Customized Retail Management for Real Time Foot Step Tracking
Customized Retail Management for Real Time Foot Step Tracking

Business Background

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

Objectives

  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 covert 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 in track for better customer dealing.

Major Roadblocks

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

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

The Solution

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

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