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A predictive response model to classify the outbound sales mails based on their subject and body. It helps sales teams to increase their call conversion rate by calling the right people.
Hiring a sales team and tasking them with calling the unresponsive customers is a tedious task and wasting money. If you can understand who is likely to respond you can mail or call the right people and generate more from less. The model helps to identify the right customers who responded by targeting the people who are not currently purchasing.
We are always there to fine-tune your processes by developing a custom framework by implementing such amazing and accurate problem-solving techniques in your organization.
Classify text as positive, negative or neutral and return as classifier
Classify Customer sentiments towards certain entities
Classify social media sentiments towards certain entities
Summarize any piece of text with just a click
Automatically identify the key information within a document
Generate a human quality title for the Source
Classify text as likely to have been written by a human or machine
Extract email address from text
Extract date and time from text
Extract person names from text
Extract locations from text and give coordinates
Extract Phone numbers from any piece of text
Extract company and organization entities from text
Classify outbound sales email responses based on their subject and body
Classify news based on Topics
Classify retail products based on their descriptions
Classify job titles into categories
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