Automatically combine internal data with geographic and demographic data to create robust territory plans
Get the right accounts to the right salespeople, without overloading your salesforce
Efficiently create models that reduce the number of accounts that fall through the cracks
What does it take to optimize sales territories? How do you arrive at a size, both geographically and by customer composition, that ensures fairness to individual representatives and overall sales success for the company?
Factors in setting sales territories include workload, sales potential, geographic constraints, and travel time. Because no single source contains all the data required for accurate calculations, sales operations teams pull data from HR systems, CRMs, enterprise data warehouses, and industry-specific sources. They then spend days or weeks building elaborate models in spreadsheets and even more time every year running and updating the models.
Automating the process of establishing sales territories starts with spatial analytics like geographic distance, driving time, find-nearest, create-points, spatial matching, and location optimization. Instead of relying on spreadsheets, sales operations teams use analytic workflows to extract and blend data from sources like HR, CRMs, compensation, sales forecasting, prospecting tools, and data warehouses.
The resulting automation is better than a spreadsheet model because it’s far less labor intensive (hours instead of weeks) and easier to maintain. It eliminates time and money spent on data costs such as purchase/acquisition from outside sources, loading, preparation, summarizing, and alignment. It does away with the manual processes involved in defining and refining territory boundaries and publishing the results.
1 – Data Connection
Import Data from HR, CRM, and market data
2 – Prep & Blend
Use tools like the JSON parse tool to transform data into a workable format
3 – Export
Use blended sales and activity data to jumpstart GTM execution