In an Account-Based Marketing (ABM) strategy, building your list of key accounts is an essential first step.
But which of these accounts are actually ready to buy?
This is where the Qualification Score, Demandbase’s predictive score, comes in.
Using artificial intelligence, it helps you identify the most promising accounts and focus your efforts where they will have the greatest impact.
Why use a predictive score?
A good ABM strategy relies on accuracy.
But even with a well-constructed Target Account List, it’s difficult to know which accounts are most likely to become customers.
The Qualification Score solves this problem:
This score allows you to:
- 🎯 Prioritize your marketing and sales campaigns
- 🤝 Align sales with high-potential accounts
- 💰 Optimize your budgets by focusing on the most profitable opportunities
How is the Qualification Score calculated?
The Qualification Score is based on a machine learning model trained using your existing customer data.
Demandbase analyzes what characterizes your best customers, then evaluates each account according to the same criteria.
Here are the main data sources used:
| Data Type | Example | Role in Model |
|---|---|---|
| Internal (CRM & Marketing Automation) | Customers, Won Opportunities | Identify existing customer profile |
| Firmographics | size, industry, revenue, region | Define the structural “fit” of an account |
| Technographics | tools used: Marketo, Salesforce, HubSpot, etc. | Determine technological compatibility |
| Intent Data | Keywords searched on the web (ABM, marketing automation, etc.) | Measure active interest in your topics |
AI then compares these signals to those of millions of other companies in the Demandbase database to calculate the probability that an account will become a customer.
How to use the Qualification Score in Demandbase
Once calculated, the Qualification Score becomes a powerful lever for action in your Demandbase platform.
Here are some concrete uses:
1. Create smart audience segments
Filter your accounts according to their score: for example, all accounts with a score > 70.
This segment represents your “good fits” — the accounts that deserve your prospecting and nurturing efforts.
2. Prioritize your sales actions
The score is automatically pushed to your CRM.
Your sales teams can then sort their accounts according to potential and focus their prospecting on the best candidates.
3. Customize your marketing campaigns
In Marketo or any other automation tool, use the Qualification Score to tailor the message and intensity of your campaigns according to the account’s potential.
4. Analyze your performance
Compare conversion rates and revenue generated according to score ranges.
This is an excellent way to validate the relevance of your predictive model and refine your ABM strategy.
Best practices
✔️ Have at least 50 to 100 customer accounts in your CRM before launching the model (the richer the sample, the more reliable the score will be).
✔️ Retrain the model every 6 months so that the AI incorporates your new customers and trends.
✔️ Integrate the score into your CRM and marketing automation dashboards to track the progress of your accounts.
In summary
| Objective | Action | Benefit |
|---|---|---|
| Identify the right accounts | Use the Qualification Score as the main filter | Focus on high-potential accounts |
| Align marketing and sales | Synchronize the score with the CRM | Common prioritization |
| Measure performance | Analyze conversions by score range | Validate the AI model |
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