Case Study

Customized Retail Management

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Customized Retail Management

Business Background

A CRM that tracks real-time sales results, connects to customers and lets you see your foot traffic on any device.


  1. Doorcounts tracks real-time sales results connects to customers and lets you see what’s happening with your foot traffic on any device. So, you can convert foot traffic into sales and make more money.
  2. Counts all the sales, no sales and potential sales for a day, month, or year.
  3. Never miss any sales opportunity.
  4. Keeps future action on track for better customer dealing.

Major Roadblocks

Doorcounts as the name suggests. It is all about grabbing all the opportunities that are coming towards it. Basically, the main roadblock for us while working on door counts was regarding the photos that the camera clicks.

  1. How to retrieve the photo data from the camera to our own database?
  2. To fetch the photos immediately after it is being clicked.
  3. To account for the whole Sales, No sale, Potential sale.
  4. To overcome the problem of customer duplicate entries.

The Solution

So basically, to achieve the whole concept of photo fetching from the camera to our own database we came up with the following solution.

  1. When the camera setup is all done click the picture after then the picture is clicked, is directed towards the Apache server which creates the logs for each image that is captured from the camera.
  2. After then they are redirected to the ElasticBean Stalk service which handles the load of photos which are sent by the different cameras at different locations. They are now redirected toward the AWS S3 service where they are compressed (using Lamba) and managed. (In order to manage space and time for photo load on door counts)
  3. After then their compressed version of the photo link is sent to our database of Doorcounts on to the Photo staging table where we can find records for every photo that is clicked from the camera.
  4. So, after all this the photos are fetched on our door counts database and then we process them according to our needs. Now we can count the number of photos entered in our database and can separate them on basis of the store, and company.
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