Autometa / Blog
Notes on building AI-native software.
Product decisions, CRM architecture, engineering deep-dives, and actionable playbooks from the team building Autometa CRM and Synkly.
What Is Lead Scoring? A Beginner's Guide
What is lead scoring? Learn how fit and engagement scores rank your leads, when a small business actually needs it, and how to start with a simple 5-rule model.
How Lead Scoring Works: Models, Points and Examples
How does lead scoring work? See the models, a points table you can copy, negative scoring, decay and a worked example that sets your sales threshold from data.
Predictive Lead Scoring: How AI Ranks Your Best Leads
Predictive lead scoring uses your CRM history to rank leads by likelihood to convert. See how models train, how much data vendors require, and when it pays off.
AI Lead Scoring: How It Works and How Accurate It Is
AI lead scoring ranks leads using CRM data and conversations. Learn how accurate it is, which metrics matter, and how to test vendor claims on your own data.
What Is Lead Qualification? Frameworks and Criteria
What is lead qualification? Learn the fit, intent and timing criteria, how MQLs, SQLs and PQLs differ, and which framework suits your team. Read the guide.
How to Qualify Leads: BANT, MEDDIC and AI-Assisted Qualification
Learn how to qualify leads in sales with a 6-step process, BANT and MEDDIC question banks, and a clear split of what AI agents should and shouldn't handle.
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