Identify in-store display location
using AI
Below is a free classifier to identify in-store display location. Just upload your image, and our AI will predict the optimal locations for in-store displays to maximize customer engagement - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("in-store-display-location", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/in-store-display-location/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/in-store-display-location/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict the optimal locations for in-store displays to maximize customer engagement.
This pretrained image model uses a Nyckel-created dataset and has 24 labels, including At Register, Back Of Store, Bulk Display, Center Aisle, Checkout Area, Clearance Section, Cross-Merchandising Area, End Cap, Front Of Store and In Display Case.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the optimal locations for in-store displays to maximize customer engagement).
Whether you're just curious or building in-store display location detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify in-store display location at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Retail Space Optimization: This use case involves using the false image classification function to analyze in-store displays and their locations. By identifying displays that don’t align with optimal layout strategies, retailers can enhance customer flow and improve overall shopping experience.
- Product Placement Analysis: Retailers can use this function to assess the effectiveness of product placements within their store. By identifying displays that may be misclassified, businesses can make data-driven decisions to enhance visibility of key products and strategically reposition them.
- Marketing Campaign Evaluation: This function can help evaluate the success of marketing displays by identifying which ones are attracting customer attention. By analyzing foot traffic and engagement with certain displays, businesses can refine future marketing strategies and optimize promotional efforts.
- Shelf Compliance Monitoring: Retailers can ensure compliance with merchandising plans by using this function to identify misclassified display locations. This ensures that products are placed according to brand guidelines, allowing for better coordination with suppliers and adherence to visual standards.
- Dynamic Inventory Management: By leveraging the false image classification capability, retailers can track inventory levels based on the display locations. Understanding which displays are underperforming allows businesses to adjust inventory distribution effectively and cater to consumer demand.
- Seasonal Display Assessment: This use case involves evaluating seasonal or promotional displays to ensure correct classification and visibility. By identifying missed opportunities or misplaced displays, businesses can capitalize on peak selling seasons and maximize sales potential.
- Customer Experience Improvement: By analyzing in-store displays through this function, retailers can better understand customer interaction with their environment. Identifying displays that are frequently ignored or misclassified can lead to restructuring the store layout, enhancing overall customer satisfaction.