KPI used by Ecommerce Companies in Business Intelligence

Keeping a tab of KPI is a very good exercise and can help entrepreneurs in understanding the current state of business and the way forward.The general KPI used by Ecommerce companies are listed below (ofcourse there could be variations and a lot will also depend on the companies business goal as well). These KPI, in different charts and tables and visualizations, can be built using any of the Business Intelligence software (BI). This blog will be talking about KPI used by Ecommerce Companies in Business Intelligence


Ecommerce KPI

Ecommerce KPI

Generic Reports are
– Average number of items per purchase
– Percentage (%) of new customers to existing customers
– Frequency of sales transactions
– Average lifetime value of customers
– Shopping cart abandonment rate
– Checkouts per cart
– Average Days to Purchase
– Order session Percentage (%)
– Average Visits to Purchase
– Coupon conversion percentage
– Cart conversion rate
– Percentage (%) of returning customers
– Percentage (%) of canceled checkouts
– Average order size

Operational reports
– Stock Week Cover: Giving information about how much units we have in stock and for how long this will last
– Rate of Stock Turns
– Stock at the COGS value
– Stock at the SRP value
– Dispatch costs per warehouses

Performance Related Reports:-
– Gross Profit
– Gross Margin Percentage (%)
– Return Rate and Return Rate Percentage (%)
– AVG Order Value
– AVG Item per order
– Traffic: number of visits or visitors, it depends what do you like to measure
– Conversion Rate = Number of Dispatched orders / Visitors
– Price Point

Helical IT Solutions

Best Practices while doing Data Migration

Data migration is one of the most common database related task. In this blog we will talk about the best practices which should be followed while doing any data migration project


Data Migration ::

It is a process of moving data from one platform to another platform. This is one of the most common task with databases with setting up of new servers, new databases, new applications, load balancing, HA etc. For a typical data migration project, for ease, any ETL tool can be used (can be open source or proprietary).


The different stages of a typical data migration project is highlighted below


Step 1: First step is taking data from the source stage (which could be ERP, flat files, any type of database etc) and putting into the database. ER model is generally not changes. At times, additional metadata information, timestamp information can be added.


Step 2: Data moved from stage 1 to stage 2 (only those columns are moved which are necessary). Filtering is applied, duplicates are removed, erroneous data is removed. All the logs should be maintained of this step.

Step 3: In this step, we should map the data from old ER model to new ER model. All actions should be logged and metadata should be transferred. Extreme caution should be taken while defining data types just to make sure that no data is rejected because of data length.

Step 4 : All data translations and calculations take place here. Data is translated to meet target system rules, implement functional requirements. Metadata and SID are maintained, all the logs and audit information should also be maintained. Data translation information is maintained in data dictionary.

A check should also be put at this stage to make sure that there is no data duplication happening, no data type error is present etc.

Step 5 : Referential integrity check to be performed to make sure that data structures are completely ready to be written to the target system.

Step 6 : This is the final step. In case if the data is to be shown to outside world in the form of any API, that is created here.


Please get in touch with us at [email protected] for any data migration or ETL project.


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