Wonderkind case

Enabling Machine Learning for the #3 fastest-growing Dutch Tech Company

 

Introduction

How much online job advertisement budget is needed to find your new PHP developer in Amsterdam, your new Sales Manager in Zwolle or even in London? This is the question Customer Success Managers of Wonderkind are facing every day. Using data of all their previous job advertisement campaigns, external API’s, machine learning and the knowledge of the Wonderkind employees, we developed the Wonderkind Predictive Learning Engine. This helps Wonderkind to reach their ultimate goal: make their complete system self-learning.


The Business – 
Being #3 in the list of fastest-growing Dutch tech companies,the scaleup Wonderkind is rapidly expanding their number of customers and online campaigns. Their promise is to reach talented people wherever they are. They use highly-targeted job ads on a variety of channels (like Youtube, Instagram or in-app advertisements) to find talent for their clients. And they do this completely automated.

The Challenge – The rapid expansion of Wonderkind required even further automation of the process where a customer can set up their job ads. Imagine a customer comes to Wonderkind and wants to hire a PHP Developer in Amsterdam or an account manager in Zwolle. Sales and customer success managers of Wonderkind need to answer one main question. Namely, how much budget do we need to deliver the right amount of talent to ultimately hire the right person? This is where we help out.

The Solution
Based on data of previous campaigns and API connections with their partners (Google, Facebook), we developed the Wonderkind Predictive Learning Engine. This engine predicts the needed budget for a new campaign, such that the required amount of leads is reached. Moreover, we set up the data science infrastructure of Wonderkind such that future data scientists are are enabled to put models in production and work more efficiently. We kickstarted the data science team of Wonderkind and helped them to reach their ultimate goal: Make their complete system self-learning.

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