Ever since my doctoral studies (and probably even earlier) I have been excited about everything data. And what data could be more exciting or vital or insightful than customer data? So it should come as no surprise that a lot of folks like me end up in the broad area of consumer data. However, after 6+ years, I came to realize that all I was doing was moving data between disparate systems: what we call “data plumbing.” 


Many companies are trying to simplify data plumbing. The space is huge and populated by dozens of companies from ETL vendors (including next-gen ETL or remove-ETL vendors) to data management companies such as Informatica, as well as API management vendors such as MuleSoft. If we look specifically at customer event data (real-time events generated by customer interactions) the available solutions in the market fall into three categories:


  • Customer Data Infrastructure: Companies such as Segment and mParticle are great for moving event data into multiple tools (like Google Analytics). But they are mostly designed for medium-size businesses and lack the extensibility necessary in an enterprise. Furthermore, their lack of security and privacy protections often make them a non-starter for enterprises that are sensitive about sharing consumer data with 3rd party vendors.
  • Customer Data Platforms: These include companies like ActionIQ and TreasureData. They have a lot of bells and whistles but they are designed for narrow use cases in marketing and sales. They have very limited extensibility and power beyond those functions. Not all companies are e-commerce but most traditional CDPs were built with the e-commerce retailer in mind.  
  • Open Source Solutions: Companies sometimes piece together their own event stacks using Kafka or Kinesis streaming engines, or they might adopt a service like Snowplow.  These methods are helpful to address the problem of event collection, but collection is just the first stage of the process. The events also have to be analyzed and acted upon, which involves sending the data to multiple destinations.


There has to be a better way. The idea of a single platform that can address the diverse needs of varied functional teams across business domains might seem like a pipe dream. 

But we at Rudder are confident that we can find a way to help companies manage, filter and interpret their data and then deploy it across diverse systems in an open and secure way that protects data privacy. 


When we began working with data a decade ago when “Big Data” was not even a term. Now it is an essential topic on every businessperson’s lips. Rudder is the culmination of our experience, and we couldn’t be more excited to get to work.