AI Theme Spotter is an AI agent that surfaces patterns and trends across customer conversations, identifying recurring insights that would be impossible to spot manually. With AI Theme Spotter, you gain a clear view of the aggregate voice of the customer so you can make informed strategic decisions.
What AI Theme Spotter solves for your team
Sales and revenue leaders often struggle with limited visibility into customer sentiment at scale, scattered insights across individual calls, and a lack of aggregated qualitative data. AI Theme Spotter solves these challenges by:
Uncovering patterns and emerging themes across large datasets
Providing qualitative insights that inform strategy
Enabling proactive identification of concerns, objections, and opportunities
Delivering scalable voice-of-customer analysis by segment
Use cases
AI Theme Spotter gives your team a fast way to see what customers are saying at scale, so you can:
Spot emerging pain points that affect multiple segments
Track common objections and concerns across deals
Monitor reactions to pricing or packaging changes
Collect product gaps and feature requests to inform roadmaps
Compare themes by region, industry, or deal stage
How it works
Start by selecting your business question. You’ll see suggested questions based on Gong’s pretrained smart trackers, and company specific questions based on your company’s smart trackers.
So, for example, you’ll see suggested general business questions like “What are the most common business goals? and “What are the most common objections?” as well as company-specific questions, based on your company’s custom trackers that may be related to new features, campaigns, competitors, and your company's unique terminology.
Choose call filters to define the segment that you want to analyze. Once filters are set, Gong analyzes the calls in the defined segment to surface recurring themes, and then clusters the themes into clear, named themes.
View a quick summary of a theme or drill into individual themes to see supporting evidence and links to source calls. You can also download the data as a CSV for further analysis.