Speakers: Alberto Lambert, Product Manager, Analytics, Planhat
What does Planhat do?
Alberto Lambert: My name is Alberto and I'm Product Manager of Planhat's analytics team. Everything we do is designed to help business users convert large amounts of data to action, and power infinitely more flexible and tailored customer workflows.
What’s the role of data for customer action?
Alberto Lambert: Taking the right action at the right time requires a deep customer understanding only found in data, particularly time series data. And that's why Planhat is first and foremost a data platform built to empower business users with a 360 degree view of all their customer KPIs and interactions, the ability to build flexible no-code system queries through universal filters, and the ability to combine time series and static CRM data into real-time KPIs and dashboards converting data to insight.
What technical challenges did Planhat face?
Alberto Lambert: First, because we had to host both static and time series data in the same warehouse, we were using storage inefficiently. Given the rate at which we're scaling our customer base, we knew we had to address this to continue empowering our customers to drive action from data without facing prohibitively high costs. Second, for our dashboards to support the real-time custom filtering our customers need to extract insights on specific segments and portfolios, we had to report on both raw and aggregated datasets simultaneously. This resulted in poor performance at scale, with some dashboards taking minutes to render for our largest customers. And finally, to power the data flexibility our customers have come to expect, we were using a number of intermediate states between the raw data and its final result. Especially for big data operations, these steps led to data inconsistency and a lack of trust in our metrics.
How did Planhat overcome those challenges with Google Cloud?
Alberto Lambert: In doing so, we've managed to optimise our storage, improving cost efficiency, eliminate intermediate states and data inconsistency, and improve reporting performance at scale, with even our customers' most data intensive dashboards rendering up to 40 times faster in just a few seconds. But most importantly, this allows us to continue scaling our customer base and serving our largest enterprise customers without sacrificing the data accessibility, flexibility or actionability our customers need to drive NRR.
