In digital marketing, acquiring new customers is becoming more expensive, and their lifetime value is decreasing. To help companies and agencies use their digital marketing budgets more effectively, the Likelihood to Purchase (LTP) algorithm offers a valuable segment that drives more conversions and improves ROAS (return on ad spend).
The LTP algorithm predicts the probability that a user will make a purchase within a specific time frame by analyzing real-time behaviors such as repeated visits to the same product, adding items to the cart, or browsing on certain devices. It does not rely on CRM data—only real-time session data such as product page views, cart events, and interactions.
How does the Likelihood to Purchase (LTP) work?
The algorithm learns from the behaviors of users who complete a purchase and identifies patterns that typically lead to conversions.
It assigns coefficients to these behaviors through its classification model, which predicts whether a user is likely to purchase or not.
Each visitor, logged in or anonymous, is assigned a dynamic LTP score based on their behavior while on the site.
This score updates in real time, and once it surpasses a model-determined threshold, the user is expected to make a purchase within the next seven days.
Since behavior differs between platforms, LTP values are calculated separately for app and web, reflecting their distinct data inputs.
Model Details
The LTP algorithm operates with a real-time, behavior-based classification model. The following details explain how the model functions and how frequently it is updated:
Segment update frequency: Real-time
Data span: Active session
Calculation time: Model training takes approximately 15–20 days
Model type: Classification
Key Behavioral Signals
The algorithm identifies and weighs specific user behaviors strongly correlated with purchase intent. These behaviors shape the LTP score calculation:
Session recency and frequency
Product category interactions
Cart abandonment patterns
Users with a high LTP score can be retargeted with personalized offers, time-limited discounts, or cart abandonment reminders. These high-intent segments can also be synced with ad platforms such as Google Ads, Facebook Ads, and other digital marketing channels to convert more clicks into purchases.