Exploding Growth By Sourcing Customers

Overview

Data scraping can significantly enhance lead generation by collecting and analyzing information about potential customers, their behaviors, and interests. This information allows businesses to create targeted and personalized marketing strategies that are more likely to convert leads into customers.

A single website containing a list of your target demographic can be astronomically valuable to extract.

Challenge

A promising startup in the food-delivery sector came to Atlas looking to source new leads for their company. The startup stood apart in the saturated food delivery space due to a distinctive vision - serving a frequently ignored demographic, customers with specific dietary needs. To actualize their vision, they needed to create a formidable network of restaurants that catered to specialized dietary requirements. Data scraping emerged as a key component of their strategy, offering to generate a wealth of potential leads and steer the startup toward its ambitious growth targets.

Solution Overview

Understanding Client’s Needs

The bedrock of a successful project is an in-depth understanding of the client's demands. Our partnership took off with several strategic dialogues with the startup's CEO. These talks helped us clarify their vision, the extent and ambit of their operations, and the pressing requirement for a broad and relevant set of leads geared toward their Minimum Viable Product (MVP) launch. From these conversations, we singled out a website that contained the types of leads our client was interested in (UberEats.com), as well as developed a mapping strategy for extracting the most relevant results possible.

Data Scraping

With a clear understanding of our client’s specifications, we initiated the data scraping pipeline. Our team crafted custom AtlasBots to parse through the UberEats website and extract only the most relevant pieces of information. Along with developing the bot, we wrote up internal schema diagrams, fired up AWS resources, and configured proxy servers to integrate with our extraction programs. Despite being a meticulous and lengthy process, we finally put together a raw data lake of leads that our clients aimed to sort through and use.

Data Engineering

The data extract required many rounds of processing and refining. We applied filtering techniques to separate the signal out from the noise and cleaned up the data based on a variety of parameters (restaurant category, geographical location, allergy labels, ratings, and more). This cleaning stage greatly reduced the manual burden needed to apply for the cleaning work. The result of this cleaning effort was a final list more aligned with the strategic demographic our clients had communicated to us.

Data Labeling

To maximize the value of this refined dataset, we passed the data forward to a team of data entrists to further enhance the dataset. They meticulously analyzed the output, assuring its quality as well as highlighting and labeling rows of the data that were most relevant to the client’s venture. In this scenario, this translated to eateries that had on offer menu options catering to customers with certain food sensitivities.

Report Generation

Putting everything together now, we put the data into a user-friendly, collated CSV format. This format enabled easy ingestion into the client's database making the data instantly available for their customers.

Conclusion & Next Steps

Hundreds of thousands of distinct restaurants were extracted, offering our client a comprehensive choice of potential leads. Additionally, our client could efficiently filter these leads using tags making the process of identifying restaurants aligned with their business needs much more straightforward. The most meaningful evidence of our project's success was how effectively the startup turned many of these leads into meaningful business relationships. This achievement established a solid basis for the anticipated debut of their MVP and crucially influenced their competitive stance in the food delivery world.

This project demonstrated the potency of strategic data mining and data refinement in unlocking the potential for growth. When deployed effectively, these tools can reveal exact leads that perfectly coincide with a business's unique demands, guiding it toward explosive growth.

‍