The Era of Ad Automation: Smart Solutions for Google Ads and Meta

Navigating Performance Max, Advantage+, and automated bidding algorithms across Google Ads and Meta platforms.

Speakers: İlker Emir, Abdullah Tanıdır

23 Jul 2024

Video Transcript

⏱ 21 min read• 3,731 words

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— Welcome to ZTalks. Today, Abdullah and I are discussing automation in ads. We’ll cover smart solutions for Google Ads and Meta. I’m İlker Emir from the PPC team. I’ve been a Senior Performance Marketing Executive at ZEO'da for about 3 years. Abdullah and I have been working together for 3 years now.

— Hi, I’m Abdullah. I’ve been at ZEO'da for over 4 years. I’m a Performance Marketing Team Lead. As İlker mentioned. We’ve been building projects and working behind the scenes for about 3 years. We’ll cover Google Ads, Meta, and various automation tools today. We’ll discuss what you can achieve with them. Let’s get started, İlker.

— Sure. I want to talk about the current state of automation in advertising. Automation offers us some key benefits. I want to cover why we need it and what it actually brings to the table. First, it saves time. Repetitive tasks can really burn you out. If I’m doing the same thing over and over, I should automate it. That’s how you save time and stay efficient. We optimize our ads regularly. This happens daily, weekly, or monthly. We follow a set schedule. We turn these into rules for automation. My main goal is to automate the tasks I hate.

That is my go-to method. We have many data sources. Automation helps us with data checks. I have been using it more lately. Is this the rise of automation in advertising? Or is it just my growing need for it? I am not sure. But based on my recent experience, I am using automation a lot more.

— We must address something here. AI technology is a hot topic today. Many people are testing it and having different experiences. But 1.5 or 2 years ago, it was different. For Google Ads, we relied on scripts. We used these scripts to build automations. They made our work much easier. Along with that, CRM systems helped too. Various third-party tools also streamlined our automation tasks. Like İlker said, it saves time. It simplifies data analysis. We can automate daily routines. Setting rules for optimizations makes our lives easier.

It helps businesses of all sizes. But honestly, Google Ads scripts are a bit outdated now. We used to use them for everything. Think keyword tweaks, budget management, and bid adjustments. But there were limits. We couldn't use scripts to exclude placements in GDN. Luckily, we have better solutions for that today. Do you have any other examples regarding Google Ads scripts, İlker?

— I used them back in the day. They were simple tasks. Eventually, Google Ads and Meta introduced automated rules. They basically copied each other. I used to work this way. Then Performance Max entered our lives. It was known as a black box. We couldn't access much data. It didn't share most insights. But we could reach them via API. We still access some data this way. I have current workflows in place. My scripts are active. I keep an Excel list for high-impression keywords that don't convert. I check which platform drives the most conversions and spend in Performance Max. I constantly monitor if I need to re-optimize.

We also use third-party tools at ZEO'da. These help our team with weekly reports. They also help us detect small anomalies. I connect the Google Ads API with NATN. I analyze data to spot anomalies. I check percentage changes week-over-week. If there's a shift, I dig into other data to find the cause. It's a mini-project for generating quick reports. It's currently under construction. I'm integrating AI here too. We bounce ideas off each other often. Thanks for your support. Using third-party tools for automation is key. I'm a marketer, not a coding expert.

But with no-code tools, I can handle almost any API documentation. There's nothing I can't do once I dive in. We can pull this off easily with a little effort. I use these projects to automate tasks and analyze Performance Max campaigns. I use it all the time.

— Our main approach is imagining solutions. We ask, "How can we solve this?" We work across many sectors. A problem for one client isn't always the same for another. Clients have different campaign models and resources. Identifying the core problem is key. We look at what can be done. We decide which AI tools fit each stage. Even without AI, data feedback helps train algorithms. Take lead generation. Offline conversion has been around for a long time. Yet, many mid-to-large firms still haven't integrated it.

Look at analytics. Consent mode changed everything this year. Plus, iOS 14 privacy updates hit hard. Many clients lost significant ad data across various sectors. This caused a major issue. The algorithm couldn't collect accurate data anymore. We use third-party tools like Zapier, make.com, or NATN. We feed lead quality data back to the algorithms. This helps us filter out spam. It trains the algorithm to be smarter. We reach a much more accurate target audience this way. We started with Google Ads. I'll circle back to NATN and AI later, İlker. Meta used to rely on rules. It’s an outdated model, much like old Google Ads scripts. What are your thoughts on API integrations?

Do you have any thoughts on this?

— I’ve worked extensively with the Meta marketing API. Pulling data from Google Analytics into Looker Studio is easy. Then you look at Meta. Many people in the industry have hit this wall. Supermetrics pops up. I think Supermetrics is way too expensive. I told myself I could build it. That’s how it started. I found myself deep in the Meta marketing API. I started building community connectors for Looker Studio. I wanted to see how I could pipe data via API. It gave me a lot of trouble. I ran into so many bugs. The marketing API lets us pull tons of data. We get way more info than the standard dashboard. We can build custom automations easily. We can pull every single data point we need.

I mostly used it for reporting. I didn't use it for direct automation. But Meta's marketing API offers huge potential. There is so much we can do with APIs. I ran into a few issues, though. You usually need to store the data elsewhere first. It makes more sense to process it that way. Meta limits your requests after a certain point. You'll get throttled if you hit them too hard. This can disrupt your workflow. You might miss out on the reports you need. I've dealt with that. I also ran into a few bugs in Looker Studio. I mostly set up rules directly in the Meta dashboard.

I use them for budget controls and preventing overspend. I also manage campaign completion with total budgets. I've even set rules to kill ads if the CTR stays low for too long. I don't have much experience with Meta automation. My expertise is mostly in the marketing API and reporting.

— Rules are a huge help for campaign and budget management. We use them all the time. For example, if a campaign needs to end on a Sunday night. We just set a rule. It saves us from working off-hours. We still use them. Meta offers many use cases via their marketing API. There isn't much to tweak on that end. Here is an example. Say you run a real estate site. You can let agents promote their listings on your social media. You can automate this. Use API connections to launch ads directly from your content.

Meta uses these tools often. You can't do as many placement exclusions as in Google Ads. Unique settings are limited. We mostly exclude underperforming platforms or ad placements. We can automate that. But for audiences? Many pros will agree. Since the iOS 14 privacy updates, many audience segments feel empty. I believe accurate targeting now requires broader settings. Others may disagree, of course. Automating audience targeting is tough. But campaign management is different. Since iOS 14, Meta Pixel data is often unreliable. Using Meta API for server-side tracking is now critical for feedback.

Every scrap of data is vital for feeding the algorithm now. These small differences and automations set us apart from competitors. We use these automations to boost our campaign performance. That’s my take on Meta and Ads for now. Anything you want to add, İlker?

— Nothing to add on Google or Meta. Let’s move on to AI. Even in performance marketing, AI is our biggest focus lately. We’re constantly finding new ways to integrate it. At its simplest, AI is a huge advantage for copywriting. I honestly ask myself this sometimes. Do you feel the same? How did I even write headlines and descriptions before? I can generate them so fast now. It’s effortless. I have total control. I can spend more time on strategy. I’m producing better work in less time.

I really wonder how I managed before. It lifted a huge weight off my shoulders. I was using tools like Copilot even before LLMs went mainstream. It was incredibly helpful. The logic is the same. But it wasn't this widespread. It wasn't this public or accessible to everyone. Now, I have so many alternatives for headlines and copy. I create unique copy for every target audience. I tailor the tone for premium users or eco-friendly segments. This approach significantly boosted my CTR and ad quality scores.

It’s a huge advantage. That’s just the basics. Let’s dive into AI now.

— Many of you watching have likely used AI tools already. Agencies and brand managers have definitely experimented with AI for ad copy. It’s been a lot of trial and error. We still use them too. But we can take it a step further. We focus on automation and integration. We connect AI via NATN, Google Ads API, or Meta API. What kind of projects can we build? We’re developing tools behind the scenes. As you know, İlker, we all struggle with the same things. Ad management and optimization are constant challenges.

We handle negatives every other day. This includes keyword or placement negatives for GDN. We also block kids' channels and gaming channels on YouTube. These are basic issues we all struggle with. We use API connections and NATN integrations. We feed data to AI. We calibrate the AI correctly. It helps us automate negatives. It makes our workflow much easier. We go beyond basic ad copy generation. We push things a step further in the background. We also collaborate with our internal AI consulting department.

Do you have any ideas or apps you're developing, İlker? Want to talk about them?

— The training at ZEO sparked my interest. Yiğit and Ozan have been huge supporters. They paved a new path for me. I’m grateful for that. I have a small project in the works. The team has several projects going on. I’m currently focused on weekly reports. Every Monday morning, I check the accounts. I see what’s happening and analyze the performance. Is there an issue? Are the ads still running? Is there a payment problem? Did conversions drop? Did they spike? How are my impressions? I have to check a ton of things like this.

I check these, but I need to report them to the client. How do I report this? I have the data. I wondered how to list this for my clients. Can I automate this? At worst, the team can evaluate it. It’s easier for the team to read a summary than audit the whole account. We can look at the summary together to brainstorm what happened. I have a project for this. Where am I at? I use Google Ads API with NATN. I’m using the Google Ads API through NATN. But NATN’s Google Ads API has some limitations.

So, we send direct requests. This lets me connect to the Google Ads API to pull campaigns or data. I created an Excel sheet to list the clients I want to report on. It uses checkboxes to select who to pull. Then it grabs the classic data. It pulls impressions, clicks, CTR, and conversion rates for a quick review. It compares current data with the last seven days. It evaluates past weekly trends. It maps out a path based on these findings. I have a project for this. I built an AI persona. I assigned it a performance marketing role. It acts as an expert in data analysis and ads. Now I'm adding few-shot prompts.

I'm showing it how to write reports. I'm working on these examples now. I hope to finish this week. If I find the time, I'll wrap it up. I'm juggling a few other projects too. But I'm leaning heavily into reporting. I want to automate reporting with AI. Those extra insights are always valuable. This project is all about reports. It seems like that's the direction I need to take.

— I've seen you in client meetings. You always ask how to improve the account. You look for issues and how to fix them. It makes sense why you're so focused on reporting. Many of our client accounts can use these automated models. Take negative keywords, for example. These are patterns we can apply across many accounts. We also build custom feedback loops for clients. We offer suggestions and report issues. I’m currently developing a NATN project too. Since these projects are similar, I’m building a keyword planner using AI tools. You’ve probably looked into this. We usually deploy scalable improvements across many accounts.

Like I mentioned, we handle negative keyword optimizations. This is a standard fix we apply to many client accounts. As İlker mentioned, we’re building AI integrations for reporting. These tools flag issues and suggest actionable optimizations. I’m also building a custom keyword planner. I started with Google Ads. I plan to integrate Meta and other platforms later. It’s an upgraded version of the standard Google Ads keyword planner. You pick the language and country. Let’s take a dental clinic client as an example. They want to run ads for dental implants across major European cities. We have to segment by country and set individual budgets.

I built a custom keyword planner. You pick a country and a keyword. AI translates it for that market. It outputs a full ZEO template. It generates an Excel file. It even forecasts the entire budget. Development is ongoing. My team uses a basic version now. Soon, it will handle GDN plans too. It will add them as new tabs in the same Excel. Need YouTube ads? It will adjust the budget accordingly. We can let AI calculate the split. Or I can set the distribution manually. We are building this tool right now.

It’s a long-term project. It uses many API connections. It runs complex queries. It compiles, cleans, and interprets the data. It builds a final template for us. Only the keyword planner is live for now. There is so much more potential. We want to simplify our workflow. How can we better support our clients? How can we optimize campaigns further? AI and automation are saving us massive amounts of time. Like I said, İlker. That’s the big picture. AI has sparked so many new ideas. It showed us what is possible. We are building based on real needs.

We discuss how to feed the algorithm best. We use AI feedback and client data. The team is constantly brainstorming on this. Anything to add, İlker? That’s all from my side.

— The possibilities are endless. Time is my biggest constraint. I’m doing this to save time. Saving time lets me create new things. I’m using no-code and low-code tools now. I’ve been working with API integrations. That’s been a huge help. Advertising is a trend right now. Broad campaigns focus heavily on optimization. Think about negative keywords, lists, and anomaly tracking. There are countless variables to manage. I have a dream. I want a client to let me build an agent. Let’s have an AI manage the ads entirely. We’ll just oversee the process. I’d love to run a year-long project with an AI agent.

We’d probably win an award for it. I just need a client willing to try. This idea really excites me. Can we manage ads with full automation? There are risks, of course. But with our oversight, I think it’s doable. I don't know what you think.

— Does data accuracy in our work worry you at all, İlker? Let's talk about that.

— I've used many different models with AI. I always remember what Yiğit says. You're using the wrong prompt. AI isn't wrong. You are. I actually taught AI how to count characters using math. I explained it step-by-step. Like, A is one, B is two. It always struggled with character counts. It also struggled with sentences or math problems. But we can verify the accuracy. It's just like coding. You write the code, then you write the test. If you skip the test, you'll have problems.

We can move forward if we test it. Sure, there's always a risk of errors. Even without AI, automation carries risks. Things can break or stall. You might be late. It misses the data. It sees zero. Then it kills your top keyword. That’s a huge problem. That’s why I obsess over reports. It helps me mitigate the risk.

— In general.

— I evaluate the results as they are.

— You always need a human eye on this. We all do. Even if it’s 99% accurate. We optimize every AI query to hit absolute accuracy. We’re building a version that works for everyone. But edge cases happen. We can’t predict everything. We start with suggestions instead of direct account changes. We build tools to give us recommendations first. Then we move forward with controlled optimizations. That’s the only way. Software taught me one thing. You always need a verification step. Otherwise, we're human. We can make mistakes too. The algorithm can misinterpret things and slip up. It's a computer, after all. If we check it properly, we won't have problems.

— Yes, absolutely. I think an agent can handle this. Paired with a reviewing agent, you could build a department. To me, it feels like a pipe dream right now. Not the tech build, but dealing with clients. We mostly handle conversion tracking and budgets. We discuss profit margins and budget scaling. Clients want to know the bottom line. I don't think AI will handle that part. Yes, they might still need us for this. If clients work directly with AI, maybe. If they use agents, they can manage things together. They can manage ads, I'm sure of that. For us to transform, marketing teams must transform too.

These kinds of issues can happen. But doing things I couldn't do before feels great. When I started years ago, everything was totally different. Advertising is evolving. It goes beyond just work. LLMs and AI are spreading everywhere now. Sure, this part excites us. Advertising is shifting its shape too. It integrates with this tech every time. That really excites me. I always say this is as big as discovering electricity. Maybe not fire, but definitely as big as electricity. Its scale is becoming more obvious every day. If you don't feel it, sit down. Ask yourself: What am I doing? Where am I headed? Where is the world going? Where do I fit in? Even I feel inadequate despite my focus.

I constantly feel I need to learn more. I keep looking for new resources. If you aren't paying attention, you need to start now. AI will make your life easier, in advertising and beyond.

— We all have our anxieties. With the rise of AI, we fear losing our jobs. We are all scared of that. But as I said, AI output needs human verification. Humans must check the accuracy. Our roles are just evolving, that's all. Performance marketing departments won't be fully replaced by AI. We will always need human oversight. I wanted to share this so our audience doesn't panic.

— Actually, I like to scare people. Yiğit uses this approach too. He starts presentations with a punchy, scary AI fact. I think his method is right. I'm never quite sure either. I think PPC teams could go fully AI. Not just PPC, though. Advertising is already heavily regulated. It evolved through these constant restrictions. It used to be a wild west with no limits. It’s very restricted now. Still, the ceiling is high. There’s room for more regulation. AI is facing the same talk. The EU is worried we’re moving too fast.

There’s a political side to this. Look at China, the US, and Europe. Two sides are investing heavily in AI. One side is trying to regulate it. People wonder if they’d regulate it if they were winning. I expect more regulations here too. It feels weird being in two heavily regulated fields. But we need guardrails. Otherwise, things could get dangerous. You can just put an agent in my place.

— We’ll definitely cover these regulations and topics in future Zeotalk sessions. It gets complicated fast. We deal with our own ideas. We also face regulations from Google Ads, Meta, and other platforms. We aren't just looking for a fix. We want the best path forward. We constantly research to keep clients compliant and risk-free. It varies by industry. It’s a deep topic. We’ll cover more in future Zeotalks. Anything to add, İlker?

— No, not really. If I start, we’ll never finish. One thing leads to another. I’m already deep in regulations. I’d love a dedicated Zeotalk on this. Shoutout to the marketing team. We just added another project. Let’s wrap it up here. Thanks for listening. These are my personal experiences. I can't guarantee they are absolute truths. I hope this was helpful. I truly believe the future is headed this way. Thanks for tuning in. Thanks to Abdullah as well.

— Thanks, İlker. Thanks for joining me today. Thanks to everyone watching and listening. Subscribe to our channel for more content. Follow our podcasts too. We chat about performance marketing and other departments. We cover a lot of ground here. Follow us so you don't miss out. Thanks for tuning in. See you at the next Zeotalk.

This transcript was generated using AI speech recognition and verified against subtitle style rules.

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