Products & platforms / Project story
Web crawling & machine learning
At Echobot (now Leadfeeder), I developed components for web crawling and online content analysis. As part of the engineering team, I played a key role in training a neural network for text classification and the detection of sales-relevant company signals.
01 / Context
Context
At Echobot (now Leadfeeder), I developed components for web crawling and the analysis of public online content. The task was to collect and structure information from different sources and make it useful for lead detection. As part of the engineering team, I played a key role in training the neural network used for this analysis. It classified text and interpreted company information to identify signals relevant to sales.
02 / Requirements
Requirements
Online sources vary in structure and content. The crawlers needed to collect them reliably, while the analysis had to interpret their meaning to identify company and lead signals.
03 / Implementation
Implementation
My engineering work connected data collection, model training and content analysis. I also developed tools for scheduling, configuring and monitoring the crawlers. These supported recurring crawls and analysis, providing control over the processes and visibility into their operation.
04 / Outcome and project status
Outcome and project status
Our team combined web crawling with a neural network we trained to classify text and identify sales-relevant company signals. My work covered crawling and analysis components and tools for operating the crawlers. I played a key role in the team’s model training work.
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