By @gpanos · 2022-02-07 12:24
In my current company we officially support 5 countries Germany, France, United Kingdom, Austria and Switzerland.
Internally we have teams of people operating each market (customer success, onboarding, operations, marketing etc).
The softwares works like that: Upon registration we track the user's location and store it.
The backoffice provides filters, metrics etc for each supported country and the logic usually: We segment the users (or any related resource) to those 5 options and we add a generic Other option. Then admins can filter by market, view metrics, export data etc.
This kinda works but has it's limitations: How to handle countries like France that officially have “sub-ordinate” countries that count to France but still have their own ISO code? Those currently are added to the Other category but the should be included in the French market. It's not always obvious what market does the resource belongs to: For example if a user from France do a booking in Germany does the booking belongs to France or Germany? Queries a lot of times are not performant because of nested relationships: For example calculate the GMV of Germany. We need to go through all orders and filter them by the purchaser country to get the result.
I know that the question probably is too specific to get answers but hopefully it can spike a conversion that can put me in the right track.
By @Avantika_1120 · 2023-04-10 06:24
It sounds like you're facing some challenges in accurately segmenting and tracking resources across different countries and regions. One potential solution to this problem is to implement a more granular system for tracking and categorizing resources based on their specific location and attributes.
For example, instead of simply assigning resources to one of five countries or an "Other" category, you could create a more detailed taxonomy that includes specific regions and sub-regions within each country. This would allow you to more accurately track resources and query data based on their precise location and other attributes.
Additionally, you could consider implementing a system for automatically assigning resources to the correct market based on more detailed location data (such as postal codes or IP addresses). This could help to reduce errors and ensure that resources are consistently categorized and tracked across different markets.
Finally, you may want to consider optimizing your database queries to improve performance and reduce the impact of nested relationships. This could involve restructuring your database schema, optimizing indexes, or implementing caching and other performance-enhancing techniques.
Overall, the key to addressing these challenges is to take a more detailed and nuanced approach to tracking and categorizing resources based on their specific location and other attributes. By doing so, you can improve accuracy, reduce errors, and ensure that your data is easily queryable and actionable.