Tamilnadu, India +91 7868843405 info@sterison.com

The right solution for your success in retail execution!

Transform retail execution, fix out of stocks and grow sales. Leverage retail AI image recognition technology to get ahead.

Time for Active Selling +150%

70% of the purchasing decision is made in store, so if the consumer sees something wrong with your product, you could miss out on a huge number of sales. However, with image recognition, this isn’t a problem.

Product Visibility +10%

Retail manufacturers solve the problem of in-store visibility by relying on market research firms to conduct extensive store audits by deploying a large network of merchandisers or field agents to visit a set of stores and manually collect on-shelf data.

Data Accuracy +98%

AI may not be the new shiny object anymore, but ensuring the platform always delivers action-ready insights of the highest accuracy is paramount.

Key issues

In order to make business-critical decisions, brands need to stay always up to date on what they have in their possession, how much they have sold, what the competitors have in stock, and other essential data.
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>61%

COMPANIES NOT SATISFIED

Just 39% of manufacturers are satisfied with the quality of merchandising in stores

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~7%

AVERAGE LEVEL LOSS

7% of goods on average are missing on the shelf, which is approximately estimated at $ 600 bln in sales losses

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~30%

OFFLINE / ONLINE LOW QUALITY

The reliability of data with manual counting usually does not exceed 30%

True shelf intelligence through AI-powered image recognition and planogram compliance

Image Recognition by Sterison provides you with more objective and better quality data. However, it is all about much more than time-saving improved data collection. This is just the beginning of the IR journey!

Our IR solution helps you better and quicker assess in-store execution to get a clear picture of the POS situation.

It then allows you to go beyond simple data collection and solve the problems effectively. It suggests the most appropriate on-site actions to your field teams to help them improve a shelf reality.

With Image Recognition by Sterision, you can give your commercial teams the visual tools to negotiate better agreements with their clients. You can boost sales, minimize risks of losses, anticipate problems and be much more proactive than ever

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Ready For Demo?

Our Team will connect you shortly.
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Wonder How IR Solutions Work in Reality?

Watch Sterisons’s image recognition demo and see how it helps businesses gain higher visibility into the operations, increase facilities’ productivity and minimize instore execution process.

Watch Video
Watch Video
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Efficient Process

Capture shelf photos that transform into actionable data in real-time. Make adjustments instantly and ensure products are perfectly positioned.

Object Detection

Identify facing SKU

Analyze the empty space of the shelf

Check if the products are grouped together

Score the exhibition that is held

Identifying SKU count

Check with the price tag align with the SKU

Planogram compliance

SKU Location tracing

Reports

KPI reports (backend)

Report by channel

WTD reports

Trend reports

Coverage reports

Purity reports

Planogram reports

Mobile App & Integration API

Standalone app for collecting the training image

Providing the SDK for integrating with existing app (IR execution)

Capturing images by scene

Capturing images by door type

Image validation (blur detection)

Integration related master & transaction API

AI Image Recognition Software For Retailer

Sterison computer vision is an interdisciplinary scientific field that deals with how computers can be made to gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system

Object Detection is the process of finding real-world object instances of different products like FMCG products, Medical products, Automobile products, POSM Materials, etc… in still images or Videos. It allows for the recognition, localization, and detection of multiple objects within an image which provides us with a much better understanding of an image as a whole

High Efficiency

Inspection time per store is reduced from 8 min to 5 sec (efficiency increased by 99%) Real Data

The system automatically calculates the quantity of goods and the proportion of display without manual counting errors

No Backend Personnel

Once the photo is uploaded, the system automatically checks whether the display is qualified. No manual review is needed.

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Data Accuracy

With accurate data on product presence, share of shelves, and planogram compliance, you have the reliability you need to make smarter decisions.

Features

The Frontline user will capture the image.

The front facing product SKUs will be detected and localized.

If there are any empty spaces, then it will be detected and the front facing SKU stock is updated.

The statistics of the stock quantity gets displayed for easy reference.

Real-Time Visibility

Get a real-time overview of in-store execution and product positioning in every store.

In-store automation combined with image recognition helps retail stakeholders to gain real-time visibility into their stores by capturing just a few images iof retail shelves! Retail stakeholders can now track every SKU on a shelf across thousands of stores in any geo-location and time zones, at any given moment.

In-store automation can be achieved with two methods:

By enabling your merchandizers to capture in-store image using their mobile devices, or

By installing low form-factor-based IoT-based cameras on the retail shelves to capture images of the store shelves frequently throughout the day.

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Analyze and Improve Product Placement

Compare shelf and store performance data with sales data to understand and optimize your campaigns, product positioning and in-store execution.
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Features

Auditing shelf management using Image Recognition digitizes store checks and plays an essential role in understanding the shelf conditions and how they affect the sales of their core SKUs.

Using a deep neural network, detects SKUs within images of shelves and classifies them at manufacturer, brand or SKU level.

Such a neural network can be trained to compare and identify gaps between actual shelf image and reference planogram.

The pictures of the racks are captured one by one and then they are stitched together in a complete scene where this is compared to the planogram template and helps to detect the wrongly misplaced products.

How It Works

Image Recognition is a part of a broader strategy of retail execution that relies on smart technology. Parallel dots uses Image Recognition and Computer Vision for better and efficient planogram compliance at the stores

Take Pictures of Your Products on Store Shelves

Automatically calculate data according to your KPI’s

See real-time results and make improvements

All Your KPI's Optimized

  • Product presence
  • Number of facings
  • Share of facing
  • Share of shelf
  • Empty Space
  • Foreign SKU
  • Purity
  • Eye level positioning
  • Product Proximity
  • Counter
  • Display material
  • End of aisles
  • Promotion support
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We Always Try To Understand Users Expectation

Of course, these questions need to be tailored to your industry and product universe.

Have any question about us?

Don't hesitate to contact us

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