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Data Export

You can use the data that the system has calculated and analyzed for you. For example, to correlate system shelf information with the sales information. As well as to calculate bonuses for merchandising, or to analyze distribution and logistics bottlenecks.

To use the output of the Inspector Cloud system, you would need to export it.

Export Methods

Export methods differ in degree of automation. Automatic methods are faster, and practically eliminate the human factor. But they require people who will be responsible for the system’s operation on your part.

File

We discuss in advance what data, and in what format and form you need to receive. After that, we will implement an adapter, that will take information from our database to form a file.

A link to download a file, for example in Excel format, will be periodically sent to your mail on a timer.

Via portal

The file is uploaded from the project portal in Excel format. When uploading, you can set filters, for example, by region or by retail chain. For regular data uploading, export parameters can be saved in template and the export schedule can be set up.

Via an external resource

Export to machine readable formats. The files are sent to your resource, such as an FTP server or the cloud. On our side, a robot will start on a timer. It automatically uploads files in a specified format, such as XLS, CSI or XML.

Data API

Special API. Allows you to get detailed information about all recognized products in the images, calculated indicators, time stamps, coordinates of recognized products, and other data.

The Data API allows you to track data updates. For example, view new visits, visit results and tasks. This is a convenient tool, if the visits are offline. The data and photos will be fed through when the master data is updated on the device, and the results of the visit will be updated.

We recommend using this method, as it is the most granular, complete and universal.

Intermediate database

This is a form of API, where the master data is stored in a separate database. The base has a relational structure. For example, a planogram will refer to stores, an assortment matrix will refer to a product catalog, and so on. This method allows you to customize the base logic for the needs of your project.

Data is synchronized on a schedule. We create a separate database on our side, the robot uploads data into it, and then you can use the database.