Once a year, RevOps and sales leaders sit down, analyze their historical data in their CRM, and build out sales territories for the next fiscal year. Most of the time, these new territories lead to ownership disputes, unworked ICP accounts, long sales cycles, and even slows down new reps on ramp.
ThoughtSpot, a technographics intelligence layer that sits on top of cloud data warehouses, decided to automate the data analysis for their territory planning using Tray.io. The results? Increased rep efficiency, improved trust, and timely sales engagement.
“Using automation, you can say to a regional director, here are the 6 reps that report to you, here are the aggregate scores of their patches, and show the RD that the playing field is level.” -Brendon Ritz
Territory building relies on two elements, fit and timing. Fit includes traditional account planning and territory planning components, like your ICP, ideal demographics, and firmographics. Timing is all about intent and interest; these signals typically come through product usage and marketing activity.
At ThoughtSpot, their ICP accounts are segmented into 3 buckets: named/strategic accounts, commercial, and enterprise. Accounts with less than 1,000 employees belong to commercial and accounts with over 1,000 employees fall into enterprise.
Even though ThoughtSpot had multiple data sources feeding into the data warehouse, their sales team mostly relied on LinkedIn as the most up-to-date data source on employee size. When it comes to allocating accounts to the right segments, LinkedIn often clashes with CRM data.
In total, ThoughtSpot has 26 different vendors sending through data and 160,000 accounts in Salesforce. One vendor may report that an account has 900 employees, another between 500-1000 employees, and a third says there are less than 1000 employees.
Ensuring that the data was accurately reflected on a monthly basis in the different multi-select picklists in Salesforce was critical for territory planning. Unfortunately, it took several weeks to get the right end results to data load into Salesforce.
“That was half of my month, half of my year, spent on this task. It was just bonkers,” says Brendon. Using Tray.io to automate this process reduced the work from 2 weeks to only 30 minutes each month because Tray.io does all the actual processing and uploads to Salesforce.
“Transitioning over to an automation tool where you can rapidly recreate excel upload processes is the key point here.” - Niels Fogt
If you’ve self selected to work in revenue operations, it’s probably because you love working with data. Using a RevOps automation solution like Tray.io can help make your data analysis so much easier and scalable—and you can do it all yourself.
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