Last summer, Inbound Design Partners explored the world of Inbound Lead Generation — but what happens after you start attracting traffic and collecting contacts? If your leads are stalling, going cold, or ghosting you after multiple follow-ups (even after those personalized emails you crafted so beautifully), you're not alone. The real challenge begins when interest doesn't turn into action.
Enter lead scoring: a smart, strategic way to rank your leads by how engaged they are and how closely they match your ideal customer profile. With HubSpot’s predictive lead scoring feature, you can even let AI do most of the heavy lifting for you.
What is lead scoring?
- Lead scoring is the process that you and your business use to assign a value to help you determine which leads to prioritize outreach to.
Lead scoring is the process of assigning points to contacts based on:
- Behavior (e.g., email opens, form submissions, website visits)
- Demographics (e.g., job title, industry, company size)
- Engagement (e.g., downloads, interactions)
- Lifecycle stage or source
For example, you can dedicate a point system: assign 20+ points to contacts who’ve filled out a form or visited your contact page. Give 10+ points to those with senior job titles like “Director” or above. On the other hand, you can assign a negative (-5 to -10) points to contacts who’ve unsubscribed from your emails. By customizing your scoring criteria within HubSpot’s CRM, you're clearly signaling to your sales and marketing teams which leads are worth pursuing—focusing their energy on high-intent prospects and avoiding those who’ve already opted out.
Lead Scoring can be found on the Marketing Hub Professional, Enterprise or Sales Hub Professional.
What is Predictive Lead Scoring?
Predictive lead scoring uses machine learning to help determine a value for your contacts. AI analyzes your existing data and automatically scores lead based on patterns it finds in closed-won vs. closed-lost deals. This will help you prioritize your leads more efficiently, improve conversion rates by focusing on the best-fit leads that can help your business shorten your sales cycle, align sales and marketing by using shared definitions of a “qualified lead” and, last but not least, improve ROI on your marketing and sales campaigns.
How does it work?
AI + machine learning will take a look at the following information:
- Email behavior - opens, clicks and saves
- Website activity - forms filled out, traffic, page visits and impressions
- CRM properties
- Historical deal data - customer interaction such as closed, not closed, won/lost deals.
HubSpot then generates a score between 0 and 100 for each lead, making it easier to prioritize high-quality prospects.
And the overall purpose of predictive lead scoring is to help you remove the guesswork and build a smarter scoring model based on real customer behavior — no manual rule settings required. HUZZAH!
Predictive Lead scoring can be found on the Marketing Hub Enterprise version of HubSpot.
Important to remember:
💡The model improves over time as it learns from your actual customer data - like any AI Model. The more high-quality, consistent data you have in your CRM, the more accurate the predictions will be.
💡If you have less than 100 customers and 1,000 non-customers, HubSpot won’t enable predictive scoring.
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