Definition
Lead scoring is the practice of assigning a numeric score to each prospect based on how likely they are to convert into a customer. A high score tells sales to call immediately; a low score tells marketing to keep nurturing. Traditional lead scoring uses rule-based points (contact from a Fortune 500 company = +20, personal Gmail address = -10, downloaded three ebooks = +15), summed into a total.
Modern lead scoring uses machine learning to learn which signals actually predict conversion in your data, rather than guessing. An ML-trained model can pick up on subtle combinations (engineering titles at mid-market companies who visit pricing twice within 48 hours are 8x more likely to convert) that rule-based systems miss.
How SheetLinkWP relates to Lead Scoring
SheetLink Forms offers an AI Lead Scoring add-on that scores every form submission 0-100 using a hosted LLM pipeline. The model evaluates the content of the submission itself (company signals in email domains, job title indicators in message text, budget mentions, urgency language) and assigns a category: Hot (80-100), Warm (50-79), or Cold (0-49). The score and category are written to their own columns in your Google Sheet, so sales can sort by score and call down the list.