Pelin vs Heap: Qualitative Insights vs Behavioral Analytics

When product teams need to understand their customers, they face a fundamental question: Should we analyze what users do (behavioral data) or what they say (qualitative feedback)? The best teams know the answer is both—but the tools you choose shape how effectively you can combine these perspectives.

This comparison breaks down Pelin and Heap, two tools that approach customer understanding from different angles, to help you decide which one fits your team's needs.

Quick Comparison

What Pelin Does

Pelin is an AI-powered customer insights platform that automatically analyzes qualitative feedback from multiple sources. Instead of manually tagging support tickets or reading through call transcripts, Pelin's AI does the heavy lifting.

Data Sources Pelin Connects To:

• Customer support: Intercom, Zendesk, Freshdesk
• Sales calls: Gong recordings
• Communication: Slack channels, Gmail
• Product tools: Linear, Jira
• Surveys: Typeform
• Documents: Notion, Confluence, Google Drive

What Pelin Surfaces:

• Pain points and customer frustrations
• Feature requests with prioritization signals
• Positive feedback patterns
• Confusion points in your product
• Churn risk indicators
• Competitive mentions
• Power user behaviors

The key value proposition is automation. Rather than having a PM spend hours reading support tickets to find patterns, Pelin clusters similar feedback, detects sentiment, and presents actionable insights in real-time.

What Heap Does

Heap is a digital insights platform focused on behavioral analytics. It uses "auto-capture" technology to automatically track every user interaction without requiring manual event implementation.

What Heap Captures:

• Page views and navigation paths
• Button clicks and form interactions
• Feature usage patterns
• Conversion funnels
• Session recordings
• User segments and cohorts

Key Heap Capabilities:

• Retroactive analysis (analyze events from before you defined them)
• Visual funnel building
• Path analysis for user journeys
• Retention and engagement metrics
• A/B test integration
• Mobile and web tracking

Heap's magic is in its auto-capture approach—you install one snippet, and it starts collecting everything. Need to analyze a button that shipped six months ago? Heap already has the data.

Head-to-Head: Different Problems, Different Strengths

Understanding "What" vs "Why"

Heap excels at: Showing you exactly what users do in your product. You'll see that 47% of users drop off at step 3 of your onboarding flow, or that power users engage with feature X 3x more than average.

Pelin excels at: Explaining why users behave the way they do. You'll learn that users drop off at step 3 because the integration setup is confusing, or that users love feature X because it saves them 2 hours per week.

Data Collection Approach

Heap: Requires installing a tracking snippet in your product. Auto-captures events going forward. Focused on in-product behavior.

Pelin: Connects to existing tools via integrations. No product code changes needed. Focused on customer voice across all touchpoints.

Analysis Methodology

Heap: Query-based exploration. You ask questions like "show me the conversion funnel for users from Google ads" or "compare retention between enterprise and SMB customers."

Pelin: AI-driven discovery. Pelin proactively surfaces patterns you might not have thought to look for, like "enterprise customers in the healthcare vertical are mentioning compliance concerns 3x more this month."

Time to Value

Heap: Quick setup for basic tracking. Getting meaningful insights requires building funnels and segments, which can take time to configure well.

Pelin: Connect your existing tools (Intercom, Gong, etc.) and insights start flowing immediately. Less configuration, more discovery.

When to Choose Pelin

Pelin is the right choice if:

1. You're drowning in qualitative feedback. If your team has hundreds of support tickets, sales call recordings, or survey responses but no time to analyze them systematically, Pelin's AI analysis is transformative.

2. You need to understand customer voice at scale. When you've grown past the point where product managers can personally read every piece of customer feedback, automation becomes essential.

3. Cross-functional insights matter. Pelin connects support, sales, and product feedback into one view, helping teams see patterns that span departments.

4. You want proactive discovery. Pelin surfaces insights you didn't know to look for, which is particularly valuable for early warning signals like churn risk or emerging feature demands.

5. Your product decisions need customer context. If you're building roadmaps based on customer input, having AI-analyzed feedback with sentiment and prioritization helps make better decisions.

When to Choose Heap

Heap is the right choice if:

1. You need behavioral analytics foundation. Every product team needs to understand user behavior quantitatively. If you don't have a product analytics tool yet, Heap provides essential infrastructure.

2. You want retroactive analysis. Heap's auto-capture means you can analyze historical behavior without having instrumented specific events in advance.

3. Conversion optimization is a priority. If you're focused on improving signup flows, onboarding completion, or feature adoption rates, Heap's funnel analysis is purpose-built for this.

4. You need session-level detail. Heap's session recordings and user journey tracking provide granular visibility into individual user experiences.

5. Data warehouse integration matters. Heap can pipe behavioral data to your data warehouse for custom analysis alongside other business metrics.

Using Pelin and Heap Together

Here's the insight most comparison articles miss: these tools are complementary, not competing.

The ideal stack looks like:

• Heap tells you users drop off at step 3 of onboarding (the what)
• Pelin tells you users find the integration setup confusing (the why)
• Together they give you the complete picture: prioritized problems with quantified impact

A practical workflow:

1. Heap alerts you that trial-to-paid conversion dropped 15% this month
2. You investigate Heap data and see it's concentrated in the "data import" step
3. You check Pelin and find a cluster of support tickets about CSV import errors
4. Pelin shows these tickets come primarily from enterprise trials
5. You fix the bug, and Heap confirms conversion recovers

This combination—behavioral data pointing to problems, qualitative data explaining causes—is more powerful than either tool alone.

Pricing Considerations

Heap pricing is based on session volume. For high-traffic products, this can become expensive. The free tier has limitations on data history and features.

Pelin pricing is typically per-seat, making it more predictable but potentially expensive for large teams. The cost scales with team size rather than customer base.

Cost comparison factors:

• High-traffic B2C products may find Heap more expensive
• Large product teams may find Pelin more expensive
• Both tools offer enterprise plans with custom pricing

The Bottom Line

Choose Pelin if your primary challenge is understanding customer voice at scale—analyzing feedback, surfacing pain points, and making sense of qualitative data across multiple sources.

Choose Heap if your primary challenge is understanding user behavior quantitatively—building funnels, tracking feature adoption, and measuring conversion.

Choose both if you want a complete customer intelligence stack that answers both "what are users doing?" and "why are they doing it?"

For most growing product teams, behavioral analytics (Heap or alternatives) provides the quantitative foundation, while qualitative analysis (Pelin) adds the customer context that makes the numbers actionable. The question isn't really "Pelin vs Heap"—it's "which do we need first, and when do we add the other?"

Want to see how Pelin can help you understand your customer feedback at scale? Start a free trial and connect your existing tools to see AI-powered insights in minutes.