{"site":{"name":"Koji","description":"AI-native customer research platform that helps teams conduct, analyze, and synthesize customer interviews at scale.","url":"https://www.koji.so","contentTypes":["blog","documentation"],"lastUpdated":"2026-09-23T23:58:08.198Z"},"content":[{"type":"blog","id":"77a33619-9c51-4e03-b34b-1300d56d1a81","slug":"koji-vs-enterpret-2026","title":"Koji vs Enterpret (2026): AI Customer Interviews vs Feedback Intelligence","url":"https://www.koji.so/blog/koji-vs-enterpret-2026","summary":"Koji vs Enterpret 2026 comparison: Enterpret is a sales-led customer feedback intelligence platform (estimated $30K-$100K+/yr) that ingests existing feedback from Zendesk, Intercom, app stores, NPS, and community channels and organizes it with an adaptive taxonomy and Context Graph. Koji is an AI-native customer research platform (free with 10 credits, then as low as €1 per qualified interview, voice as low as €3, on pay as you go) that generates new data by moderating async voice and chat interviews, asking dynamic follow-ups, supporting 6 structured question types, and auto-coding themes. Enterpret analyzes unsolicited feedback you already have; Koji produces solicited insight by asking new questions. Most teams use both: Enterpret as the listening layer, Koji for discovery, churn, win/loss, and concept testing.","content":"**TL;DR:** Enterpret is a customer feedback *intelligence* platform — it ingests the feedback you already collect (support tickets, app reviews, NPS verbatims, community posts) and uses AI to categorize it into an evolving taxonomy. Koji is an AI-native customer *research* platform — it runs moderated voice and chat interviews on demand, asks dynamic follow-ups, and codes themes across every conversation. Enterpret analyzes the past. Koji generates the future. They sit on opposite ends of the insight pipeline.\n\n## Quick answer: which one solves your problem?\n\n- **Choose Enterpret** if you have a high volume of inbound feedback flowing in from Zendesk, Intercom, app stores, NPS, and Slack, and you need one place to aggregate, tag, and trend it.\n- **Choose Koji** if you need to *go ask* customers something you do not have answers to yet — discovery, churn diagnosis, win/loss, concept tests, pricing reactions — and you want the AI to moderate the interviews and synthesize the themes.\n\nEnterpret is a listening layer for feedback you are already receiving. Koji is a research engine for questions you have not asked yet. The difference matters: no amount of taxonomy can extract an answer from feedback nobody ever gave you.\n\n## What Enterpret actually does\n\nEnterpret is a unified customer feedback intelligence platform. It connects to the channels where unsolicited feedback already lives — Zendesk, Intercom, Slack, Twitter/X, app store reviews, community forums, and NPS/CSAT survey verbatims — and consolidates them into a single source of truth. Its core strengths:\n\n- **Adaptive taxonomy.** Enterpret builds a continuously evolving categorization that reclassifies feedback as your product language shifts, avoiding the quarterly taxonomy rebuilds that plague legacy text analytics.\n- **Context Graph.** It connects each feedback signal to customer segment, lifetime value, lifecycle stage, and product area, so you can quantify which segments are asking for what.\n- **Sentiment and topic clustering**, natural-language search, dashboards, alerts, and an MCP server that lets Claude or ChatGPT query the feedback corpus programmatically.\n\nEnterpret does not publish pricing; it is a sales-led, enterprise-tier product. Industry reports peg annual contracts in the **$30,000–$100,000+** range depending on data volume. Reviewers consistently praise its aggregation power but note a meaningful learning curve given the breadth of functionality.\n\nThe fundamental constraint: **Enterpret can only analyze feedback that already exists.** If your churned customers never wrote a ticket explaining *why* they left, that reason is invisible to any aggregation tool — there is nothing to aggregate.\n\n## What Koji does differently\n\nKoji is built for the other half of the pipeline: generating primary research data that did not exist five minutes ago. You describe what you want to learn, and Koji's AI moderates [async voice and chat interviews](/docs/ai-moderated-interviews), asking real-time follow-up probes based on what each respondent says — not a fixed script.\n\n- **AI-moderated interviews** at scale, in 30+ languages, with [dynamic probing](/docs/how-ai-interviewers-work) that digs into the *why* behind every answer.\n- **Six structured question types** — open_ended, scale, single_choice, multiple_choice, ranking, and yes_no — so a single Koji study captures both the quantitative measure and the conversational reasoning behind it. (See the [structured questions guide](/docs/structured-questions-guide).)\n- **Automatic thematic analysis** across every transcript in a study, with [themes and patterns](/docs/understanding-themes-patterns) surfaced and supported by verbatim quotes.\n- **One-click reports** and an [AI consultant](/docs/understanding-the-ai-consultant) you can interrogate about your findings.\n- An [MCP server](/docs/mcp-overview) so you can launch studies and pull insights from Claude, Cursor, or your own tooling.\n\nKoji is transparent and self-serve: start **free** with 10 credits and no card, then interviews are **as low as €1 per qualified interview** and **€3 per qualified voice interview**. Start with pay as you go. No subscription needed, and volume pricing, plans and custom Enterprise are there when you want them. You pay only for the interviews your study actually uses, with no seats and no minimums. A built-in quality gate means a conversation scoring below 3 out of 5 is free.\n\n## Head-to-head comparison\n\n| Dimension | Enterpret | Koji |\n|---|---|---|\n| Category | Feedback intelligence (analyze existing feedback) | AI research platform (generate new interviews) |\n| Core input | Tickets, reviews, NPS, community, Slack | Customers answering moderated interviews |\n| Asks follow-up questions | No — it tags what was already said | Yes — real-time AI probing |\n| Structured + qualitative in one study | No | Yes — 6 question types |\n| Thematic analysis | Yes, across inbound channels | Yes, across interview transcripts |\n| Best for | VoC aggregation, trend monitoring | Discovery, churn, win/loss, concept/pricing tests |\n| Pricing | Sales-led, ~$30K–$100K+/yr | Free, then from €1 per qualified interview, up to custom Enterprise |\n| Time to first insight | Days to weeks (integration + taxonomy) | Hours |\n\n## The real distinction: solicited vs unsolicited insight\n\nThis is the heart of the comparison. Enterpret is exceptional at making sense of **unsolicited** feedback — the steady stream customers volunteer through support and reviews. But unsolicited feedback is biased toward the loudest moments: bugs, outages, and billing complaints. It rarely tells you why a prospect chose a competitor, what nearly stopped someone from upgrading, or how a brand-new concept lands.\n\nKoji produces **solicited** insight — you choose the question, the audience, and the moment. That is why teams run Koji for the high-stakes questions where waiting for inbound feedback is not an option: [win/loss interviews](/docs/win-loss-analysis-guide), churn diagnosis, and pre-launch concept validation.\n\n## What the 2026 data says\n\nThe research function is becoming strategic, and speed is the differentiator:\n\n- The share of organizations where research is essential to **all levels of business strategy nearly tripled in a year — from 8% in 2025 to 22% in 2026** (Qualtrics 2026 Market Research Trends).\n- **63% of teams** cite time and bandwidth as their top research constraint, and **39%** struggle to recruit participants in time (State of User Research 2026). AI-moderated interviewing directly attacks both.\n- **Customer interviews remain the #1 research method at 86% adoption**, ahead of usability testing (84%) and surveys (77%) — primary conversations still beat passive listening.\n- More than half of researchers (**53%**) now use AI regularly, and Qualtrics found teams *not* using AI are **4x more likely to lose organizational influence**.\n\nThe takeaway: aggregating existing feedback is table stakes. The strategic edge in 2026 comes from how fast you can ask a new question and get a synthesized, defensible answer — which is exactly Koji's design center.\n\n## Do you need both?\n\nOften, yes — and they do not overlap. Keep Enterpret as the always-on listening layer for inbound feedback at scale. Add Koji whenever you need to *initiate* a conversation: validate what the inbound data is hinting at, interview the churned accounts that never filed a ticket, or pressure-test a concept before you build it. Enterpret tells you *what people are already saying*; Koji lets you *ask the question nobody has answered yet*.\n\nIf you only have budget for one and you are a startup or a lean product team that does not yet have a firehose of inbound feedback, start with Koji — you can run real research this week for the price of a team lunch. If you are an enterprise drowning in inbound tickets and reviews, Enterpret earns its seat — and Koji becomes the scalpel for the questions aggregation cannot answer.\n\n## Try Koji free\n\nKoji turns a research question into synthesized insight in hours, not weeks — no moderator, no recruiting agency, and no research expertise required. Run AI-moderated voice and chat interviews, capture structured and qualitative answers in one study, and get an auto-coded report with quotes you can act on. [Start free with 10 credits](https://www.koji.so) and see the difference between analyzing feedback and generating it.","category":"Comparisons","lastModified":"2026-08-19T20:16:21.686887+00:00","metaTitle":"Koji vs Enterpret 2026: AI Interviews vs Feedback Intelligence","metaDescription":"Enterpret aggregates and tags the feedback you already have. Koji is an AI-native research platform that runs moderated voice and chat interviews on demand. Honest 2026 comparison of features, pricing, and use cases.","keywords":["koji vs enterpret","enterpret alternative","enterpret vs koji","feedback intelligence platform","enterpret pricing 2026","customer feedback analysis","ai customer research platform 2026"],"aiSummary":"Koji vs Enterpret 2026 comparison: Enterpret is a sales-led customer feedback intelligence platform (estimated $30K-$100K+/yr) that ingests existing feedback from Zendesk, Intercom, app stores, NPS, and community channels and organizes it with an adaptive taxonomy and Context Graph. Koji is an AI-native customer research platform (free with 10 credits, then as low as €1 per qualified interview, voice as low as €3, on pay as you go) that generates new data by moderating async voice and chat interviews, asking dynamic follow-ups, supporting 6 structured question types, and auto-coding themes. Enterpret analyzes unsolicited feedback you already have; Koji produces solicited insight by asking new questions. Most teams use both: Enterpret as the listening layer, Koji for discovery, churn, win/loss, and concept testing.","aiKeywords":["enterpret vs koji","enterpret alternative","feedback intelligence","customer feedback analysis","ai customer research","ai moderated interviews","voice of customer","thematic analysis","customer interview platform","feedback aggregation","enterpret pricing","solicited vs unsolicited feedback","churn analysis","win loss analysis","vo c platform"],"aiContentType":"comparison","faqItems":[{"answer":"Not in the primary-research sense. Enterpret is a customer feedback intelligence platform that aggregates and auto-tags feedback you already collect from support tickets, app reviews, NPS verbatims, and community channels. It does not run interviews or ask follow-up questions. To generate new research data, a moderated interview platform like Koji is the right fit.","question":"Is Enterpret a customer research platform?"},{"answer":"Feedback intelligence (Enterpret) makes sense of unsolicited feedback customers already volunteered. Customer research (Koji) generates solicited insight by asking customers specific questions through moderated interviews. The first analyzes the past; the second answers questions you have not asked yet.","question":"What is the difference between feedback intelligence and customer research?"},{"answer":"Enterpret is sales-led with no public pricing; industry estimates put annual contracts at roughly $30,000-$100,000+ depending on data volume. Koji is transparent and self-serve: free with 10 credits, then as low as €1 per qualified interview and €3 per qualified voice interview, on pay as you go with no subscription and custom Enterprise on top. Koji lets a small team run real research this week without a contract.","question":"How does Koji compare to Enterpret on price?"},{"answer":"Only if churned customers wrote about it somewhere Enterpret ingests. It cannot extract a reason that was never volunteered. Koji solves this by proactively interviewing churned accounts and probing for the real reason, then coding the themes across every conversation.","question":"Can Enterpret tell me why customers churned?"},{"answer":"Many teams do, and they do not overlap. Enterpret is the always-on listening layer for inbound feedback at scale. Koji is the research engine for initiating new conversations - discovery, churn diagnosis, win/loss, and concept or pricing tests. Enterpret tells you what people are already saying; Koji lets you ask what nobody has answered yet.","question":"Do I need both Koji and Enterpret?"},{"answer":"Koji. A Koji study can go from question to synthesized, auto-coded report in hours. Enterpret requires channel integration and taxonomy setup before it produces trends, which typically takes days to weeks - and it still depends on feedback already existing.","question":"Which is faster to get insight from?"}],"relatedTopics":["feedback intelligence","enterpret alternative","customer feedback analysis","ai customer research","ai moderated interviews","voice of customer platform","thematic analysis","win loss analysis","churn analysis"]}],"pagination":{"total":1,"returned":1,"offset":0}}