Are We There Yet? Analyzing Progress in the Conversion Funnel Using the Diversity of Searched Products
76 Pages Posted: 5 May 2017 Last revised: 11 Nov 2020
Date Written: May 4, 2020
The conversion funnel is a model describing the stages consumers go through in their journey towards a purchase. This journey often lasts several days to weeks and can include multiple visits to a seller’s website. A large body of literature has focused on using observable search patterns to identify consumers’ hidden purchasing stages and to estimate their likelihood of conversion. We propose a novel set of measures to better unveil the consumer’s hidden stage in the funnel. These measures are based on the diversity of the searches that a customer engages in while browsing an e-commerce website, and they include not only the number of different products that are searched for, but also measures that rely on unobserved similarities among products, captured in a product network (in which products are assumed to be “similar” if they are frequently co-searched). We operationalize and evaluate our proposed measures using a large-scale dataset from a medium-sized tourism website used for comparing and booking flights. We estimate a hidden Markov model to show that our proposed diversity measures are associated with progress in the funnel and consumers' conversion likelihood. Specifically, we show that consumers go through different distinguishable stages (states) in their journey, characterized by different values of our proposed diversity measures. To demonstrate the managerial and business implications of our theory, we show that incorporating search-diversity measures into a baseline prediction model improves the model’s performance in predicting purchase likelihood and churn. For example, the purchase likelihood prediction model’s recall, precision and F1-score improved by factors of 5.64, 5.59, and 6.17 respectively.
Keywords: conversion funnel, engagement, diversity, search diversity, Online Marketing, consumer research, Tourism, Online booking, E-commerce, time to conversion
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