How Guru modernized their data stack to provide more value to customers
Nov 4, 2020
At Guru, we help organizations consolidate and manage knowledge so they can get the answers they need to quickly. Our main focus is capturing a company’s information and expertise — whether from internal messaging tools like Slack and Teams, the web, and employees' heads — and creating a single source of truth that’s easy for any employee to then access and use within their corporate business applications. Our goal is that with Guru, teams spend less time hunting down information and more time doing their jobs.
Unlike traditional wikis, intranets, or knowledge bases, Guru “lives where you work.” As an overlay to any web-based application, we have a unique way of understanding what knowledge is being leveraged across specific business applications. These insights are super valuable for our customers, and as such, analytics has been a core component of our product offering since our inception in 2013.
With the combination of Looker, Snowflake, and Amazon Web Services, we’ve been able to deliver our services more swiftly and efficiently than ever before, while continuing to provide a streamlined user experience.
Identifying the need for a modern data stack
Prior to implementing this stack, we relied on a legacy data platform that served as the foundation for our business model for several years. Over time, the flaws of the system began to surface, with challenges most notably around scalability, reliability, and support. Our customers are some of the fastest growing companies in the world, and the platform didn’t have the flexibility required for the growth we were experiencing.The slow turnaround times for reporting made leveraging data in daily decision making difficult to do.
Knowing our data needs had outgrown our legacy system, we made the decision in 2019 to begin looking for a data stack that would be fully in line with our philosophy and plans for growth. We believe that knowledge isn’t just information, but that knowledge can also be used to achieve positive business outcomes. And since knowledge in the form of analytics is what we deliver to our customers, we needed a solution that would enable us to deliver measurable value to our customers and provide the metrics that matter most to them.
Our key requirements
Before the evaluation phase of our search, we identified our key requirements we wanted in our data stack.
A technology stack that could provide high performance was a must-have, as we wanted to ensure our customers have the best possible experience with our platform. To fulfill the need of a highly performant data stack, we knew we needed something that could perform tasks like receiving queries from a database or running reports within a reasonable timeframe.
Another requirement we kept top of mind was concurrency. When thinking about our plans for growth alongside our commitment to customers, it was critical that whatever solution we chose would be able to scale for thousands of users while still preserving high performance. With our legacy solution, concurrency is what eventually killed the system as more users started using the platform to access data.
With all these requirements in mind, our search for a modernized data stack led us to Looker for insights and analytics, Snowflake as our data warehouse, Stitch for ETL, with everything running on Amazon Web Services (AWS). After running a proof-of-concept and being pleased with the results, we implemented the solution company-wide ourselves. Following an aggressive timeline to complete our implementation, we successfully modernized our entire data stack in less than 120 days.
Data system use and value metrics
At Guru, we primarily use Looker to provide our customers with insights about how and to what extent their Guru system is being used at their organization, along with how trustworthy the information is. Using Looker, we’re able to assess the adoption rate of Guru by looking at the number of active users measured against the number of events over time. Looker also helps our teams assess content-trustworthiness based on how current the content stays over time. And equipped with Looker dashboards, users can view what searches are producing the highest number of results or returning no results at all, ensuring that the content end users are leveraging is trusted and useful.
Internally, we use data to understand whether customers are actively using our platform on a daily basis. We watch for fluctuations in our activity and adoption metrics so that our customer support managers can proactively reach out to our customers who may benefit from some additional support or resources . Our goal is to not only help our customers find success with using Guru, but also to show — with data — that their Guru implementation rates reflect a successful adoption of the platform across their entire workforce.
Identifying issues and providing speedy solutions with Looker dashboards
Looker also helps us measure how our customers’ Guru knowledge is impacting their sales activity. With our Looker knowledge dashboard, we’re able to quickly surface insights about various search results, which helps both our Guru teams and our customers understand whether the content in Guru is proving to be useful or not.
For example, one of our customer dashboards showed that there was information in their knowledge base about a pricing tier that didn’t exist anymore, but was still live on their website. With the ability to easily identify this information and see that it was no longer valid, the customer was able to quickly make the appropriate adjustments to their knowledge base before any decisions could be affected by this misinformation.
In another instance, a customer’s support team was able to identify the correlation between the number of support tickets they received with the amount of knowledge being utilized in tickets. This analysis enabled them to verify that they had improved knowledge usage in Guru from 7% to over 60%.
Our Looker dashboards have also helped our customers better manage information regarding their business and the COVID-19 pandemic. Leveraging Looker, we’ve been able to help customer HR teams identify information gaps around company benefits and devise an action plan to help them provide their employees with more robust, detailed information when it matters most.
Looking ahead: exploring more ways to empower customers
Today, our new stack of Snowflake, Stitch and Looker has dramatically improved our ability to give our customers a clear and reliable understanding of where Guru is having an impact, and has allowed our engineering teams to focus on Guru’s core customer value while still providing best-of-breed analytics. Looking ahead, we’re already exploring ways to leverage Looker even more to offer more custom reporting based on Guru’s underlying data model. With Looker, we can offer custom reports and dashboards without needing technical support or expertise, empowering all of our customers to be focused on the outcomes Guru is delivering for their business.
Reach out to our team to learn more about embedded analytics with Looker.