The Best Product Intelligence Tools for Gong: What Your CRM Calls Are Really Trying to Tell You

Every product leader I know says the same thing:

“Our sales team logs everything in Gong—why does it still feel like nobody knows what customers want?”

Because recordings ≠ clarity.
Transcripts ≠ truth.
And CRM notes ≠ product intelligence.

Gong is phenomenal at capturing calls. It's the most valuable resource for the rest of the company, not just sales.
But it was never designed to do the one thing product teams desperately need:

Turn hours of customer conversations into actual product decisions.

That’s where product intelligence tools step in.

Below is a founder-who’s-been-through-this breakdown of:

  • What types of product intelligence tools integrate with Gong

  • How product teams actually use them

  • What’s missing from the market

  • Where Arkweaver fits into the ecosystem (without turning this into an ad)

Let’s break it down.

Why Gong Alone Isn’t a Product Intelligence Tool

Gong organizes calls beautifully. 
It coaches reps.
It helps managers forecast.

But for product teams, Gong is a search bar, not a system. We dive deeper into how to augment Gong most effectively here.

Here’s the reality:

  • You can’t see top requested features across calls.

  • You can’t map prospects → needs → product gaps.

  • You can’t easily quantify who cares about what, or how often.

  • You definitely can’t generate PRDs, user stories, or issue tickets from it.

So the market has responded with tools promising “product intelligence on top of calls.”

Some are great.
Some are duct tape with good branding.
Some only solve 10% of the job.

Here’s the landscape.

The Four Categories of Gong-Compatible Product Intelligence Tools

1. Call-Mining & Conversation Analytics Add-Ons

These tools enrich Gong with call-centric product insights.

Examples:

  • A few small platforms focused on keyword mining + tagging

  • Internal tools built by ops teams

What they do well:

  • Keyword spotting

  • Basic trend detection

  • Coaching insights

What they don’t:

  • Real prioritization

  • Mapping requests to accounts and revenue

  • Translating calls into buildable artifacts

  • Cross-functional alignment

Useful but not enough for real product teams.

2. Product Feedback Collectors

These tools centralize feedback from multiple places (calls, support, surveys, CSM notes).

Examples:

  • Productboard

  • Dovetail

  • Canny

Pros:

  • Good at collecting scattered feedback

  • Decent tagging/organization

  • Suitable for PMs who love manual triage

Cons:

  • Gong integration is typically shallow or manual

  • Still requires humans to categorize everything

  • No automated “what to build and why”

Better than spreadsheets. Still a heavy lift.

3. Product Analytics Platforms

Tools that show you what people do, not what they say.

Examples:

  • Amplitude

  • Mixpanel

  • Heap

Strength:

  • Deep quantitative analytics

  • Journey analysis

  • Segmentation

Weakness:

  • Zero insight into why customers behave the way they do

  • No integration with Gong call intent

  • Doesn’t reduce product team workload

Great for usage data—not for understanding customers.

4. AI Product Intelligence Platforms (New Category)

This is the category Arkweaver sits in.

These tools combine:

  • Gong transcripts

  • Support tickets

  • CRM notes

  • Product analytics

  • Customer metadata

And automatically turn all of that into:

  • Prioritized feature lists

  • Product briefs/specs

  • User stories

  • GTM enablement

  • Roadmap insights

  • Persona-specific analysis

  • Feedback → decisions → execution

This is the category product teams increasingly want because:

  • AI has made engineering fast

  • Product is now the bottleneck

  • Companies spend $150B on product labor

  • Everyone is drowning in unstructured feedback

  • Gong contains truth, but no system to operationalize it

Arkweaver is the first system built to treat Gong transcripts as the core dataset for product teams—not an afterthought.

So… What Are Your Actual Options?

Here’s the blunt product founder summary:

Call MiningNiche call-analyzersShallowCoaching, keyword trendsProduct decisionsFeedback CollectorsProductboard, DovetailBasic/manualCentralizing feedbackPrioritization, automationProduct AnalyticsAmplitude, MixpanelNoneUsage insightsCalls, qualitative insightAI Product IntelligenceArkweaverDeep (Gong → Product Decisions)Full product workflowVery early-stage teams

If your job is to actually build the right product, category 4 is the only one that solves the entire workflow.

Final Take: Gong Is the Input—Not the System

If your company uses Gong but feels blind on product insights…
you’re not behind—you’re normal.

Teams built Gong → Salesforce → Slack → Linear
but never built the product intelligence layer in between.

That’s the missing system.
And that’s why this category is exploding.