Ramin Sayar is CEO of Sumo Logic, a cloud-based data analytics platform that is intended to help customers find useful patterns in their IT data in order to improve system performance, find security issues, and more. As such, he is a big proponent of the idea that there’s valuable information to be extracted from big data using advanced analytics, and has seen what it can do for customers. What’s more, he’s putting the ideas to use at Sumo Logic, to improve its own operations.
The Enterprisers Project (TEP): Businesses have always relied on data to make decisions and plan strategy. How does the advent of big data and advanced analytics change the way companies use data?
Sayar: Historically, the usage of data has been rear-view mirror focused. How did we do last quarter? What segments, geographies or territories did we sell into? The first big step many CIOs need to take in this new world of big data is figure out which initiatives they’re going to start to drive more real-time business insights. This is a great opportunity to start to leverage new methods of acquiring insights into customer churn and risk, and future predictions based on historical data, because algorithms can now start to understand past behaviors.
TEP: In what ways have you used data to your advantage at Sumo Logic?
Sayar: When I first joined Sumo Logic, I looked at our historical P&L (profit and loss), next year’s plan, looked at assumptions in the model and started asking questions around where our customers reside with respect to segment, buying decision, usage of our platform, how quickly do we spread an enterprise or mid-market account after they first become a Sumo customer.
Then our customer success organization started creating a cloud health index score for each cohort or class of customer, by quarter. We look at anomalies within in each class. We create heat maps that show us if a customer is starting to send us less or more data, or different types, or is having issues, so we can proactively respond to prevent customer churn and, more importantly, improve customer satisfaction. We proactively reach out and notify them through various means – training webinars, quick-start guides, free consulting services, real-time troubleshooting as well as in-product notifications for new features – to drive awareness, usage, and adoption.
TEP: Marketing groups are making better use of data than ever before in most companies. What are the keys to the CIO and CMO working together effectively, to ensure marketing makes the best possible use of data?
Sayar: CIOs and CMOs need to align on what the social and digital strategy is and how it plays into the data strategy. Lots of tools are out there for measuring customer intimacy. Marketing needs to use them to score leads and opportunities, and nurture them until they become sales-qualified leads. There has to be a connection with back office systems because now they tie into sales automation tools, financial tracking tools, as well as other systems. You have to be able to analyze all of those data sets. So your data scientists, data strategists, and your marketing organization all need to connect to not just your sales operations team but also with the CIO.
TEP: What other functional groups within the business have been most affected by access to more and better data, and how?
Sayar: Engineers, product and marketing folks all need to understand the level of impact the code they’re building or the services and products they’re creating have in terms of usage, adoption and feedback, whether good or bad. We have dashboards throughout our organization and share that information across development teams, marketing, sales, finance and customer success teams. It’s all about transparency. It enables us to get alignment around the types of personas we target and the use cases we build products and services for, and identify any potential issues customers may have with learning how to best leverage our platform and ultimately improve their internal alignment, usage, and service.
Equally important to tools and data strategy is how your organizational structure aligns and what sorts of processes you put in place to enable this. We see people create a data science team. That’s a good start but how do you expose that data to more than just the data scientists? How do you allow for a variety of users to deal with the levers and use the data in their day-to-day roles vs. having to ask someone else to run those reports or dashboards or create those views or analyze the data?
TEP: What’s the most unexpected benefit you’ve seen from employees having access to more data and advanced analytics?
Sayar: We’ve been able to really improve our response rate and proactiveness, not just for customer support and product engineering folks, but also sales people and presales engineers and professional services folks who have to interface with those customers. We all have the same data, we all understand the same usage patterns of specific users or sets of users and accounts. We actually now are in a position to not only be proactive but to be an advocate on behalf of users and help them in terms of guidance, and be “the trusted advisor” instead of someone trying to sell them.
