The mid-funnel represents the guest's journey from website visits to making a purchase. Mid-funnel optimization involves refining this journey by implementing targeted marketing strategies to boost the purchase rate. Guest engagement analytics focuses on evaluating engagement metrics throughout the guest's journey, specifically analyzing the Level of Engagement (LOE) and the Order of Touches (OOT). 

Mid-funnel optimization incorporates multiple machine learning models to enhance the guest's journey toward purchase.

• A classification model predicts guests with a high propensity to purchase, enabling targeted marketing efforts for prioritized guests.

• A clustering model segments guests to ensure that the right marketing activities reach the right audience with optimal resource allocation.

• A regression model estimates the velocity to purchase, predicting the number of days until a guest is likely to buy, allowing marketers to adjust the pace of their campaigns accordingly.

• An optimization model refines the timing of marketing activities by determining the ideal interval between touchpoints to drive purchases within a set timeframe.

• Classification model predicts the most effective next marketing activity to guide guests toward completing a purchase.

Guest engagement analytics measures engagement levels based on web visits. A guest’s journey is mapped by analyzing active and inactive periods before purchase. Each visit within a journey is evaluated to determine how media campaigns accelerated conversions and to identify touchpoints where guests became inactive, using order-of-touches analysis.