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This paper aims to examine whether estimates of psychological traits obtained using meta-judgmental measures (as commonly present in customer relationship management database systems) or operative measures are most useful in predicting customer behavior.

Using an online experiment (N = 283), the study collects meta-judgmental and operative measures of customers. Subsequently, it compares the out-of-sample prediction error of responses to persuasive messages.

The study shows that operative measures – derived directly from measures of customer behavior – are more informative than meta-judgmental measures.

Using interactive media, it is possible to actively elicit operative measures. This study shows that practitioners seeking to customize their marketing communication should focus on obtaining such psychographic observations.

While currently both meta-judgmental measures and operative measures are used for customization in interactive marketing, this study directly compares their utility for the prediction of future responses to persuasive messages.

This paper aims to develop and test a method of automating, for online retailers, the practice of adaptive selling, which is typically used by salespeople in face-to-face interactions. This method customizes persuasive messages for individual customers as they navigate a retailer’s website.

This paper demonstrates a method for the online implementation of automated adaptive selling using sales influence tactics. Automated adaptive selling is compared to nonadaptive selling in three e-commerce field studies.

The results reveal that adaptive selling is more effective than nonadaptive selling. The click-through rates increased significantly when adaptive selling was used.

This paper highlights the effectiveness of existing theories concerning adaptive human-to-human selling and their utility to online selling. The authors demonstrate the added value of adaptive selling in e-commerce, thereby opening up a novel area of research into adaptive selling online. While the paper focuses on the adjustment of sales influence tactics, other factors could be investigated for adjustment in future research (e.g. prices).

The methods, described in detail, are readily available for implementation by online retailers. The implementations are timely and increasingly valuable as e-commerce expands into interpersonal channels (e.g. instant messengers and social media).

To the authors’ knowledge, this paper is the first to formally implement automated adaptive selling as described in the ISTEA model in an e-commerce setting.