Abstract
This study examines the role of social media analytics (SMA) in providing competitive intelligence (CI). Building on CI theory, the data from qualitative semi-structured interviews with respondents belonging to social media, manufacturing, telecommunication, IT and service industries were analyzed using Nvivo coding and matrix queries. The results show that SMA provides an expanded CI beyond the previous limits of customers/markets and competitors, including insights on supply chains, costs and information-flow. Moreover, SMA-driven CI can provide visibility to supply chain uncertainties enabling improvements in demand planning and inventory management. SMA can provide CI about competitors’ strengths and weaknesses and customers’ dynamics; however, the bi-directional nature of CI could be determinantal if SM-linked customers are not educated/kept informed. Matrix query results illuminate the differences/similarities in respondents’ views. Academically, the study shows that SMA provides expanded CI to businesses beyond previously known scope of competitor analysis.
Highlights
The use of social media (SM) in business and everyday life is increasing exponentially
This study examines the role of social media analytics (SMA) in providing competitive intelligence (CI)
Why is the increase in cost larger than the increase in income? This can be analyzed through big data analytics on social media data
Summary
The use of social media (SM) in business and everyday life is increasing exponentially. A recent report shows that there are 3.196 billion SM users globally (representing an annual growth of 13%), with 79% of the global internet population (estimated at 4.021 billion in 2018) and 90% of brands using SM to build brand awareness (Chaffey, 2018). These staggering figures point to the potential value of SM for businesses. Given the pervasiveness of SM use among multiple tiers of society, SM data can provide valuable business intelligence about customers, including their demographics and psychographics, purchasing habits, preferences, and behavioral intentions (He et al, 2017). User-generated data from SM, including users’ geolocations, opinions, and preferences, can reveal valuable information about customers’ tastes, thoughts, and behaviors, constituting an important source of analytics to obtain competitive intelligence (CI) and other types of business intelligence for decision-makers (Shollo & Galliers, 2016).
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
