Introducing Machine Learning

Objective

After completing this lesson, you will be able to describe the key concepts, techniques, and applications of machine learning

Machine Learning

A woman checking the screen and choosing options.

Use Artificial Intelligence (AI) to understand the business. Machine Learning is a field of AI that enables business systems to learn patterns from operational data and make educated predictions or decisions.

With machine learning, understand data patterns and sell smarter. Spend more time selling, increasing forecast accuracy, and improving relationships. Create and train a model to make predictions and identify patterns and trends to act on.

SAP Sales Cloud Version 2 uses Intelligent Sales to take everyday sales data and create and train machine learning models to identify patterns and trends, enabling sales predictions.

Let’s check the Machine Learning key features in Sales Cloud Version 2.

Machine Translation

This machine learning key feature automatically translates incoming emails from the source language to the logon language, enabling recipients to understand and engage with the content in their natural language.

The Emails page shows all emails, highlighting the last email, the message for the user. It also highlights the “Show Translation” option.

Key Features:

Automate translations from the source language to the logon language.

Business Benefit:

  • Language isn’t a factor in doing business.

  • Speed up the processing and initial response times.

Sentiment Detention for Natural Language Processing (NLP) Classification

The NLP classification feature includes the "sentiment" output field, which determines whether the vocabulary used in a survey is positive or negative and its degree. The sentiment detection works on emails and surveys.

The Survey Result page shows the Insights tab, including windows for total responses captured, average score, total questions, responses to each question, most used entity, most frequently occurring, and notes for sentiment analysis.

Key Features:

  • The NLP classification feature includes the "sentiment" output field, which determines whether the vocabulary used in a survey is positive or negative and its degree. The sentiment detection works on emails and surveys.
  • The sentiment value from surveys indicates the overall emotion. The degree of the sentiment indicates how emotionally intense the content is.

 Business Benefit:

  • If the feedback is happy or sad, the sales team can quickly identify it.

  • Negative sentiment surveys and emails enable remedial actions.

Profanity Check in Email

The system analyzes profane words and promptly gives warnings when it detects them, keeping a professional and respectful communication environment.

The page shows the confirmation message window with the options to send or cancel it.

Key Features:

Check emails for sensitive words.

Business Benefit:

Guarantee professional interactions with prospects and customers.

 

Business Text Intelligence

The New Opportunity page shows the overview, timeline, and insights. It highlights the latest note to create an appointment.

Key Features:

Use Natural Language Understanding (NLU) to get actionable insights for appointments from note text using business text intelligence.

Business Benefit:

The system suggests appointments from notes in Leads and Opportunities.

Business Product Recommendation

The Opportunity tab shows the recommended products with two options.

Key Features:

This machine learning feature proposes products for upsell based on historical data for won opportunities.

Business Benefit:

It offers a customer-specific predictive model that the sales team uses to upsell customers quickly.

Lead Intelligence

The Lead Intelligence machine learning feature uses historical Lead data to create a Lead score for open Leads. The Lead score indicates the likelihood that a Lead will convert to an Opportunity. When using Lead scoring, focus on a tailored list of prospects likely to become customers.

Lead Intelligence and Lead Scoring

Let’s watch this video about Lead Intelligence.

Key Features:

  • Lead intelligence takes attributes from the historical Leads to create intelligent scores. A higher score makes the Lead more likely to convert into an Opportunity.
  • The machine learning service's lead score ranges from 0 to 99. The scores are also color-coded from 0 to 50 (red), interpreted as less likely to win. From 51 to 75 is yellow, interpreted as likely to win. From 75 to 99 is green, interpreted as very likely to win.

Business Benefit:

  • The sales team focuses on Leads that are likely to convert.
  • It helps prioritize and effectively use resources for a good business outcome.

Deal Intelligence

The Deal Intelligence machine learning feature uses historical data from existing Won/Lost Opportunities to train the model. As a result, the system builds a customer-specific predictive model and applies it to score Opportunities. The higher the score, the better the chance of winning the Opportunity.

Deal Intelligence and Opportunity Scoring

Let’s watch this video about Deal Intelligence.

Key Features:

  • It helps to determine which deals close, which don’t, and which go either way.
  • Each opportunity gets a unique win score that supports the sales pipeline management and helps teams focus on opportunities likely to close.

Business Benefit:

  • Opportunity scoring helps the sales team prioritize deals based on the winning probabilities.
  • It helps focus on the right Opportunities and improves management of the pipeline/forecast.

Opportunity Scoring

The following demonstration shows how to convert a previously created Lead to an Opportunity, note the Opportunity score, and open the Opportunity to see more details.

Summary

This section offered instruction on these fundamental SAP Sales Cloud Version 2 features:

  • Machine Learning Overview: Machine Learning in SAP Sales Cloud Version 2 enables business systems to learn patterns from sales data, make predictions, and improve sales forecasting and customer relationships.
  • Key Features: Includes automated machine translation of emails, sentiment detection in surveys and emails via Natural Language Processing (NLP). It also includes profanity checks in communications and business text intelligence that extracts actionable insights from notes.
  • Product and Lead Intelligence: It uses historical data to recommend products for up-selling, and scores leads based on their conversion likelihood, helping sales teams focus on high-potential prospects.
  • Deal Intelligence: Analyzes past won/lost opportunities to score current deals and offers predictive insights into the likelihood of winning.
  • Business Benefits: Improves sales efficiency by automating language translation and detecting customer sentiment. It guarantees professional communication, focusing on leads, and improving forecasting accuracy with data-driven insights.