SugarPredict for Sell User Guide

Overview

Sugar Sell incorporates the artificial intelligence (A.I.) capabilities of SugarPredict to give you Predictive Insight into your lead and opportunity data and Sentiment Analysis for your customer calls.

With Predictive Insight, SugarPredict uses your lead, account, and opportunity data along with intelligence gathered from millions of other companies and contacts and introduces your Sugar leads and opportunities to A.I.-driven models to analyze and accurately predict who is most likely to become your next customer. The predictions are surfaced in Sugar via badges and scoring in dashlets and list views, making it easy for you to quickly benefit from the information at a glance, and enabling you to convert leads and close opportunities faster and more consistently.

With Sentiment Analysis, SugarPredict uses transcripts from your SugarLive call records and assigns them a positive, negative, or neutral sentiment based on the tone detected in the conversation. Both the agent's sentiment and the customer's sentiment are analyzed and given separate values. The sentiment evaluations are then surfaced via user-friendly SugarPredict icons and values throughout Sugar, making it easy for you to quickly benefit from the insights at a glance, and enabling you to identify areas of success and improvement to help your customers get what they need faster and more consistently.

This documentation covers the information specific to SugarPredict as it exists within Sugar Sell. For information explaining how to interact with lead, opportunity, or call records, refer to the Leads, Opportunities, and Calls documentation in the Sugar Sell Application Guide.

Prerequisites

For more information on SugarPredict prerequisites, please refer to the Getting Started with SugarPredict guide page.

Setting Up SugarPredict for Sell

For more information on setting up SugarPredict, please refer to the Getting Started with SugarPredict guide page.

Predictive Insight

SugarPredict Predictive Insight takes the guesswork out of lead prioritization, ideal customer profile (ICP) alignment, and opportunity scoring. SugarPredict uses your account data along with third-party data on millions of companies and contacts to accurately predict who is most likely to become your next customer. Predictions are based on similarity to your converted leads or closed-won opportunities. SugarPredict utilizes micro frontend (MFE) technology to surface the information in Sugar's Leads and Opportunities modules.

Depending on how your company uses Sugar's Accounts, Contacts, Leads, and Opportunities modules, you may have one or more Predictive Insight models enabled in your instance. For more information on each model, refer to the following sections:

Ideal Customer Profile Alignment: Compare the account's ideal customer profile (ICP) similarity to existing customers
Lead Prediction: Predict the likelihood of a lead converting
Opportunity Prediction: Predict the likelihood of an opportunity being closed-won

Ideal Customer Profile Alignment

When the Ideal Customer Profile Alignment model is enabled, your account and lead information is ingested into SugarPredict's pipeline, analyzed using your company-specific model, and displayed in the Lead Conversion Prediction dashlet. Clicking on "More info" displays either a list of similar accounts or a message explaining that "This lead does not match any existing accounts." When similar accounts are identified, up to five are displayed along with their location. Clicking on the name takes you to the account record.
similaraccounts

Lead Prediction

When the Lead Prediction model is enabled, SugarPredict provides lead conversion scoring for your lead records. The lead information is ingested into a prediction pipeline, analyzed using your company-specific model, and displayed in the Leads list view, List View dashlet, and the Leads Conversion Prediction dashlet.

Note: Leads that have a status of "Converted" or "Dead" will show these values instead of a prediction.

Leads List View

The Leads list view contains a Prediction column containing the lead scores for each record. Lead scores are displayed as temperature priority prediction badges. Prediction can be sorted and filtered upon in the Leads list view. Records without a conversion score will not display a badge in the list view.
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Note: Fields and columns associated with SugarPredict are automatically added in Studio when the feature is enabled in your instance. If you do not see the Prediction column in your list view, click the Gear icon to ensure it is available to you. For more information on configuring your list view columns, refer to the User Interface documentation in the Application Guide. The columns available to you are determined by your Sugar administrator. If the Prediction column is not available, your administrator will need to follow the steps in the Setting up SugarPredict section of this page.

Leads List View Dashlet

Like the Leads list view, the List View dashlet, configured for the Leads module, may contain a Prediction column displaying the lead score for each record. More information on this dashlet type can be found in the Dashboards and Dashlets page in the Sugar Sell Application Guide.
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Leads Conversion Prediction Dashlet

The Leads Conversion Prediction dashlet is available to add to the Leads record view dashboard. In the dashlet, you will find information specific to the record you are viewing in terms of the likelihood it will convert.
leaddashlet

If no prediction is shown, SugarPredict was unable to match the lead to SugarPredicts' global database of companies and contacts using the provided data. Please ensure that you have entered an accurate company name, website, and work email address. SugarPredict information is refreshed every twenty-four hours to ensure up-to-date information is displayed across all records. A newly created record will not display prediction information until the next prediction refresh.

Note: If you do not see the Lead Conversion Prediction dashlet, you may be viewing a custom dashboard and need to add it to your record view dashboard. For more information on adding dashlets, refer to the Dashboards and Dashlets documentation in the Application Guide. Default dashboards are managed by the dashboard owner, usually a sugar administrator. If the Prediction dashlet is not available and you are not able to access the "Add Dashlet" option when clicking the Floating Actions button, your administrator must follow the steps in the Setting up SugarPredict section of this page.

Conversion Score

A conversion score (e.g., "More likely to convert") and key performance indicators (KPI) are displayed at the top of the dashlet. The KPI data is displayed as a sentence similar to the following: "This lead is similar to leads that convert 72% of the time, which is 1.8X the average conversion rate." The information below describes these metrics in more detail:

This lead is similar to leads that convert 72% of the time: This is a direct comparison of the current, open lead to all your company's closed leads. SugarPredict detects similarities using the firmographic data (i.e., industry, location, size, status/structure, and performance) and conversion data collected from Sugar (e.g., lead source, Sugar Market score) and calculates the percentage of those similar leads that have either converted or have been marked as a dead lead.
- For example, your company has 1,000 closed leads and the lead record you are viewing is similar to 100 of them, 72 of which have converted and 28 have been marked dead.
Which is 1.8 times the average conversion rate: This is an indication of your company's conversion rate and how the lead looks in comparison.
- For example, your company's conversation rate is 40% and the lead you are viewing has the first KPI score of 72%. The calculation for the second KPI is .72 / .40 = 1.8.

Prediction Details

To further understand where this lead falls in the range of other leads, click the Prediction Details link. A dialog box appears that provides more information about the model and the current record as it relates to other lead records:

Overview: This shows the prediction categories available for your leads and explains the conversion multipliers for each category.
Driving factors: Lists the fields and data that are taken into account when creating the model and scoring each lead.
Current predictions: Displays the distribution of the currently open leads among the available prediction categories.

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Feedback

We want to know whether you find SugarPredict useful in your sales efforts. To provide feedback directly to our product team, please click the Feedback icon at the bottom of the Prediction dialog to complete a brief survey.

Note: Every feedback submission is reviewed by Sugar's product team, but a response is not guaranteed. For issues needing immediate response, please reach out to your Sugar partner, Customer Sucess Manager, or Sugar Support.

Opportunity Prediction

When the Opportunity Prediction model is enabled, SugarPredict provides opportunity close predictions for your records. The opportunity record's information is ingested into a prediction pipeline, analyzed using your company-specific model, and displayed in the Opportunities list view, List View dashlet, and the Opportunity Close Prediction dashlet.

Note: Opportunites that have a Sales Stage of "Closed Won" or "Closed Lost" will show these values instead of a prediction.

Opportunities List View

When Opportunity Prediction is enabled, the Opportunities list view contains a Prediction column displaying the scores for each record. Prediction scores are displayed as temperature priority prediction badges. Prediction can be sorted and filtered upon in the list view. Records without a conversion score will not display a badge in the list view.
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Note: Fields and columns associated with SugarPredict are automatically added in Studio when the feature is enabled in your instance. If you do not see the Prediction column in your list view, click the Gear icon to ensure it is available to you. For more information on configuring your list view columns, refer to the User Interface documentation in the Application Guide. The columns available to you are determined by your Sugar administrator. If the Prediction column is not available, your administrator must follow the steps in the Setting up SugarPredict section of this page.

Opportunities List View Dashlet

Like the Opportunities list view, the List View dashlet, configured for the Opportunities module, may contain a Prediction column displaying the scores for each record. More information on this dashlet type can be found in the Dashboards and Dashlets page in the Sugar Sell Application Guide.
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Opportunity Close Prediction Dashlet

The Opportunity Close Prediction dashlet is available to add to the Opportunities record view dashboard. When viewing an opportunity record, the dashlet shows the likelihood of the opportunity being closed-won.
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If no prediction is shown, SugarPredict was unable to match the opportunity to SugarPredicts' global database of companies and contacts using the provided data. Please ensure that you have entered an accurate company name, website, and business email address in the related account record. SugarPredict information is refreshed every twenty-four hours to ensure up-to-date information is displayed across all records. A newly created record will not display prediction information until the next prediction refresh.

Note: If you do not see the Opportunity Close Prediction dashlet, you may be viewing a custom dashboard and need to add it to your record view dashboard. For more information on adding dashlets, refer to the Dashboards and Dashlets documentation in the Application Guide. Default dashboards are managed by the dashboard owner, usually a sugar administrator. If the Prediction dashlet is not available and you are not able to access the "Add Dashlet" option when clicking the Floating Actions button, your administrator must follow the steps in the Setting up SugarPredict section of this page.

Win Score

A win score (e.g., "More likely to close") and key performance indicators (KPI) are displayed at the top of the dashlet. The KPI data is displayed as a sentence similar to the following: "This opportunity is similar to deals that are won 72% of the time, which is 1.8X the average conversion rate." The information below describes these metrics in more detail:

This opportunity is similar to deals that convert 72% of the time: This is a direct comparison of the current, open opportunities to all your company's closed opportunities. SugarPredict detects similarities using the firmographic data (i.e., industry, location, size, status/structure, and performance) and conversion data collected from Sugar and calculates the percentage of those similar opportunities that have been either closed-won or closed-lost.
- For example, your company has 1,000 closed records and the opportunity record you are viewing is similar to 100 of them, 72 of which have been closed-won and 28 have been closed-lost.
Which is 1.8 times the average conversion rate: This is an indication of your company's close rate and how the opportunity looks in comparison.
- For example, your company's close rate is 40% and the opportunity you are viewing has the first KPI score of 72%. The calculation for the second KPI is .72 / .40 = 1.8.

Prediction Details

To further understand where this opportunity falls in the range of other opportunities, click the Prediction Details link. A dialog box appears that provides more information about the model and the current record as it relates to other opportunity records:

Overview: This shows the prediction categories available for your opportunities and explains the conversion multipliers for each category.
Driving factors: Lists the fields and data that are taken into account when creating the model and scoring each opportunity.
Current predictions: Displays the distribution of currently open opportunities among the available prediction categories.

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Feedback

Utilize the feedback button to submit your suggestions or questions about SugarPredict. Your feedback is reviewed by Sugar's product team and a response is not guaranteed. For issues needing immediate response, please reach out to your Sugar partner, account manager, or Sugar Support.

Sentiment Analysis

SugarPredict sentiment analysis is surfaced in two fields within the Calls module: Agent Sentiment and Customer Sentiment. Each field is assigned a sentiment value and icon (positive/smiley face, neutral/neutral face, or negative/frowny face). Administrators can place these sentiment fields on the Calls record view, list view, and preview view, on the Timeline, Record View, and List View dashlets, and in Calls subpanels. The sentiment analysis fields will be visible to every user who can see call records (and has not been restricted via field-level controls) whether they are licensed for Sugar Serve or Sugar Sell. Additionally, the Agent Sentiment and Customer Sentiment fields are available for evaluation in SugarBPM in Sugar versions 12.0.0 and greater.
sentimentlistview

Prerequisites

SugarPredict Sentiment Analysis must be set up by an administrator in conjunction with SugarLive in your instance. For more information on setting up SugarLive, refer to the Amazon Web Services page in the Sugar Sell Administration Guide. The minimum requirements to have Sentiment Analysis enabled are:

Your instance must be on version 12.0 or higher.
Your instance must be licensed for Sugar Sell.
Your instance must have SugarLive enabled and configured with call transcripts set up via Contact Lens for Amazon Connect.
You must initiate your calls via Amazon Connect in SugarLive for Sugar to populate the sentiment fields.

Adding the Sentiment Analysis Fields

Follow the steps below to add the Customer Sentiment and Agent Sentiment fields to your Record View layout:

Go to Admin > Studio > Calls > Layouts > Record view.
Determine where in the layout you want the fields to display and add a new row or new panel as needed.
Locate the Customer Sentiment and Agent Sentiment fields in the left-hand side.
Click and drag the field to the desired location in the record view.
Click Save & Deploy.

sentimentfields

For more information on using sentiment analysis, refer to the Calls documentation in the Sugar Sell Application Guide.