[Purpose/significance]How to effectively integrate and utilize multi-source data in the big data environment is the key problem of enterprise product competitive intelligence research and practice. This paper aims to solve the different tasks of product competitive intelligence analysis by using the characteristics of different data sources from the perspective of task decomposition. It proposes and verifies the competitive intelligence analysis model of the goal-level fusion, which provides the basis for the follow-up theory research and practice.[Method/process]First of all, it compared several typical network sources of the product consumption data, product dynamic news and user data, and combed its characteristics and the value in the product market competitive intelligence analysis. Secondly, In terms of three tasks-competitive product identification, product dynamic tracking and product user analysis, the corresponding data sources were integrated into the product competitive intelligence analysis process. In the empirical part, it chose the "OPPO R9s" phone as the analytic target, integrating the data of mainstream e-commerce platform, Baidu News and Sina Microblog into the product competitive intelligence analysis.[Result/conclusion]The experimental results show that our approach can identify the competitive product of "OPPO R9s", detect their hotspot issues in market and reveal the distribution of users who concern about these products. The multi-source fusion scheme proposed in this paper can effectively support the enterprise market competition intelligence analysis.
Chen Guo
,
Zhu Xiling
,
Xiao Lu
. Study on Multi-source Fusion Competitive Intelligence of Enterprise Products from the Perspective of Task Decomposition[J]. Library and Information Service, 2017
, 61(22)
: 127
-133
.
DOI: 10.13266/j.issn.0252-3116.2017.22.016
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