Who can use this: Business admin
Available on: Gong Foundation
Question-based AI Trackers consume Gong credits based on the amount of call and email data analyzed.
You can create and publish as many AI Trackers as needed.
Well-designed AI Trackers help reduce unnecessary processing and improve the quality of AI Tracker insights.
This guide explains how to create AI Trackers that:
Analyze only relevant calls and emails
Reduce unnecessary Gong credit consumption
Focus AI Tracker analysis on high-value business workflows
Plan the AI Tracker before building it
Clearly defining the AI Tracker purpose helps reduce unnecessary analysis and improve the relevance of AI Tracker results.
Define the following before creating the AI Tracker:
What business concept, customer behavior, or conversational topic the AI Tracker should identify
Whether the AI Tracker should analyze calls, emails, or both
Which side of the conversation the AI Tracker should track:
Our rep
Customer
Any party
Which conversations are relevant to the AI Tracker
Whether filters are needed to narrow the analysis scope
Whether the AI Tracker should analyze the entire conversation or only part of the call
What additional details may help improve tracking accuracy
Create focused AI Trackers
AI Trackers work best when they focus on a specific business signal or workflow.
Examples of focused AI Trackers include:
Pricing objections during proposal-stage calls
Product feedback for a specific product line
Customer churn risk during renewal discussions
Competitor mentions during discovery calls
Focused AI Trackers are easier to validate and usually consume fewer credits than broad AI Trackers.
Avoid overly broad AI Trackers
Broad AI Trackers may analyze large amounts of unrelated activity and consume credits unnecessarily.
Avoid AI Trackers that:
Monitor too many unrelated concepts
Analyze all company calls and emails without filters
Combine multiple unrelated business goals into one AI Tracker
Example of an overly broad AI Tracker:
“Identify customer concerns, pricing objections, competitor mentions, and product feedback.”
Broad AI Trackers are harder to validate, may return less relevant results, and can consume large amounts of Gong credits.
Decide when email analysis is necessary
Selecting Calls and emails increases the amount of processed activity and may consume more credits.
Use Calls only when the relevant business signal mainly appears in spoken conversations.
Examples include:
Pricing objections discussed during sales calls
Competitive discussions during discovery meetings
Customer sentiment during live conversations
Product feedback discussed during demos
Use Calls and emails only when the business signal commonly appears in both activity types.
Examples include:
Procurement discussions
Legal approval processes
Renewal communications
Product requests discussed over email
Apply filters
Filters help narrow AI Tracker analysis to relevant conversations.
Applying filters helps:
Reduce Gong credit consumption
Improve AI Tracker relevance
Focus AI Tracker analysis on the correct audience or workflow
AI Trackers without filters may analyze large amounts of unrelated activity and consume credits unnecessarily.
AI Tracker filter examples
Available filters include:
Call participants, including specific users, teams, or managers
CRM filters for accounts, opportunities, contacts, or leads
Deal stage, either during the call or the current deal stage
Account type or account tier
Account industry
Opportunity type
Close date
Deal size
Call duration
Call type, including web conference, inbound, or outbound calls
Conversation engagement metrics such as talk ratio or questions asked
Use multiple filters for more precise targeting
Combining multiple filters helps narrow AI Tracker analysis to the most relevant conversations.
Example:
Enterprise accounts
Proposal-stage opportunities
AE team
This filter combination limits analysis to enterprise pricing conversations handled by account executives during proposal discussions.
Match filters to the AI Tracker purpose
The filter strategy should match the purpose of the AI Tracker.
Examples:
If an AI Tracker supports a specific sales play, filter to the deal stage where that sales play is relevant
If an AI Tracker is used for coaching a specific team, filter to that team’s calls
If an AI Tracker monitors a specific product, filter to opportunities associated with that product
Understand how filters apply to emails
Selecting both Calls and emails allows the AI Tracker to analyze email activity in addition to calls.
Most available filters also apply to emails, including:
CRM filters
Participants
Account name
Date
Scope
In combined call and email analysis, the Call title filter also applies to email subject lines.
The following filter categories only apply to calls:
Call info
Interaction during call
Questions
Webcam
Screen share
Collaboration
These filters do not affect email analysis.
Reduce unnecessary email analysis
Users with captured email activity may send large volumes of outbound emails.
AI Trackers configured for both calls and emails may analyze irrelevant email activity if filters are too broad.
To narrow the analysis scope, consider using filters such as:
Deal stage
Associated with an opportunity
These filters help reduce analysis on irrelevant email activity.
Review AI Trackers regularly
Business priorities and workflows change over time, and AI Trackers should be reviewed regularly.
Review AI Trackers quarterly to:
Remove outdated AI Trackers
Refine filters
Improve AI Tracker targeting
Reduce unnecessary analysis
Regular maintenance helps improve AI Tracker quality and optimize Gong credit consumption.