Woo

How Liran Kotzer Built Woo's Automated Sourcer to $6.5M Revenue

February 28th, 2025

Founded By

Liran Kotzer

Monthly Revenue

$542K

Founders

Employees

34 (est.)

Profitable

Yes

Year Started

2015

Customer

B2B

Founded By
Liran Kotzer: Monthly Revenue
$542K: Founders
2

Employees
34 (est.): Profitable
Yes: Year Started
2015

Customer
B2B

Who is Liran Kotzer?

Liran Kotzer is the co-founder and CEO of Woo, a recruiting technology company. He and his co-founder Ami Dudu founded Woo in 2015 after running a successful recruiting agency. Liran hails from Israel, where he originally started his career and has built his expertise in leveraging data to enhance recruitment processes.

What problem does Woo solve?

Woo makes it easy for recruitment agencies to find and keep track of top candidates in their database, so they’re not always scrambling for new hires and wasting time on repetitive searches.

How did Liran come up with the idea for Woo?

Back in 2015, Liran Kotzer and Ami Dudu started Woo to tackle a significant challenge they noticed in the recruiting industry. They had previously founded a successful recruiting agency and observed that companies were losing touch with a large portion of their candidate databases, making it difficult to source qualified candidates for new roles. This gap inspired them to create a technology that would continuously engage and maintain relationships with candidates, even after initial contact.

Liran and Ami's goal was to build an automated system that could leverage machine learning to enhance and utilize existing candidate data more effectively. This led to the development of an Automated Sourcer that uses advanced algorithms to keep company databases updated and active, ensuring that potential candidates are always ready to be tapped for suitable positions. The process of building this product involved significant research and involved manually studying recruitment processes to create a machine learning-driven solution.

The challenges they faced included training the system to accurately interpret and act on vast amounts of data and ensuring the technology was seamlessly integrated into existing client systems. By continuously refining their technology with feedback from real-world usage, Woo was able to create a compelling product that addressed the recruiting inefficiencies they had experienced firsthand. The key lesson learned was the importance of understanding and solving a specific problem deeply and using technology to create scalable and sustainable solutions.

How did Liran Kotzer build the initial version of Woo?

Woo was developed by Liran Kotzer and Ami Dudu to address inefficiencies in traditional recruiting frameworks. Initially, the creation of Woo's Automated Sourcer took about three years. During this time, a team of 20 recruiters manually worked while the tech team studied their processes to incorporate machine learning-driven automation. This detailed observation allowed them to develop algorithms that adapt to a client’s ATS, ensuring data enrichment and candidate re-engagement. The tech stack primarily leverages AI and machine learning principles to handle and analyze real-time data efficiently. Building the product presented challenges, especially when integrating complex data sets and ensuring the AI could not only manage but learn from vast amounts of candidate and employer data.

What was the growth strategy for Woo and how did they scale?

Email Marketing

Woo utilizes email marketing extensively to reconnect with and engage candidates in their database. Their system is designed to send personalized emails, offering opportunities that align with the candidates' qualifications and job preferences.

Why it worked: By focusing on personalization, Woo manages to create more meaningful interactions, leading to higher engagement rates. Candidates receive relevant, timely opportunities, which enhances their experience and increases the likelihood of them responding positively. This approach resonates well because it taps into existing interests and needs of the candidates, making them feel valued and understood.

Automation and AI Technology

Woo employs an Automated Sourcer that functions around the clock to handle unlimited candidate profiles. This tool is built with machine learning capabilities to consistently update candidate information and keep the database active.

Why it worked: Automation allows Woo to maintain long-term engagement with a vast pool of candidates without human intervention. The use of AI helps predict and personalize interactions, ensuring that communication is both relevant and efficient. This results in a system that never loses touch with potential candidates, significantly increasing the chances of them being hired.

Integration with Applicant Tracking Systems (ATS)

Woo's technology integrates seamlessly with clients' ATS. This allows companies to leverage their existing data and infrastructure to manage recruitment workflows more efficiently.

Why it worked: This integration improves the utilization of internal candidate databases, reducing the need for external sourcing. By enriching and updating the data within the ATS, companies can better identify qualified candidates already in the system, making the recruitment process faster and reducing costs associated with sourcing new candidates externally.

What's the pricing strategy for Woo?

Woo employs a data-enriched, AI-powered pricing strategy, offering an automated candidate sourcer with scalable, customizable plans based on client needs, with pricing starting around $500 per month.

What were the biggest lessons learned from building Woo?

Leverage Existing Data: Woo succeeded by focusing on leveraging and enriching existing candidate databases, enabling agencies to maintain long-term relationships with talent instead of constantly searching for new leads.
Automation Is Key: By developing an Automated Sourcer, Woo demonstrated how automating repetitive tasks can enhance efficiency and free up human resources for more strategic activities, ultimately improving candidate engagement.
Curated Data Matters: The company underscored the importance of curated and accurate data as a foundation for AI tools, which can enhance recruitment processes and provide a competitive edge in the industry.
Balance Technology with Human Touch: Despite the heavy use of AI and automation, Woo emphasized maintaining a human element in recruitment, acknowledging that emotional intelligence and personal interactions are crucial in building trust with candidates.
Adapt and Evolve: Woo highlighted the need to continually adapt to industry changes, such as economic uncertainty and technological advancements, by strategically adopting technologies that align with business goals.

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