Variation matters: How to curb ad intrusiveness for native advertising on Facebook, Twitter, and Instagram

Abstract

Purpose

In-feed native ads have become a major social media advertising format. The purpose of this paper is to investigate strategies for leveraging native advertising in terms of content creation and platform selection on social media, proposing that variations in content and platform reduce the intrusiveness of native ads, thereby resulting in enhanced brand attitude and purchase intent.

Design/methodology/approach

Two experiments were conducted with online samples, employing a 2 (content strategy: repeated ads vs varied ads) × 2 (platform strategy: single platform vs multiple platforms) between-subject factorial design. ANCOVA and structural equation modeling were used to test the hypotheses.

Findings

When repeated ads were used, the use of multiple platforms reduced ad intrusiveness, resulting in more favorable brand attitude and greater purchase intent as opposed to the use of a single platform. In contrast, when varied ads were used, there were no significant differences in the outcome variables between a single platform and multiple platforms. The results were largely consistent across the two experiments.

Originality/value

This study contributes to theory advancement by unpacking the underlying mechanisms of processing native advertising and shedding light on which content and platform strategies are the most effective on social media.

Citation

Huang, G. (2019), "Variation matters: How to curb ad intrusiveness for native advertising on Facebook, Twitter, and Instagram", Internet Research, Vol. 29 No. 6, pp. 1469-1484. https://doi.org/10.1108/INTR-12-2017-0524