Predicting Deal Closure in a Sales CRM using Email Sentiment

The ninth edition of The Fifth Elephant will be held in Bangalore on 16 and 17 July 2020.

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**Event details:

Dates: 16-17 July 2020
Venue: NIMHANS Convention Centre, Dairy Circle, Bangalore

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All submissions

Predicting Deal Closure in a Sales CRM using Email Sentiment

Submitted May 31, 2020

Emails are the most common form of communication in a sale and can be used to actively determine the customer’s interest in purchasing a product/service. Statistically, deals with more email replies from the customer are more likely to win. Our project, Deal sentiment at Freshworks as a part of the Freshsales CRM involves predicting sentiment from customers’ and agents’ mails and using it to estimate the probability of the deal winning.

Outline

Cleaning and Parsing emails (Data cleaning)

Parsing HTML mails
Removing Signature from emails
Processing Zoom invites
Processing calendar invites
Converting emails to conversations

Annotating emails/conversations (Data annotation)

Sentiment tagging (-2 to +2) : Need for tagging conversations and why deal outcome cannot be used.
Intent tagging : One or more intents tagged from a pool of 50 intents picked by consulting salespersons

Instrumentation

Pipeline
- Ingestion : Kafka consumer, followed by preprocessing and language prediction
- Population and generation of conversations
- Sentiment prediction : Get embedding and predict conversation sentiment
- Use conversation sentiment scores and other features to predict deal sentiment
Multi-account models : Using clustering to pick models