it.

Guardrails to implement

  1. Set caps:
    • Minimum and maximum bids
    • Budget ceilings
    • Acceptable CPA ranges

  2. Start at ad level
    Campaign-level pausing can reset learning. Ad-level changes are often safer.

  3. Use human-in-the-loop
    Alert first. Auto-approve later once you trust the rule.

  4. Test incrementally
    Roll out in one region or one campaign before scaling account-wide.

Automation should feel like support, not surrender.

What to automate more (and less) in 2026

If you want to make the biggest impact immediately, automate:

  • Budget caps and pacing
  • Non-performer pauses
  • Negative keyword hygiene
  • Critical alerts

These are operational tasks. They’re rules-based.

Keep human oversight on:

  • Creative direction
  • Messaging strategy
  • Audience positioning

Automation is strongest where the logic is fixed, and humans are strongest where context matters.

Final thoughts

The here goal isn’t to replace marketers - not even close. It’s to remove the repetitive decisions that dilute focus.

When budget protection, non-performer pausing and hygiene checks run automatically, you free up time for what actually moves pipeline. Stuff like:

  • Sharper messaging
  • Better offers
  • Smarter scaling decisions

That’s how you save 5+ hours a week.

And in many accounts, that’s how you cut 30% of silent waste, too.

If you want the scripts and resources referenced throughout this article, they’re all available under the header below.

And if you’re running increasingly automated campaign types like PMax or Advantage+, make sure the signals you’re feeding them are clean.

Because automation doesn’t create efficiency on its own.

It enforces whatever logic (and data) you give it.

Looking to scale your automation across all major ad platforms? Be sure to check out Sami - Silvio's all-in-one ad automation platform.

Scripts, documents, links, & resources mentioned in the session:

 

 

 

 

 

 

 

 

 
avatar
Ben Harris
Ben is a digital marketer and content writer who enjoys music, hiking, and looking suspiciously similar to Ed Sheeran.

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