Identify ad format type
using AI
Below is a free classifier to identify ad format type. Just upload your image, and our AI will predict what type of ad format it is - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("ad-format-type", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/ad-format-type/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_image_url"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_image_url"}' \
https://www.nyckel.com/v1/functions/ad-format-type/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict what type of ad format it is.
This pretrained image model uses a Nyckel-created dataset and has 26 labels, including App Install, Banner, Carousel, Content Recommendation, Display, Email, Floor Ad, Gamified, Horizontal and Image.
We'll also show a confidence score (the higher the number, the more confident the AI model is around what type of ad format it is).
Whether you're just curious or building ad format type detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify ad format type at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Ad Performance Optimization: This use case involves leveraging the false image classification function to analyze the effectiveness of different ad format types. Marketers can identify which formats are being falsely attributed to certain performance metrics, allowing them to optimize ad spend and improve conversion rates.
- Fraud Detection in Advertising: The function can help detect fraudulent activities by identifying images that do not align with the expected ad format type. By flagging these discrepancies, businesses can mitigate losses from deceptive practices and maintain the integrity of their advertising campaigns.
- Content Moderation for Digital Ads: Advertisers can use this function to ensure that the images used in their ad campaigns conform to the intended formats. This helps maintain brand consistency and appropriateness by automatically identifying and removing misleading or inappropriate images.
- Audience Targeting Refinement: Using false image classification, businesses can analyze how different ad formats resonate with various target demographics. This data can refine audience targeting strategies, ensuring that the right images and formats reach the right people, increasing engagement and conversion rates.
- Cross-Platform Ad Consistency: The function can assist in maintaining consistency across multiple advertising platforms by auditing images for their correct format types. This ensures that branding and messaging remain uniform, even as formats vary between platforms, enhancing brand recognition.
- A/B Testing Enhancement: By integrating false image classification into A/B testing frameworks, businesses can analyze which ad formats are producing misleading results. This allows for more accurate comparisons, aiding in making data-driven decisions about which formats to scale or retire.
- Report Generation for Stakeholders: The function can streamline the process of generating reports on ad performance by providing insights related to false classifications of image formats. Stakeholders can receive detailed analyses that inform strategy adjustments, budget allocations, and overall advertising effectiveness.