AI/NLP Sentiment Analysis

Using third-generation Artificial Intelligence/Natural Language Processing, we take a deeper look at anonymized corporate communications such as outgoing emails or Slack messages and show how and where our findings correlate with other data. What’s the alignment with data points? Corporate culture? Other business and employee-centric KPIs? What does a layering of this data reveal about recruitment, retention, development, career progression, and turnover? We work with clients to turn insights into actions. Some recommendations might involve training, but they all involve creating sustainable change at the 4P-level: policies, practices, pay, and pipeline.

Traditional Content Analyses

Content Analysis is a research tool used to determine the presence of certain words, themes, or concepts within some given qualitative data (i.e., text). Using content analysis, we can help with recruiting, for example, as to where and how to build awareness around hiring bias, check the language in job descriptions, blind the resume review process, standardize the interviews, look for bias toward likeability, implement a collaborative hiring process, acknowledge confirmation bias, consider diversity & inclusivity goals, and vary where you advertise. Content analysis can be both quantitative (focused on counting and measuring) and qualitative (focused on interpreting and understanding). In both types, you categorize or “code” words, themes, and concepts within the texts and then analyze the results.