Investigating Purchase Conversion by Uncovering Online Visit Patterns

Abstract

This research aims to understand and predict online customers’ store visit and purchase behaviors. To this end, we develop a model that accounts for different patterns of online store visits at the individual level. Given the latency of visit patterns, we employ a changepoint modeling framework and statistically infer them using a Bayesian approach. The inferences obtained are then used to examine the effects of visit patterns on purchase dynamics across store visits. Using Internet clickstream data at an online retailer, we find that online store visit patterns tend to be clustered with significant variation across customers in terms of the number and size of visit clusters as well as the visit frequencies, both within and between clusters. Furthermore, the conversion rates vary significantly, depending on store visit patterns, such that they tend to be higher at later visits within a visit cluster, compared with earlier visits. The proposed model thereby offers superior fit and predictive performance than benchmark models that ignore clustered visit patterns and their impact on purchase behavior. We demonstrate the model’s ability to better identify prospective customers by utilizing their visit patterns, which can assist marketers in scoring customers and making targeting decisions across individuals for marketing activity. Data, as supplemental material, are available at https://doi.org/10.1287/mksc.2016.0990 .

Will this search end up with booking? Modeling airline booking conversion of anonymous visitors

“…Price may have impacts on customers' loyalty throughout the whole decision-making process, from search to purchase. While many studies have explored how customers' search activities affect purchase conversions (Moe and Fader, 2004;Iwanaga et al, 2016;Park and Park, 2016;Mokryn et al, 2019), very few studies have investigated the price effect on customer engagement within a website. Our empirical results imply that simple measure of search-topurchase conversion rate may be misleading in the context of online promotion and marketing as price, often measured as discounts, may play a significant role in the purchase conversion.…”

“…While search and visit are the fundamental elements of online activities, a booking may be made after many searches, and often visits, spanning hours, days or even weeks. In fact, many of previous studies including Chatterjee et al (2003), Moe and Fader (2004) and Park and Park (2016) investigated online behavior across visits. Lastly, a user is identified through a cookie, which is stored in a user's computer.…”

“…Our work relates to various streams of existing literature on online browsing behaviors and purchase conversion. Many studies including Chatterjee et al (2003), Moe and Fader (2004), Iwanaga et al (2016), Park and Park (2016) and Mokryn et al (2019) investigated online search activities and their effects on purchase conversions. Chatterjee et al (2003) developed a model to capture search and conversion behaviors in online banner advertising.…”

“…Moreover, they examined the relationship between visit frequency and purchase probability. Park and Park (2016) suggested a model to predict online store visit and purchase probabilities. They specifically investigated customer visit patterns and their impacts on purchase dynamics across store visits.…”

Do cognitive and affective expressions matter in purchase conversion? A live chat perspective

“…This question is important but has yet to be adequately answered. Purchase conversion, which originated from e‐commerce research, refers to a phenomenon in which a visitor purchases during a visit to an online retailer (Park & Park, ). This research thus investigates how the communication between retailers and shoppers via live chat can lead to purchase conversion in an online context.…”