A consumer-dependent (business-to-consumer) organization tends to present itself as possessing a set of human qualities, which is termed as the brand personality of the company. The perception is impressed upon the consumer through the content, be it in the form of advertisement, blogs or magazines, produced by the organization. A consistent brand will generate trust and retain customers over time as they develop an affinity towards regularity and common patterns. However, maintaining a consistent messaging tone for a brand has become more challenging with the virtual explosion in the amount of content which needs to be authored and pushed to the Internet to maintain an edge in the era of digital marketing. To understand the depth of the problem, we collect around 300K web page content from around 650 companies. We develop trait-specific classification models by considering the linguistic features of the content. The classifier automatically identifies the web articles which are not consistent with the mission and vision of a company and further helps us to discover the conditions under which the consistency cannot be maintained. To address the brand inconsistency issue, we then develop a sentence ranking system that outputs the top three sentences that need to be changed for making a web article more consistent with the company's brand personality.

中文翻译：

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一种提高网页内容品牌一致性的综合方法：建模、分析和推荐

依赖于消费者（企业对消费者）的组织倾向于将自己展示为拥有一系列人的品质，这被称为公司的品牌个性。通过组织制作的内容，无论是以广告、博客还是杂志的形式，这种感知都会给消费者留下深刻印象。随着时间的推移，一致的品牌将产生信任并留住客户，因为他们对规律性和常见模式产生了亲和力。然而，随着需要创作并推送到互联网以保持数字营销时代优势的内容数量的虚拟爆炸，为品牌保持一致的消息基调变得更具挑战性。为了了解问题的深度，我们从大约 650 家公司收集了大约 30 万个网页内容。我们通过考虑内容的语言特征来开发特定于特征的分类模型。分类器自动识别与公司使命和愿景不一致的网络文章，进一步帮助我们发现无法保持一致性的条件。为了解决品牌不一致问题，我们开发了一个句子排名系统，输出需要更改的前三个句子，以使网络文章更符合公司的品牌个性。