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To unlock social media’s value, this study aims to integrate insights from several theoretical perspectives and the relevant literature, developing an extended social media analytics framework. It identifies the stages underlying the social media analytics process and tests the framework in three important and interconnected areas: social media (Twitter), new product adoption (iWatch and Google Glass) and social media analytic techniques (text mining and sentiment analysis).

Based upon a systematic review of different research approaches, theories and media types, this paper presents and tests an extended framework in three important and interconnected areas mentioned above.

This paper offers a theory-driven social media analytics framework. It validates the framework by providing concrete processes, examples, evidence and insights related to three chosen areas mentioned above, thereby helping managers create effective and efficient social media and new product development strategies.

This paper integrates insights from theories of the middle range (Merton, 1949), Campbell’s (1965) model of sociocultural evolution and Fan and Gordon’s (2014) social media analytics framework, developing its own extended social media analytics framework and validating it in three important and interconnected areas mentioned above. This paper demonstrates not only how the proposed framework can be applied to the context of new product development, but also how social media are transforming research approaches (qualitative, quantitative and mixed method) and the very nature of business itself (increased importance of digital business).

Consumers are assumed to engage in external information search only after exhausting their internal information sources. Guided by the accessibility/diagnosticity and ease-of-retrieval frameworks, and the elaboration likelihood model, the current study investigates this phenomenon.

To test the relationships between internal information accessibility/diagnosticity and the importance of external search, and the moderating role of involvement in these relationships, 308 responses were collected on Amazon MTurk. Then, structural equation modeling was employed to analyze the data.

The analyses showed that while accessibility and diagnosticity of internal information have an impact on external information search, involvement with the product class has a consequential moderating effect on these relationships. In particular, in the low-involvement group, only the diagnosticity of internal information had a negative effect on external information search. On the contrary, in the high-involvement group, only accessibility of internal information had a negative effect.

These findings highlight the possibility of drawing erroneous conclusions resulting from not incorporating involvement, in conjunction with information accessibility and diagnosticity, in the study of the consumer external information search behavior.

The findings also imply that if practitioners aim to prime consumers to engage in external information search, they need to take into account that the effects of internal information's accessibility and diagnosticity on consumers' external search behavior may be different depending on their levels of involvement.

This study's results showed that without considering the moderating effect of involvement, spurious conclusions may be made about the relationships between accessibility and diagnosticity of internal and external information importance. This finding may explain the discrepancy between the accessibility/diagnosticity and ease-of-retrieval frameworks, thus enriching the literature.