A Case for Normalization: Get More From Your Data

What is the true impact of revenue operations? Go Nimbly, a RevOps consultancy, helped Watershed with a data management and quality project that will ultimately help reduce carbon emissions worldwide. Join Trevor Hussey, RevOps at Watershed, and Jen Igartua, CEO at Go Nimbly, as they walk through how data normalization can help you hit your revenue goals so you can change the world.

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“We have a strong chance of being the neck that turns the head at decarbonizing the global economy.” - Trevor Hussey

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Global temperatures are rising–and we’re the last shot at reversing that trajectory. Watershed helps enterprise companies collect and manage all of their data, then provides a report to help them make meaningful progress to reduce their carbon footprint. 

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But without data normalization, Watershed was struggling to reach the right customers. Marketing didn’t know where to focus, product couldn’t access the right data fields, and sales had to search for what they needed. Watershed chose Go Nimbly to deliver a solution that normalizes all data sources and intent signals, allowing Watershed to reach the right accounts and make a worldwide impact.

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Getting back to first principles

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“What if the most innovative work was actually a product of the simplest approach? Sometimes the best, biggest areas of change are rooted in simplicity.” - Jen Igartua

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Go Nimbly tackled the normalization of Watershed’s firmographic data, first. That meant prioritizing the most trustworthy inbound data and normalizing it in one field as one data point. Today, at Watershed, if an account is headquartered in North America, ZoomInfo is prioritized. If the account is based in Europe, Cognism data is prioritized. 

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By normalizing Watershed’s data based on straightforward, intuitive processes, Go Nimbly helped the company get back to the first principles of data normalization:  

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• Simplicity: Normalize data into one field to rule them all. Data is simplified and visible to the entire GTM team
• Multivendor: Prioritize multiple sources of information from multiple vendors, like ZoomInfo or Cognism
• Easy override: Build override capabilities. Vendor data isn’t always accurate
• Ongoing: Ensure ongoing updates from your data vendors. Company demographics are always changing
• Flexible system: Design a system that can adapt to more vendors and data points as needed
• Integrations: Connect your data and ensure it’s flowing to the right tools so every team has what they need at their fingertips 

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Tackling future projects

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“We’re able to make reps feel confident to do outbound because they have the right data.” - Jen Igartua

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A lot of companies worry that their data quality issues means that they can’t get value out of analytics. But that’s usually not the case. Analytics can help identify quality problems and give you insights into where the biggest issues are, and how to fix them. 

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Now that Watershed’s firmographic and intent data is normalized, Go Nimbly is tackling their contact level data. This new data model will even flag when people move companies, especially if they go from a customer company to a prospect company, a key buying indicator.

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Ready to normalize your data?

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“We saw data normalization as a crucial pillar in understanding our market. We’ve had productive conversations about where we can expand this year and it’s a game changer.” - Trevor Hussey

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Go Nimbly wants you to know that it’s ok to start working on your data where it currently lives. Through their guided change management process, you’ll eventually move your data around to accomplish your ideal normalization. To see Go Nimbly in action, check out the full webinar for a detailed demo. 

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