What is PPC monitoring?
PPC monitoring is checking your paid campaigns on a schedule for changes that need action: spend spikes, conversion drops, campaigns that stop delivering and tracking that breaks. The goal is to be proactive instead of reactive, and to spot and fix issues before clients ask or when the budget is used up.
It covers every paid channel you run, like Google Ads, Meta Ads, LinkedIn Ads and Microsoft Ads.
Here's what to watch:
| Signal | Example | Why it matters |
|---|---|---|
| Spend spike or drop | A campaign spends three times its usual daily amount | Money goes out faster than planned, or stops going out at all |
| Conversions dip | Conversions fall by half while spend stays the same | The client pays the same and gets less |
| Stalled delivery | A campaign looks set up but has zero impressions | Nothing runs, and nobody knows until the report |
| CPA or ROAS out of range | Cost per lead climbs past the client's target | The account drifts away from the client's goals |
| Tracking breaks | Add-to-cart or purchases drop to zero while ads keep running | Spend continues with no way to measure results |
| Disconnected account | An ad account's connection expires | Reports and checks run on missing data |
| Big changes across the book | Five clients' CTR drops on the same day | Often a platform change, not five separate problems |
Here's what PPC monitoring is not:
- Brand monitoring watches for competitors bidding on your brand terms. That's a different check.
- Budget pacing compares spend with a budget plan. See budget pacing for that.
- An audit is a one-off review of how an account is set up. Monitoring runs every day or week.
Manual vs. automated PPC monitoring
If you have less than 5 clients, manual PPC monitoring still makes sense. But once you grow past that stage, monitoring every client and campaign becomes a bloated job that can take over most of your week.
Platform tools can be useful here. Google Ads automated rules can change bids, budgets and ad status, or send you an email, when conditions you set are met. Google Ads scripts let you write JavaScript to query and manage accounts on a schedule. GA4 custom insights can alert you when a metric has an anomaly.
But the problem is: each one only covers one platform, and you need to set up each account by hand.
With Whatagraph IQ Agents, this problem goes away because:
- Agents work on top of your cross-channel governed data layer. Connect all your cross-channel data to Whatagraph, blend data, and normalize dimensions on one platform. Then, agents work on top of this cleaned, governed data.
- Agents are multiplayer. Build one agent and everyone on the team can use it. Conversations are also shared by default so you can collaborate with your team. Sensitive conversations can still be marked private.
Here's how manual vs. platform rules vs. agents compare.
| Manual checks | Platform rules and scripts | Monitoring software | AI agent + specialist | |
|---|---|---|---|---|
| Channels covered | Whichever ones you log into | One platform at a time | Depends on the tool | Every connected channel, per client |
| How often | When someone has time | On the rule's schedule | On the tool's schedule | On your schedule, daily or several times a day |
| Thresholds | In your head | Fixed numbers you set | Fixed or preset | Fixed or relative to each client's normal |
| What you're told | Whatever you spot | That a rule fired | That a metric crossed a line | What changed, by how much, and the likely cause |
| Who acts | The account manager | The rule, or the account manager | The account manager | The account manager, after reading the flag |
| When the owner is away | Checks stop | Rules keep running | Alerts keep coming | The agent keeps checking, and anyone on the team can read the flags |
| Typical failure | A problem found at month end | A rule that pauses the wrong campaign | Too many alerts to read | A vague brief, caught in the first week of review |
Looking for software recommendations? Check out our PPC reporting tools guide.
How do marketing agencies use AI agents to monitor PPC campaigns in Whatagraph?
Agencies use an agent to check every client's campaigns on a schedule and tell them what changed. A person then looks at the flag and decides what to do. Here's how three agencies set it up.
A Canadian paid media team: monitoring 200+ campaigns on autopilot
This team runs more than 200 campaigns for its clients. It's virtually impossible to monitor all of them and have a real grasp of what's going manually.
The paid media specialist at this team built an agent instead that:
- monitors their Google Ads accounts for conversion dips every week
- compares each campaign with the week before
- sends digests to Slack every week
A UK agency: spotting spend spikes and drops
This agency checks client accounts every week, and sometimes more often. They wanted something to do that check for them and flag anything odd.
They built an agent that looks for sudden spikes or drops in Google Ads spend. The output looked like what they expected to see.
"On a Monday morning, we'd come in and already have a breakdown of what it's found each week for each client."
A UK media agency: campaigns that never started
This agency had a problem that's hard to catch by hand. A campaign would look fully set up, and then near the end of the month they'd find it didn't actually start.
"We thought the campaign's completely set up, perfectly fine, and then... it'll get to... nearly the end of the month, and it hasn't delivered any impressions at all."
They built an agent that checks every connected ad platform each day for stalled campaigns, day-parting problems and spend without conversions, then writes a short digest. On the first run, the digest also showed a broken Meta connection that wasn't returning any data.
How to set up PPC monitoring alerts with an AI agent
Treat the first two weeks as co-creation. The agent runs the check, you read the flags, and you tighten the rules until the flags match what you'd have caught yourself.
1. Connect every channel for each client. Put each client's ad accounts in their client folder. Group accounts from the same platform into a source group, so the agent reads them as one.
2. Define your metrics once. Build CPA, ROAS and conversions as custom metrics in the Data Hub. The agent then uses the same numbers as your PPC client reports.
3. Decide what "normal" means for each client. Pick a baseline, like the last 7 days, the last 28 days or the same day last week. Then pick how big a change counts as a problem. A 20% drop means something different for a $3,000 account than for a $300,000 one.
4. Write the brief. Describe the agent to IQ Agent in plain language, or paste this:
Run every [day] at [time], in [client's time zone].
For each client in [client folder or list], compare [yesterday / the last 7 days] with [the 7 days before / the same day last week].
Flag any campaign or ad set where:
- spend is up or down more than [X]%
- conversions are down more than [Y]% while spend is steady
- there is spend but zero impressions or zero conversions for [N] days
- CPA or ROAS is outside [range]
- conversions or key events are at zero while spend continues
Also list any data source with an expired or failed connection.
Group the flags by client, most urgent first. For each flag, give the numbers, what changed and the likely cause. If you're not sure of the cause, say so.
If nothing needs attention, reply "none".
Don't pause campaigns, change budgets or edit anything. Only report.
5. Run it on one client and check the flags. Open the ad platform and compare two or three flagged numbers. Fix anything that doesn't match, like a time zone, a currency or a campaign you meant to exclude, and tell the agent to save the fix to its instructions.
6. Schedule it. Daily works for most clients. Run it several times a day for big spenders or during launches. It runs on Whatagraph's servers, so nobody has to keep a laptop open.
7. Decide where the flags go. Each run starts a conversation in Whatagraph that the whole team can see. If you've connected Slack, the agent can post the summary to a channel.
8. Keep the changes with a person. The agent reports. Your specialist pauses, edits or changes budgets in the platform.
For the account-level checks, like expired connections, the pre-made Pacing agent reviews your whole account setup and gives you a checklist. Once one client works, copy the monitoring agent and change the client folder and thresholds.
What are the benefits of PPC monitoring with AI agents?
The first benefit is finding problems sooner. The business impact comes from what that changes: less wasted spend, fewer awkward client calls, and specialists who spend their time fixing campaigns instead of looking for what's wrong.
✅ Problems found before the client finds them. A stalled campaign caught on day two is a quick fix. Caught at month end, it's a hard conversation.
✅ Every client checked, not only the biggest. Manual checks favor the largest accounts. An agent checks all of them on the same schedule.
✅ Every channel in one check. Google, Meta, LinkedIn and Microsoft are checked together, per client, instead of in four separate places.
✅ Flags that explain themselves. Each flag comes with the numbers and the likely cause, so your specialist starts from a diagnosis.
✅ A Monday summary instead of 50 logins. The team starts the week with one list of what needs attention.
✅ Checks keep running when someone's away. The agent lives in the team's workspace, so monitoring doesn't stop when one person is on leave.
✅ Numbers that match the client report. The agent reads the same governed data as your reports, so a flag and a chart use the same numbers.
Best practices for PPC monitoring
Good monitoring comes down to a few habits:
- Compare each client with their own normal. Use each client's recent history as the baseline, not one number for everyone.
- Watch results, not only spend. Track conversions and revenue next to spend and clicks. Spend can look fine while results fall.
- Split urgent from weekly. A campaign that stopped delivering needs a same-day flag. A slow drift in CTR can wait for the Monday summary.
- Send one summary per run. Group flags by client, most urgent first. Ten separate alerts get ignored. One clear list gets read.
- Tell the agent about planned changes. Launches, sales and paused products all look like problems in the data. Save them to the agent's memory so it doesn't flag them.
- Review flags for two weeks, then tune. Loosen thresholds that flag too much and tighten ones that miss real problems.
- Log what each flag led to. Note which flags led to a fix and which were noise. That tells you which checks to keep.
To decide which numbers to watch for each client, start from the goals you already track. Our KPI tracking page covers how to set them up.
What common mistakes to avoid in PPC monitoring?
1. One threshold for every client
A 20% drop is noise on a small account and a real problem on a large one. One fixed number means too many flags for some clients and missed problems for others. Set the threshold per client, or make it relative to each client's recent history.
2. Watching one platform
Alerts on paid search alone miss what happens on Meta, LinkedIn and in the analytics behind them. A tracking break often shows up as a drop in conversions on every channel at once. Check all channels together, per client.
3. Treating it as real-time
Scheduled checks can run several times a day, but not second by second. If you need to know within minutes that a website is down, use an uptime monitor. A PPC agent is for the changes you'd want to catch within hours, not seconds.
4. Flags with nowhere to land
Without Slack connected, each run starts a conversation in Whatagraph that someone has to open. If nobody opens it, the flag doesn't help. Connect Slack, or make reading the summary part of the team's morning.
5. Trusting a zero
A metric at zero can mean the campaign stopped, tracking broke or the data connection failed. Each one has a different fix. Before you act, check which it is. Ask the agent to list failed connections separately, so you can tell them apart.
6. Comparing numbers with different definitions
If the agent calculates CPA one way and your report calculates it another, the flag and the chart won't match. Define each metric once in the Data Hub and have the agent use it.
7. Letting the agent act on its own
Pausing campaigns or changing budgets through an agent depends on each platform's access rules, and a pause is a client decision anyway. Keep the agent on detect and report. Your specialist makes the change.
8. Mixing monitoring with pacing
Monitoring looks for campaigns that behave differently than normal. Pacing checks spend against a budget plan. They need different rules, so run them as separate checks.
