Conversion Testing is used to verify zone data format will be converted into another data format so that the converted data format will be seamlessly by the application under the test appropriately. Any type of data can be converted from any form to another, for web-based application, the web pages should be of the form HTML that should agree to W3C HTML specification so that browsers which can render the page correctly.
Generally conversion testing is about showing the different content to the people who will access our website and then measuring the impact of change on your conversions and conversion rate.
Conversion testing allows us to see if the change and its impact is real or just coincidence. In essence, you want to ensure that change which has a positive effect, if we have to do this testing we need enough data which makes sure that we are seeing true results.
When we start testing, to optimise our conversions we need to make sure that we are measuring conversions. This will be achieved using Google Analytics and we want to ensure that we are measuring macro-conversion and micro –conversion.
A micro-conversion is a high value interaction, think of them as the most important things we are trying to get people to do on our website. The most common types of macro-conversions are leads and are transactions if we are selling online.
There are macros conversions, these conversions are secondary objectives they are not critical actions that we want people to perform but are still provide some values because here people are engaging with deeper actions. Consider examples like downloading PDF, watching video, commenting or logging into a members area.
Common examples of conversion testing are:
- Button Color-when we test whether blue cotton converts at higher rate than a red button.
- Background Image- For example, it tests whether background image converts at a higher rate than a normal plain image.
- Offer- For example, it tests whether free shipping of products of $40 or less, and converts 10% discount.
- Pop up- consider an example, it tests whether the pop-up converts at a higher rate rather than flyout for mobile visitors.
Levels of data conversion testing:
We have mainly two levels of testing is done like technically and business, Warm and Fuzzy testing. Technical testing checks conversion against the spaces while business testing will give business representatives the confidence when their old system will be in rest the data copied flawlessly to new system.
- Technical testing
We should start the technical test by establishing the test traceability. Once the test be written against each statement as previous to make sure test will cover all data to be converted. We should initiate this testing by establishing test traceability. There are mainly two common queries:
- Row count- These are used to compare no of records in source and target table. If the conversion is straight conversion, above queries can easily check number of rows. For example,
Run against Source Table,
Choose count(*) from [Source table] where [field1] = [a condition] [field2] = [another condition] Run against Target Table, Choose count(*) from [Target table]
This test will give us number of subset table which are to be converted and total number of rows in target table.
- Identify objects with Missing data
It tests each parent will have their corresponding child object we write the sql query following steps.
Write a query which gets the foreign key that goes back to parent table from child objects table. e.g.
where [field1] = [value1] AND [field2] = [value2] AND [field3] = [value3]
Write a query where parent table that gets all the parent_id’s that should be child object in ChildObjectTable e.g.
Choose id from parentTable where [fieldX] = [a value]