Summary
Want your AI agent to qualify better leads? It all starts with the right lead qualification setup. This guide explains how to use and customize Astra’s built-in framework to match your sales process. Whether you're using the standard BANT model or your own custom approach, you can fine-tune every detail to get high-quality leads that actually convert.
Instructions
Your AI agent qualifies leads based on the criteria and scoring rules you set. Getting this right is key to helping your sales team focus on the most promising leads.
1. Start with the BANT framework (default)
By default, Astra uses the BANT model to qualify leads:
Budget – Can the lead afford your solution?
Authority – Is the lead a decision-maker?
Need – Does the lead actually need your product or service?
Timeline – When is the lead looking to make a decision?
2. Customize your qualification criteria
You can easily tailor the BANT framework to suit your business needs:
Enable or disable specific criteria.
Adjust weightage for each criterion to prioritize what matters most to your team.
Edit questions your AI agent asks to capture the right information.
For example, if timeline is less important for your business, you can reduce its weight or turn it off entirely.
Tip: Go to the Build My Agent settings of your AI agent to edit the lead qualification criteria and scoring.
3. Add your own custom criteria
Already using a different qualification method? No problem.
You can create and define your own criteria—just like BANT—based on what works best for your business. This gives you complete control over how leads are evaluated.
4. Fine-tune for better results
The more precise your criteria and scoring setup, the better your AI agent can:
Ask the right questions
Identify serious buyers
Assign accurate lead scores
This means less time wasted on unqualified leads and more focus on deals that are likely to close.