For example, Ada had a list of custom verticals they wanted to categorise all accounts by; Ada used Kernel to build a classifier to do that much more precisely than off-the-shelf data providers.

Kernel enabled Ada to use the custom data to create an easy-to-edit account score in collaboration with reps., The score shows all the data points that contributed to the specific score for each account. This account score has become the foundation for finding new accounts, ranking accounts and personalizing outbound.

With Kernel, Ada carved new territories by splitting up accounts so that each rep would get the same number of great accounts. The Kernel account score showed that previous years’ top-performing reps had also been working the most promising account territories; the quality of their accounts drove performance. Previously, Ada had no visibility over quality that everyone trusted. Now, Ada could easily balance territories by account volume and quality, freeing up RevOps capacity for more strategic projects.

As part of the territory carving exercise, Kernel added 100,000 brand-new accounts to Ada’s CRM. They then used the Kernel data to narrow down the entire account universe via Ada-specific signals to the 15,000 best accounts and then divided those accounts among reps.

The Kernel score meant that reps knew exactly which accounts to target on the first day of the new quarter, saving reps 1-2 weeks of getting familiar with their account territory.