Koji vs Heap: AI Customer Research vs Autocapture Product Analytics (2026)

TL;DR: Heap is the leading autocapture product analytics platform — drop one snippet, and Heap records every click, page view, and form submission retroactively. Koji is an AI-native customer research platform that runs AI-moderated voice and text interviews and synthesises thematic reports automatically. They answer different questions: Heap shows you what users did across millions of events; Koji shows you why they did it in their own words. Most modern product teams need both. Koji starts at €29/month self-serve. Heap offers a Free tier up to 10,000 monthly sessions, with Growth pricing reported at roughly $1,000/month and Pro/Premier on custom contracts.

Heap's pitch — "no instrumentation needed" — is genuinely the right call for product teams whose engineers have no bandwidth to define events every sprint. But once Heap shows you a 47% drop-off at step 3 of onboarding, you still need to know why. Autocapture cannot answer that. Heap's Illuminate AI clusters behavioral patterns; it does not interview the humans behind the clicks. That is the gap Koji fills.

This guide compares both platforms feature-by-feature, explains where each genuinely wins, and gives a decision framework so you can avoid double-paying for overlapping coverage.

Quick comparison table

| Feature | Koji | Heap | |---|---|---| | Primary use case | AI-moderated customer interviews and qualitative research | Autocapture behavioral product analytics | | Answers | "Why did they do that?" | "What did they do, and where?" | | Data source | Voice/text conversations + structured questions | Autocaptured DOM events from web/mobile SDKs | | Instrumentation | None — drop an interview link | One JavaScript snippet, then define events retroactively | | AI voice moderator | Yes — ElevenLabs voice with real-time probing | No — Heap does not talk to users | | AI analysis | Yes — thematic clustering, one-click reports | Yes — Sense AI / Illuminate for pattern detection | | Talks to non-users | Yes — share link with churned users, prospects, anyone | No — only users on your instrumented product | | Surveys | Yes — blended with interviews, 6 question types | Limited — relies on integrations like Sprig or Survicate | | Session replay | No (not the use case) | Yes — add-on cost on Pro/Premier | | Free tier | 10 credits at signup | Free up to 10,000 monthly sessions, 6 months data | | Entry plan | Insights — €29/month, 29 credits | Growth — approximately $1,000/month | | Self-serve | Yes, fully | Yes for Free; paid plans require annual contract negotiation |

The core difference: events vs. conversations

Heap is a behavioral analytics platform. Its defining innovation is autocapture: drop one snippet on your site, and Heap silently records every DOM event — every click, scroll, form submission, page view — without an engineer instrumenting anything. Later, a PM or marketer can point at any element in the UI and retroactively define it as an event. That removes the single biggest bottleneck in legacy analytics: getting engineering to track the right events before the question is asked.

Koji is a qualitative research platform. It does not listen to your event stream — it conducts AI-moderated interviews. Drop a Koji link into an email, a Slack message, or a post-purchase confirmation page, and the AI moderator runs a 10–15 minute conversation, asks your discussion guide questions, probes vague answers in real time, and returns a thematic report with verbatim quotes.

The metaphor: Heap is a security camera that records everyone who walks through the store. Koji is the friendly clerk who asks why each customer walked back out empty-handed.

What Heap is genuinely best at

Heap's autocapture model is a category leader. We do not recommend skipping product analytics — and if your engineering team has no bandwidth to instrument events, Heap is the cleanest choice. Where Heap wins:

• Retroactive event definition. A PM has a new question on Tuesday? Define the event on Tuesday and Heap shows you data going back months. Amplitude and Mixpanel typically cannot do this without prior instrumentation.
• Funnel and retention dashboards. The classic "which onboarding step has the worst drop-off" chart is Heap's sweet spot.
• Account analytics (Pro tier). B2B SaaS users can roll user events up to the account level — useful for CSMs tracking workspace health.
• Session replay add-on. Watch a single user's session frame-by-frame to debug a UX bug.
• Engineering-light setup. One snippet. No event taxonomy meetings.

If your job is "I need to see which funnel step is breaking without asking an engineer for help" — buy Heap. Koji does not solve that problem.

What Koji is genuinely best at

Koji answers the questions autocapture cannot:

1. Why is the funnel breaking?

Heap will tell you that 47% of new users drop off when prompted to invite teammates. Koji asks 20 of those users why, with an AI moderator that probes in real time. You will hear "I want to evaluate this solo before pitching it to my team" or "I don't trust your product enough yet to put my colleagues' emails in." Those are roadmap insights. Heap only shows the drop-off bar.

2. Talking to people not on your product

Heap can only see users who loaded your snippet. The much larger group — bouncers from your homepage, churned users you removed access for, prospects researching a buy — are invisible to autocapture. Koji is built to reach them via shared links, CSV imports, or panel recruiting through participant recruitment platforms.

3. Real-time probing during the conversation

Koji blends 6 structured question types — open-ended, scale, single-choice, multiple-choice, ranking, yes/no — with AI follow-ups in the same session. Ask "On a 1–10 scale, how clear was the value prop?" and immediately probe "You gave it a 4 — walk me through what was confusing." Heap's survey integrations cannot probe; they fire static questions and move on.

4. Generative and discovery research

For genuinely generative work — when you don't yet know what events to track — autocapture is the wrong starting point. You need conversations first. See the jobs-to-be-done interview guide for the methodology.

5. Churn and win/loss

Win/loss interviews and churn interviews cannot be done via autocapture. They require talking to humans. Heap shows you that users churned. Koji explains why.

Where Heap's qualitative features fall short

Heap has invested in AI features like Sense AI and Illuminate — they cluster behavioral patterns and surface anomalies. These are excellent, but they remain event-based. Where Heap is structurally weak for research:

• No voice modality. Heap is event-stream only. There is no equivalent to Koji's ElevenLabs voice interviews.
• No async interview format. Koji participants take an interview on their own schedule via a link. Heap surveys require the user to be on your site.
• No structured discussion guide. Heap surveys are short polls — not 10–15 minute discussion guides with branching follow-ups.
• Limited reach beyond your product. If a user is not on a Heap-instrumented page, they don't exist in Heap.
• No participant recruitment workflow. Heap assumes the user is already there.

If you tried to run a discovery study using only Heap, you would get pattern-rich behavioral data with zero verbatim quotes and no probing. That is not Heap's job — and it shouldn't be.

Pricing comparison

| | Koji | Heap | |---|---|---| | Free tier | 10 credits at signup, self-serve | Free up to 10,000 monthly sessions, 6 months data history | | Entry plan | Insights — €29/month, 29 credits, self-serve | Growth — approximately $1,000/month, annual contract | | Mid plan | Interviews — €79/month, 79 credits | Pro — custom pricing, contract required | | Enterprise | Custom | Premier — custom pricing | | Cost driver | Per-credit (1 text chat = 1 credit, 1 voice = 3 credits) | Sessions + add-ons (Session Replay, AI features) | | Hidden costs | None | Session Replay, AI modules, session overages | | Annual commitment | None — self-serve monthly | Required on Growth and above |

For a small product team, Koji at €29–€79/month is a complete research stack with no annual commitment. Heap is genuinely free at the smallest tier, then jumps to a roughly $1,000/month annual contract for Growth. The two budgets do not overlap — they fund different jobs.

Decision framework

Use Heap when:

• You need autocaptured behavioral events without engineering effort
• You want retroactive event definition — ask new questions, see historical data
• You need funnel analysis, retention curves, or session replay
• Your team has more PM/marketing bandwidth than engineering bandwidth
• You are tracking installed users on web or mobile

Use Koji when:

• You need to understand why a behavior is happening
• You are doing customer discovery, JTBD, or generative research
• You need to talk to churned users, bouncers, or prospects (people not on your product)
• You need structured questions plus open probing in a single session
• You need a thematic report from 20 interviews in 48 hours

Use both when:

• You are building any meaningful SaaS or consumer product
• You want quant data to flag the problem and qual data to explain the cause

A workflow that uses both

The pattern we see from high-performing teams:

1. Heap flags a problem. Autocaptured data shows step 3 of onboarding broke this week — drop-off jumped 8 points.
2. Koji explains it. Ship a Koji study to the last 50 users who hit step 3 and dropped. The AI moderator asks "walk me through what you saw on the team invite screen" and probes when answers are vague. Two days later, a thematic report lands with verbatim quotes.
3. You ship a fix. The fix is informed by both what broke (Heap) and why (Koji).
4. Heap validates. Re-check the funnel a week post-ship. Behavior moves.

That full quant-qual-quant loop is the operating model that produces compounding product wins.

The market context

According to industry research, AI-powered research increased by 32% across product teams in 2025, and ResearchOps automation is rapidly becoming a baseline expectation for any product organization larger than a seed-stage startup. Teams that pair behavioral analytics with AI-moderated qualitative — instead of choosing one or the other — are the ones shipping informed roadmaps in 2026.

Heap remains a category leader for autocaptured behavioral analytics. Koji is the category leader for AI-moderated qualitative research. The teams winning in 2026 use both.

Try Koji free

If your team has Heap installed and you have ever stared at a drop-off chart asking "but why are people leaving?" — that is the question Koji was built to answer. Start a free study with 10 credits at signup. Pull a list of churned users from Heap, import them into a Koji study, and run an AI-moderated interview campaign by the end of the week.

For more, read Koji vs Amplitude, Koji vs Mixpanel, or the user research complete guide.