Categorizing and Prioritizing Target Accounts at Observe Inc
Observe, Inc., aims to conquer the multi-billion dollar observability market by making the troubleshooting of modern distributed applications an order of magnitude faster and, by using a modern cloud architecture, an order of magnitude cheaper. With its early market shaped by existing legacy observability tools, Observe used CloseFactor to target the exact right kind of customers that were not huge organizations but were mature enough to move towards a Kubernetes and microservices-based architecture.
Finding the Right ICP in Observability
Observe was putting in place an outbound team that could work with an early set of customers with the right level of cloud and DevOps maturity to be great incubators and design partners. Customers that were moving to cloud-native architectures and adopting DevOps and SRE functions were of interest to Observe. Very specific personas within these right size companies made for good targets to engage with.
Why Observe Chose CloseFactor
With these very precise criteria, it was difficult to use standard tools which had only firmographic information, and mostly out-of-date datasets to hone in on exactly the right companies.
Observe chose the CloseFactor team because they provided an up to date dataset at a scale that could be used to categorize accounts into exact A, B, C, and D categories for a well-defined go-to-market based on companies’ investment in newer technologies like Kubernetes and microservices, hiring for DevOps and SRE and presence of other custom indicators such as competitors that were ripe for disruption.
CloseFactor’s team helped the Observe team experiment and hone in based on custom buying indicator data pulled from various internet sources, including hiring data and initiatives corralled from persona profiles of companies that fit the critical criteria around the industry, size, and location. Within months, they were able to see the results of this structured go-to-market. These included faster progress of deals at identified high priority accounts, increased set of target personas to call on at these accounts, and rapid acceleration of their pipeline.
“CloseFactor helped us get a scalable go-to-market off the ground, much more efficiently than relying on teams of manual researchers”, says Keith Butler, CRO. “They helped us experiment with different types of buying indicators till we found the exact set that could help us grow our pipeline efficiently.”