4 Use Cases of AI Marketing Analytics to Boost PPC Campaign Performance

There are a lot of moving pieces to PPC campaigns. 

On the one hand, you need to research for keywords, write content, and stay on top of what competitors are doing. 

On the other hand, you need to create performance reports for clients, monitor campaigns, and adjust bids constantly.

Through this all, it’s easy for low-performing campaigns to slip through the cracks and eat up your ad spend without much returns to show for. 

That’s where AI marketing analytics comes in. It can:

✅ Identify high-impact keywords faster

✅ Generate and refine ad copy variations effortlessly

✅ Automate monitoring and deliver key insights from all your PPC data in seconds

Below, we dive into exactly how AI can not only improve PPC campaign performance but also save you valuable time.

Use Case 1: AI for Keyword Planning 

Keyword research is the backbone of PPC campaigns, but it’s also one of the most time-consuming parts of paid advertising. 

AI marketing analytics tools eliminate guesswork by analyzing massive datasets and surfacing high-impact keywords that align with user intent.

As Brooke Osmundson, Director of Growth Marketing at Smith Micro Software, wrote in her Search Engine Journal article: AI-driven keyword research is about making keyword planning more effective by surfacing insights humans might miss.

Here are all the ways she says AI can help in keyword planning:

1. Identifying new keyword opportunities

AI scans millions of search queries to detect emerging trends and long-tail opportunities. It also predicts user intent, helping advertisers bid on the most valuable terms.

💡 Example prompt for identifying new keywords:

“You’re a Google Ads manager and your client is [client name], [type of product/company]. Please provide an extensive list of all the keywords you would recommend bidding on in Google Ad keyword auctions. Please reference their website for this research: [website link]”

Prompt from ElectricKite, creative marketing agency

2. Expanding existing keyword lists

AI finds synonyms, variations, and semantic keyword matches to expand keyword coverage without broadening targeting too much.

💡 Example prompt for keyword expansion:
“Generate a list of long-tail PPC keywords based on ‘best running shoes for beginners.’ Include variations that focus on performance, comfort, and durability.”

3. Optimizing negative keywords

AI analyzes historical search queries and flags irrelevant traffic, preventing wasted ad spend. It also fine-tunes exclusions to avoid blocking high-value searches.

💡 Example prompt for negative keyword optimization:

“Analyze my PPC campaign data and suggest negative keywords that are draining budget but not converting.” [upload your PPC data as CSV or PDF]

4. Analyzing competitor keywords and predicting trends

AI scans competitor PPC campaigns to find high-performing keywords they’re bidding on. It also:

Monitors bidding shifts and ad copy trends to help you stay ahead of competitors Predicts seasonal changes in search behavior so you can adjust your strategy before trends peak

💡 Example prompt for competitor insights:
“Analyze the top PPC keywords my competitor [Brand X] is bidding on and suggest ways I can counter-strategize.”

Use Case 2: AI for Dynamic Content Generation

Ad copy can make or break your PPC campaign. But creating compelling ad copy, and different variations of it, is extremely time-consuming.

This is where AI comes in.

AI tools can generate multiple versions of headlines, descriptions, and visuals, then test them in real-time across different audience segments. 

The best part is—AI models are continuously learning which ad copy elements drive the highest engagement and conversions. This makes sure that every ad iteration outperforms the last (in theory). 

“We’re doing content experimentation with AI that no human could ever have the time to execute. Suppose we want to test 20 versions of a LinkedIn Ad headline; in seconds, AI can write those, and we run them all at once,” says Peter Lewis, Founder and CEO at Strategic Pete, a marketing consultancy agency. 

But the quality of your prompts matter here. As Braveen Kumar writes for Foreplay, an end-to-end ad workflow software, in this article, the key to getting high-quality output is to:

Give specific copy parameters Ask for multiple generations to choose from Provide context via custom instructions or in the prompt itself

He shares a simple prompt to get several copy variations for the same campaign:

Prompt 💬

You are a Facebook ad copy expert. [Brand/website] sells [product] that [list value props]. I’m running a [campaign/promotion type] targeting [target audience]. My brand voice is [list 3 adjectives]. Write the copy for 5 Facebook ad variations for my target audience using this copy template: Headline (max 40 characters), Primary text (125-300 characters), Description (max 30 characters).

Example 🤖

You are a Facebook ads expert. Lushbakes.biz sells bespoke, artisanal cakes that are handcrafted and customizable for any occasion. I’m running a Valentine’s Day promotion targeting couples who want to make their day extra special. My brand voice is romantic, cute, warm. Generate 5 Facebook ad copy variations for my target audience using this copy template: Headline (max 40 characters), Primary text (125-300 characters), Description (max 30 characters).

It’s also important to note that AI writes to the algorithm, not to your specific audience. Peter advises that this is where your copywriters should take over and refine the best-performing versions to sound like a person—not a bot. 

James Targett, Creative Project Manager at StackAdapt also shares the same sentiment in this article. 

“We can produce 50 headlines as quickly as we could historically produce one,” he says. “That’s really beneficial, but we always want a human involved to curate and refine the best ones.”

So, the takeaway is: use AI to come up with different variations for ad copy but have your copywriters refine the best versions for your target audience. 

Use Case 3: AI for Performance Monitoring

Tracking PPC performance is a full-time job. Marketers juggle multiple campaigns across different platforms, each with its own set of metrics and reporting structures. 

To understand what’s working and what’s not, agencies often spend 4-5 hours a week manually compiling data—exporting reports, formatting spreadsheets, and trying to find actionable insights before they become outdated.

But AI removes the bottlenecks in PPC performance monitoring by automating data collection, analysis, and reporting. 

Instead of waiting for human input, AI continuously tracks key performance indicators (KPIs), detecting anomalies, and flagging underperforming campaigns so you can take action quickly.

But in order for AI to monitor performance, it first needs to have cleaned, standardized, and accurate data from all your campaigns on all PPC channels. Without this, AI won’t be able to do much. 

This is where marketing intelligence platforms like Whatagraph come in. On Whatagraph, you can:

Connect: Bring in data from all your PPC channels and sources in one place. Whatagraph’s integrations are fully-managed and direct, so they’re stable and your data is always accurate.  Organize: Blend data, standardize names, create custom metrics and dimensions, change currencies, and more without writing any codes.  Report: Visualize your data using drag-and-drop widgets or ready-made templates. Create white-labeled reports with custom logos, domains, and color schemes. Share them with clients as live links, PDFs, Excel spreadsheets, or automated emails.  Monitor: See all your KPIs and trends on one dashboard, and slice and dice data by client, campaign, Account Manager, or more. Ask AI anything about your campaign performance and get actionable insights. Add AI summaries to your reports (and edit them!).

For instance, Kim Strickland, Digital Marketing Specialist at Peak Seven saved 63 hours on reporting thanks to Whatagraph. She uses it for:

Monitoring campaign performance across all channels and clients Identifying KPIs that are trending up and down Sharing performance summaries and insights with Account Executives so everyone is aligned before client meetings

She says, “Whatagraph has helped everyone on our team get on the same page about clients, what’s important, and how to talk to them. It’s now our Bible—both for clients and internal teams.”

Use Case 4: AI for Campaign Insights and Summaries 

Marketers managing PPC campaigns have access to tons of data, but that data is only as valuable as the insights extracted from it. 

But most PPC reports are loaded with raw numbers—click-through rates, conversion rates, cost-per-click, ROAS—but they don’t always tell a clear story about what’s working, what’s failing, and what to do next.

AI bridges the gap between data and decision-making by automatically analyzing PPC performance, detecting patterns, and providing clear recommendations on what to tweak for better results and writing out summaries for clients. 

For instance, on Whatagraph, you can use AI Summaries and the AI Chatbot to quickly understand campaign performance without digging through spreadsheets. Here’s how each works:

1. AI Chatbot

This is like your personal ChatGPT trained specifically on your cross-channel marketing data. 

Instead of manually digging through reports to find answers, you can simply ask the chatbot anything about your marketing performance, and it will pull insights instantly.

How It Works

Ask a question: Click on the AI Chatbot icon and type in any performance-related query. Specify your data source & date range: Tell the chatbot which campaign(s) you’re analyzing (e.g., Google Ads, Meta Ads) and over what time frame. Get instant answers: AI scans the relevant campaign data and delivers insights in a clear, easy-to-digest format—whether as numbers, tables, or short summaries.

Refine & explore: If you need more details, you can ask follow-up questions, and the chatbot will remember your previous query for better context.

2. AI summaries

Writing out performance summaries on your client reports can take up hours, especially if you have dozens of clients.

Whatagraph’s AI Summaries take that burden off your plate by automatically generating clear, structured insights based on your campaign data. 

Instead of spending hours manually summarizing what’s working, what’s not, and what to do next, AI writes customized, editable summaries in seconds—so you can focus on strategy instead of reporting.

How it works:

Insert the AI text widget: Add the text widget to your Whatagraph report. Click “Generate AI Summary” : The AI scans campaign data from your selected date range. Choose your summary type: Select which insights to include, such as performance highlights, challenges, or recommendations. Customize if needed: The AI-generated text is fully editable, so you can tweak the wording before finalizing.

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Both of these AI marketing analytics features can help you:

✅ Save hours of manual work per week: No more digging through reports or spreadsheets to find your next best step. 

✅ Achieve consistent reporting quality: Every client gets structured, professional insights without variation.

✅ Make the right decisions faster: You and your team can now easily identify performance issues and opportunities on the spot and adjust your campaigns right away. Fast action means you’re not wasting ad spend and squeezing the most out of it.

Final Thoughts

AI isn’t here to replace marketers but it’s here to make it easier to manage and monitor PPC campaigns. 

At the end of the day, AI doesn’t run successful campaigns. Humans do. But with the right tools, you can save time, make better decisions (faster), and get the most out of your ad dollars. 

Want to learn more about how to implement AI successfully at your agency? Grab a copy of our AI Playbook for Agencies.