Analyzing competitors' paid ads with AI enables businesses to uncover targeting tactics, messaging priorities, and channel strategies. Using AI to analyze competitors' paid ads gives you a clear view of their strategy. You can see who they're targeting, the type of messaging they use, and where they allocate their budget. AI processes large sets of ad data to highlight patterns in timing, platforms, creatives, and offers. This makes it easier to adjust your own campaigns based on what’s working for others in your space.

Of course, this tutorial doesn't teach you how to streamline your ad strategy based on your competitors' advertising patterns. It shows you how to find those patterns and the ad spending metrics. This tutorial shows you the exact method for finding your competitors' paid ad strategies and how they utilise them to drive traffic to their websites and/or apps. We will use ChatGPT for this purpose due to its ease of access. 

By the end of this tutorial, you'll be able to:

• Collect ad data
• Extract key elements from the ad data
• Analyze performance Indicators
• Spot patterns and gaps

Let's get right into it. 

Step 1 - Collect ad data

Let's collect the ad data first. This is an important step. You can find your competitors' data on the Meta Ads library, the Google Ad Transparency Center, and the TikTok creative center. These are the free resources. Alternatively, you can use SimilarWeb, AdSpy, and BigSpy for a more structured approach and robust export options. 

To search ads on Facebook, go to Meta Ads Library. Select the country, ad type, and specify the keywords or the competitor's name. Press Enter. 

Click 'See detail' to find more data for the respective ad. 

You should focus on the ads that have been running for the longest time, as they're usually the top performers.

What I would advise to do if you're gathering data from Meta for instance, is to take screenshots of the ads, give them to ChatGPT, and ask it to extract the data into a file.

Step 2 - Extract key elements from the ad data

Before analyzing the data and extracting key elements from it, it is necessary to ensure that the data has all the information you need to make the right decisions. The following elements should be in the report:

• Headline & Body Text
• Call-to-Action (CTA)
• Ad URL or Destination
• Platform and Date Range
• Engagement metrics (likes, shares, comments if visible)
• Visuals (images, videos, screenshots)

Note: engagement metrics are usually very tough to find. 

After gathering the data, upload it to your ChatGPT using the attach feature. 

Change the ChatGPT o4 model to o3. 

Use the following prompt to extract key elements from the data. 

Prompt:
Extract the target audience, value proposition, tone, visual style, and CTA from the attached paid ad campaigns data and metadata.

Take a look at the visual style used by your competitors and the primary CTAs (Cost per Action). CTAs will give you a sneak peek into what your competitors are offering as a freebie in exchange for their emails. This insight could be valuable once you finalize your ad campaigns. 

Step 3 - Analyze performance Indicators

To analyze performance indicators for paid ad campaigns, start by focusing on the core metrics available on the platform. These include impressions (the number of times the ad was shown), clicks or click-through rate (CTR), engagement (likes, shares, and comments), and conversions, such as purchases or sign-ups. Some platforms also provide cost metrics, such as CPM (cost per thousand impressions) or CPC (cost per click), which help assess the campaign's efficiency. For competitor ads, exact conversion data may not be visible, but you can estimate performance through public engagement levels and inferred ad frequency.

Next, benchmark these indicators against industry averages to understand what qualifies as good performance. For instance, a CTR above 1.5% is often considered a solid performance, although this threshold varies by industry and platform. If an ad has high engagement but likely low conversions, it might mean the messaging resonates, but the landing page or offer needs improvement. Noting such discrepancies is useful for diagnosing weak points in the funnel.

Let's say you want to focus on Google Ads data. Ask ChatGPT to analyze impressions, click-through rates (CTR), engagements, conversions, and estimated spend.

Prompt: 

Analyze the impressions, click-through rates (CTR), engagement, conversions, and estimated spend of competitors, focusing specifically on Google Ads. I want to find out the success of their campaign and the amount of traffic they received.

The chatbot also interpreted campaign success metrics. This data provided us with a real sneak peek into the mechanics of ad spend and how it translated into traffic. 

For more in-depth estimates, export full Google Ads auction insights and analytics data, or use tools such as Semrush's "Traffic Analytics" to back-solve impressions and clicks.

Step 4 - Spot patterns and gaps

Next, identify the strengths and weaknesses of your competitors' paid ad campaigns. Instruct ChatGPT to explore high-performing formats, such as video versus carousel, and identify areas of fatigue, which occur when ads run for an extended period with declining engagement. Also, note any seasonality or timing advantages. 

Prompt:

Analyze the ad data to identify the campaign's key strengths and weaknesses. Look for high-performing formats, such as whether video ads are consistently generating more engagement than carousels or static images. Check for signs of ad fatigue by identifying campaigns that have been running for an extended period but are experiencing a decline in interactions. Also, pay attention to any timing or seasonal patterns that may be influencing performance, like spikes during holidays or end-of-quarter pushes. Summarize these insights to highlight what's working, what's losing traction, and when the ads are most effective.

The timing and seasonality insights were invaluable. It provided us with some interesting data points that could be crucial for the success of our paid ad campaigns. 

After analyzing the patterns and gaps, we concluded that short-form video and personalized InMail are the clear winners. At the same time, carousel fatigue and an underutilized YouTube presence present immediate opportunities for improvement. Refresh high-spend creatives on a 60-day cadence and align enterprise pushes with quarter-end dates to maintain high momentum and low costs.

That's it for this tutorial, folks. Remember to tweak the prompts according to your needs. The more data you provide, the deeper ChatGPT's analysis becomes. It all boils down to the art of writing prompts and extracting the most valuable insights that can catapult your business into success.