For the past few months our dev team has been working on the roll-out of the sentiment analysis feature for Grace. In basic terms, sentiment analysis is the process of determining whether a piece of writing is positive, negative or neutral by using natural language processing, text analysis and computational linguistics. From companies using sentiment data for monitoring consumer perception, to public figures and celebrities leveraging the power of sentiment data for impression management, sentiment analysis is all around us; from social networks to online stores to chat bots. Now, Grace is integrating sentiment analysis features into its product to simplify the daily management tasks of its users.
Sales reps get bombarded with hundreds of emails on a daily basis. Critical and time-sensitive data gets lost in the flood of replies, side conversations and noise; as it takes hours and days to go through every email. Grace is set to make this process more effective and manageable. In addition to automatically capturing sales-related emails inside Salesforce, Grace scans each email for the following: emotional reaction and intent to buy. Grace indicates each of these parameters via icons next to the captured email inside the Grace timeline. Thus, making it much easier for the sales rep to focus on the most pressing emails without having to read every email in full first. Grace allows sales reps to filter emails by emotional response as well as intent to buy, so each sales rep can decide which to focus on first.
Additionally, Grace allows sales reps to filter the timeline to display only the emails and updates pertaining to their leads and accounts, eliminating any noise from the constant inflow of data.