Understanding Behavioral Marketing and Customer Segmentation
Understanding Behavioral Marketing and Customer Segmentation checks whether you can use what a contact does - not just what they typed - to decide what they see next.
Explicit versus implicit data
Explicit data is declared: form fields, surveys, stated preferences. Implicit data is observed: pages viewed, emails opened, content downloaded. Behavioral marketing runs on implicit data.
Lists and properties
Static lists are a snapshot; active lists update themselves as contacts meet or stop meeting criteria. Build active lists from behavioral criteria because they stay accurate as the database changes. Custom properties store what you learn about a contact; lifecycle stages track progression from subscriber to lead, MQL, SQL, opportunity, customer, and evangelist.
Lead scoring
Score fit (industry, job title, company size) and engagement (email clicks, site visits, form fills) separately, then combine. Set the threshold that triggers sales notification, and add score decay for inactivity so old engagement does not inflate rankings.
Worked example
A team wants to email pricing-sensitive leads. Reasoning: an active list built only on "visited /pricing" would capture curious competitors and existing customers. A better list uses "engagement score ≥ 20" AND "downloaded the pricing guide" AND is suppressed against the current customer list. Suppression matters as much as inclusion - the wrong recipient costs more than a missed one.
Traps
Segmenting on demographics only; forgetting suppression lists so customers receive prospecting email; relying on static lists that go stale; treating a single page view as buying intent.