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data preparation leads to ai success: three use cases
1. Ai enhances efficiency
imagine a sales team at a tech company, let’s call them “futurix dynamics.” they’ve cleaned andthat’s stored in their customer relationship management (crm) tool. This data preparation ensures accurate customer profiles and well-documented sales interactions. When they launch new ai capabilities for their crm, the ai assesses existing data and gives them insights on potential leads and upselling opportunities. Even better, it can then generate emails for the sales reps, and provide them with automated call summaries any time afghanistan phone number list they interact with a customer. As a result, their team spends less time typing and more time closing deals, significantly boosting their sales efficiency.
Over at “humanistek inc.,” a competing tech firm, the management rushes into ai implementation without proper data preparation. Their crm is cluttered with outdated contacts and inconsistent sales data. As a result, their ai platform frequently suggests irrelevant leads based on outdated customer information, leading to missed opportunities and frustrated sales staff who constantly have to correct data errors. Sales reps also have to spend too much time proofing the ai-generated emails, as they are frequently incorrect, so the efficiency ai promises is never realized.