REAL TIME BRAND HEALTH
A strong and recognizable brand, which has a consistent identity across all marketing activities, helps differentiate from competitors. It gives a sense of credibility as well as competitive advantage. In order to support marketing strategies, RTBH assesses companies' brand image, relevance and competitive positioning with a new methodology, based on the analysis of "spontaneous" expressions of consumers and stakeholders. For example, data is considered from social media and online news.
The advantage of RTBH over traditional analytics measures is that we do not rely on surveys administered to small samples of consumers. Our measures can be calculated using any source of online text document- news articles, emails, and tweets -in order to capture honest insights and signals through the analysis of textual big data. Spontaneous expressions from consumers, or other brand stakeholders, can be collected in almost real-time from the places where they are posted. In addition to reducing response time, this has the advantage of reducing bias induced by the use of questionnaires, where respondents know they are being observed. To this end we monitor, on a daily basis, the following web channels:
Blogs | News online | Social Networks | Forums | Daily Newspapers
RTBH provides the most relevant customer journey metrics, along with sentiment analysis and an estimate of how brand attributes are perceived. We also calculate the Semantic Brand Score (SBS), a composite indicator that measures brand importance by considering the relationship between words within text. Brand importance is not only a matter of the frequency with which a brand is mentioned (share of voice) but also of the associations a brand has in the text. Specifically, texts are transformed into networks of co-occurring words, and the relationships are studied through Social Network Analysis. Semantic Brand Score a composite indicator that measures brand (SBS), importance by considering the relationships between words in a text. Brand importance is not only a question of the frequency with which a brand is mentioned (share of voice), but also of the associations a brand has in the text. Specifically, texts are transformed into networks of co-occurring words and the relationships are studied through Social Network Analysis. In the phase of generating networks from texts, some common text pre-processing routines are applied.
Brand importance according to the Semantic Brand Score (SBS) is measured by combining methods of Social Network Analysis and Text Mining, along three dimensions:
Prevalence, partly related to the brand awareness construct, measures the frequency with which a brand name is used in discourse. The more a brand name is mentioned, the more readers will remember and recognize it, which is likely to influence their opinions and behaviors.
Diversity is a dimension of SBS that considers the relationship of brands to other words in the text. This is related to the construction of brand image and the idea that when associations are distinctive and in large numbers, the brand is more important. Diversity is calculated through "distinctiveness centrality" metrics.
The connectivity dimension represents the "brokering power" of brands: how much can it act as a bridge to connect other terms (and ultimately topics) in the discourse. In addition to measuring a brand's image and relevance, we offer a useful report on what actions can be taken in terms of investing in social media campaigns to tie the brand to disparate topics and concepts. We report the words that, if used in future communication, could make the brand more central to the discourse. However, one must also avoid favoring competitors and pay attention to keeping communication consistent with the brand strategy. We use specific algorithms to help solve this problem.
RTBH reports, which can be provided on a daily, monthly, or quarterly basis, offer in-depth details on:
- Semantic Brand Score (brand importance)
- Sentiment analysis and graphs of brand positioning, comparing importance with sentiment
- Analysis of brand importance dimensions: prevalence, diversity and connectivity
- Brand metrics and perception of brand attributes
- Study of prevalent words at the connective center of discourse
- Modeling of major discourse themes and study of their association with the brand
- Analysis of perceived and conveyed brand image through the study of the main brand associations and distinctive features of each brand
- Analysis of the distances and similarities between the different brand images resulting from the processing