Qualification Scores help you identify accounts that closely match your ideal customer profile (ICP). Demandbase uses a machine learning model trained on your past customers to evaluate account fit based on firmographics, technographics, and historical intent signals.
Demandbase calculates Qualification Scores for accounts imported from your CRM or CSV files, as well as accounts in the Demandbase database. You can use these scores to prioritize accounts that are most likely to fit your ideal customer profile, regardless of their stage in the buyer journey.
Important: Only Accounts with a domain receive a Qualification Score.
To configure Qualification Scores, see Set Up Qualification Scores.
You can also configure multiple Qualification Scores to evaluate account fit for different product offerings. See Understanding Multiple Predictive Scores.
Quick Facts about Qualification Scores
| Score |
|
| Initial Model Build Time | 24 hours. |
| Model Re-Training Time |
24 hours. See Retrain Qualification Scores. |
| Score Updates | Scores remain relatively static because the criteria used to evaluate account fit do not change frequently. |
| Customer Connection Modes |
|
Data Used to Calculate Qualification Scores
Demandbase uses the following data to train the Qualification Score model and evaluate account fit.
Data |
Description |
| Customer Accounts | Requires at least 50 accounts. For best results, use 100 or more past and current customer accounts. |
| Firmographics | Country, industry, revenue range, and number of employees. |
| Technographics | Technologies used by accounts in your Customer or Target Account lists. |
| Historical Intent | Intent activity from the past 12 months |