Leveraging Machine Learning for Intelligent Sales and Lead Scoring
Objective
After completing this lesson, you will be able to develop the skills to leverage machine learning techniques for enhancing sales strategies and optimizing lead scoring, enabling more accurate predictions and improved decision-making in sales processes.
Machine Learning Administration
An administrator can access the settings for various Machine Learning capabilities in SAP Sales Cloud Version 2.
As administrator you can configure, train and activate the Machine Learning models.
The administrators can configure the following Machine Learning capabilities using path User Menu → Settings → All Settings → Intelligence Service.
Lead Intelligence
With Lead Intelligence you can identify open Leads that have a high potential of conversion into an Opportunity. Historical data taken from the converted and declined Leads, is used to train the machine learning model. As a result, you get a customer-specific predictive model that is applied to provide users a scoring of Leads.
Open "Lead Score" tab to get started with Lead Intelligence.
Check the "Reediness Report" to analyze your Lead data to determine if you can get useful predictions for Lead scoring.
In addition to standard fields custom fields can also be added to machine learning scenarios to train the machine learning models, please ensure that extension fields have sufficient data volume before enabling it in the machine learning scoring scenario level, otherwise they will not have any impact.
Add, save and train the model .
Once the model is trained, activate the model.
Lead Intelligence
Important factors for an administrator to consider:
When you activate the Lead scoring model, the Lead scores display for the Leads. However, the scores don't show up until the initial scoring process is completed.
The Lead score popup display is updated daily. This update is triggered at midnight (based on the time zone of your data center).
The insights are available in the Leads score popup after the completion of the initial scoring run, depending on the data volume.
Now let's practice setting up Lead Intelligence scenario in the following simulation.
With Lead Intelligence you can identify if an Opportunity can be won or lost. Opportunity scoring uses the machine learning model trained on past sales data to predict the probability of winning a deal. Opportunity scoring helps your sales representatives prioritize their deals based on the winning probabilities.
Open "Opportunity Score" tab to get started with Deal Intelligence.
Check the "Reediness Report" to analyse your Opportunity data to determine if you can get useful predictions for deal scoring.
In addition to standard fields custom fields can also be added to machine learning scenarios to train the machine learning models, please ensure that extension fields have sufficient data volume before enabling it in the machine learning scoring scenario level, otherwise they will not have any impact.
Add, save and train the model .
Once the model is trained, activate the model.
Business Text Intelligence
Business Text Intelligence uses Natural Language Understanding (NLU) to get actionable insights for appointments from note text.
Open "Business Text Intelligence" tab to get started.
Add, save and train the model.
Once the model is trained, activate the model.
NLP Classification
The NLP Classification scenario includes the Sentiment output field that determines if the vocabulary used in the survey, is positive or negative and the degree of positivity or negativity.
Open "NLP Classification" tab to get started.
Add, save and train the model.
Once the model is trained, activate the model.
Product Recommendation
Product Recommendation machine learning model provides actionable insights. Sales representatives can use these recommendations to make quick upselling/cross-selling offers to customers.
Open "Product Recommendation" tab to get started.
Add, save and train the model.
Once the model is trained, activate the model.
Machine Translation
This machine learning capability provides automated translation of incoming emails from the source language to the logon language.
Open "Machine Translation" tab to get started.
Add, save and train the model.
Once the model is trained, activate the model
Profanity Check
Profanity Check machine learning capability enables detection of profane words, promptly issuing warnings in cases where such language is detected to maintain a professional and respectful communication environment.
