Identify an ad's mood using AI

Below is a free classifier to identify an ad's mood. Just upload your image, and our AI will predict the mood of the advertisement. - in just seconds.

an ad's mood identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("an-ad's-mood", "your_image_url", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/an-ad's-mood/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/an-ad's-mood/invoke
                

How this classifier works

To start, upload your image. Our AI tool will then predict the mood of the advertisement..

This pretrained image model uses a Nyckel-created dataset and has 20 labels, including Adventurous, Cynical, Dramatic, Emotional, Energetic, Funny, Informative, Inspirational, Introspective and Light-Hearted.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the mood of the advertisement.).

Whether you're just curious or building an ad's mood detection into your application, we hope our classifier proves helpful.

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Need to identify an ad's mood at scale?

Get API or Zapier access to this classifier for free. It's perfect for:



  • Targeted Advertising: By identifying the mood of an ad (happy, sad, angry, etc.), businesses can tailor their campaigns to better resonate with specific demographics. This helps in optimizing ad spending by ensuring that the right message reaches the right audience.

  • Content Performance Analysis: Marketers can analyze which moods correlate with higher engagement levels. By determining the effective emotional appeal of ads, companies can refine their content strategy based on real-time performance metrics.

  • Brand Mood Consistency Check: Brands can use this function to ensure that their ad campaigns maintain a consistent mood that aligns with their brand identity. This consistency fosters brand recognition and loyalty among consumers.

  • Competitive Analysis: Companies can employ the mood identifier to assess the emotional strategies used by competitors in their advertising. This insight allows businesses to differentiate their campaigns and possibly exploit gaps in competitors' emotional messaging.

  • Mood-Driven Product Launches: Before launching new products, businesses can test various ad moods to gauge consumer response. This data-driven approach enables brands to select the mood that will likely generate the most favorable reception.

  • Real-Time Mood Adjustments: During live campaigns, marketers can use the mood classification function to make real-time adjustments to ad creatives. This flexibility allows for improved relevancy, potentially boosting audience engagement on the fly.

  • Audience Segmentation Strategy: Understanding the emotional impact of different ad moods allows businesses to create more nuanced audience segments. This granular approach helps in crafting personalized messages that cater to the emotional needs and preferences of diverse consumer groups.

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