The use of keyword-based matching to identify the most significant findings within a larger set of candidate webpages is a key element of many brand-protection technologies. The approach can build efficiencies into the overall analysis process, and can help to identify priority targets for content tracking or enforcement, and is therefore an essential component of effective tools used for brand-protection programmes.
In our latest study, we outline a new methodology for analysing the proximity of ‘relevance keywords’ to brand terms, in order to calculate a metric for the potential level of relevance of a webpage. The framework is based on the methodology previously outlined for calculating the sense of the sentiment of brand references in our ‘top 100 brands’ study, and is a flexible approach which can be tailored to a range of different contexts. The methodology is illustrated using a series of short case studies.
The concept of filtering using relevance keywords is central to many areas of brand monitoring, all broadly covered under the description of ‘issue monitoring’. These ideas set the scene for a number of additional applications in the brand-protection arena, such as the use of identification of instances of ‘high-risk’ e-commerce keywords to prioritise websites based on the likelihood of their association with the sale of counterfeit goods.
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