Lead scoring needs engagement data to function. When engagement is low, your scoring model is working with thin signals — a single like might push someone to the top of the list simply because nobody else is engaging at all. This produces noisy, unreliable scores. Ghost addresses both sides of the problem: it helps you create content that drives genuine ICP engagement (more data points) and applies sophisticated scoring that accounts for signal quality, not just quantity.
The problem
Low engagement means your scoring model has insufficient data. Scores are noisy and unreliable because they're based on one or two interactions rather than a pattern of behaviour. Your team doesn't trust the scores because they've been burned by false positives.
How Ghost solves this
Ghost helps you generate more ICP engagement through content optimisation and then scores those interactions using a multi-dimensional model that weighs recency, frequency, and depth. More data points produce more reliable scores.
Ghost users who increase ICP engagement by 2× see their lead scoring accuracy improve by 45%, as measured by score-to-meeting correlation.