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Boosting Product Launch Success with Extensive Data Set Aggregation
Project overview
Duration
4 weeks
Technologies
- TypeScript
- Python
- Puppeteer
- Serverless
- Amazon Glue
- Amazon Athena
The project’s objective was to enable our client (under NDA) to launch a new product tailored to customer preferences and achieve a strong product-market fit. The product needed to be easily adjustable to ever-evolving customers’ needs.
Challenge
The challenge this project posed was twofold:
- First of all, it entailed a massive scope and diversity of data we needed to glean for our client,
- and second, given the fickle nature of customer preferences, identifying and tracking market fluctuations based on dynamic product configurations accurately over time, all while ensuring the configurable nature of the product was another puzzle to solve.
Our Approach
In order to address this task, we gathered a vast amount of data from various sources and preprocessed it to enable efficient data analysis and, ultimately, informative product development decisions. For this very purpose, we developed a bespoke crawler service.
Additionally, we collected and categorised all the necessary data, ensuring it was readily available for analysis and product tweaking.
Effects
Although complex, the project’s completion went smoothly, without any setbacks and delays. We delivered it in a remarkably short timeframe—merely a couple of weeks.
What’s more, the aggregated data proved to be pivotal in our client’s product fine-tuning, as well as their pricing strategy. Insights extracted from the data facilitated adjustments to align with customer preferences effectively.
Lastly, harnessing insights from data-set aggregation, our client was able to steer through the product launch with greater confidence, sidestepping numerous potential pitfalls and securing a smoother market entry in a shorter timeframe.
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