Qualification Score is derived from a machine learning model that is trained to identify which accounts look most similar to your past customers. It considers various factors such as account firmographics, technographics, and intent signals to define an ideal customer.
Demandbase scores your accounts from your CRM and CSV, along with the 55 million accounts in the Demandbase database. By focusing on accounts with high qualification scores, you can strategically prioritize accounts that most fit your ideal customer profile, regardless of where they are in the buyer journey.
Important: Only Accounts with a domain get a Qualification Score.
See Set Up Qualification Scores to configure your Qualification Scores.
You can also set up multiple Qualification Scores according to account fit and interest in your different product offerings. See Understanding Multiple Predictive Scores.
Quick Facts
| Score |
|
| Initial Model Build Time | 24 hours |
| Model Re-Training Time |
24 hours. See Retrain Qualification Scores. |
| Score Update | Static (The qualification score criteria does not change frequently.) |
| Customer Connection Modes |
|
Factors Used When Calculating the Qualification Score
Demandbase uses the data in the following table:
| Accounts | Set of 50 or more accounts. For best results, we recommend using 100 or more of past and current customers. |
| Firmographics | Uses country, industry, revenue range, and number of employees. |
| Technographics | Uses the current tech stack of your Customer or Target Account lists. |
| Historical Intent | Uses past one year of intent. |