Introduction
Recently, I returned to Nigeria after a considerable time in Ghana. While settling back in, I encountered a mundane yet surprisingly challenging task: choosing the best value data plan. Juggling conversions between Nigerian Naira and Ghanaian Cedis and comparing data values, I realized this wasn’t just a personal dilemma but a common challenge for many. Thus began my journey to create a tool not just for me but for anyone facing similar issues.
The Challenge: Navigating Complex Data Plans
The complexity of data plans often lies in their structure and pricing. Providers offer a myriad array of options – daily, weekly, monthly, and non-expiry plans, each with different data allowances and costs. Choosing the best plan isn’t just about finding the cheapest option; it’s about finding the plan that offers the best value for your specific data usage patterns.
The Solution: An Algorithm-Based Web App
To address this, I decided to develop a web application, underpinned by a simple yet effective algorithm. The core idea was to calculate the cost per megabyte for each plan and then compare them, factoring in the user’s estimated data consumption. This algorithm not only provides a straightforward comparison of different plans but also personalizes recommendations based on individual usage.
Developing the Algorithm
The algorithm evaluates each plan based on its cost efficiency – the cost per unit of data. It also considers the validity period of the plan, as daily plans might seem cheaper but are less valuable if you can’t consume all the data in time. The goal is to suggest plans where users get the most out of every Naira spent.
Translating the Algorithm into a Web Application
I chose React for the frontend and TypeScript for type safety and better developer experience. The app allows users to:
- Create categories of plans (daily, weekly, monthly, non-expiry).
- Add plans under each category, detailing cost, data allowance, and validity.
- Input their estimated monthly data usage.
- View recommendations based on their input.
Material-UI was the go-to for designing a responsive and aesthetically pleasing interface. To make it more user-friendly, especially at night, I added a dark mode toggle feature, enhancing the visual comfort of the app.
Open Sourcing the Tool
Realizing the wider applicability of this tool in different countries and contexts, I decided to open source the algorithm. This way, the community can benefit from it, contribute to its improvement, and adapt it to various needs.
Conclusion
What started as a personal project to solve my data plan dilemma has evolved into a tool with broader implications. By open sourcing the algorithm, I hope to foster community-driven enhancements, making it an ever-evolving solution for anyone looking to optimize their data plan spending.
