{"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":"2026-11-11T19:57:26.075Z"},"content":[{"type":"documentation","id":"ebaaece5-0896-4ad2-9b52-cb1269155b66","slug":"price-increase-research-guide","title":"How to Research a Price Increase Before You Raise Prices","url":"https://www.koji.so/docs/price-increase-research-guide","summary":"Before raising prices, run a short wave of AI-moderated customer interviews to map the acceptable increase threshold, identify churn-risk segments, surface value anchors, and build a fairness story. Use scale questions with anchoring for willingness curves and open-ended probing for the reasoning. Koji fields the study in days via voice or text and auto-synthesizes a willingness curve, ranked value drivers, and churn signals.","content":"**Before you raise prices, interview the customers who will pay them.** The single biggest mistake teams make with a price increase is treating it as a spreadsheet exercise — pick a number, send an email, brace for cancellations. The teams that raise prices successfully do the opposite: they run a short, structured wave of customer conversations first to learn *which* increase customers will accept, *which* segments will churn, and *what value story* makes the new price feel fair. This guide shows you how to do that research in days, not months, using AI-moderated interviews.\n\n## Why surveys fail for price-change research\n\nA survey that asks \"Would you pay 20% more?\" gets you a useless number. People anchor to the price they already pay, under-report what they would actually tolerate, and over-state their intention to cancel as a negotiating reflex. None of that tells you why.\n\nPrice-change decisions are emotional and contextual. The same 20% increase feels trivial to a customer who just expanded their team and outrageous to one who is quietly evaluating a competitor. You cannot see that difference in a Likert score. You need the conversation behind it: what they compare your product to, who signs off on the budget, what would have to be true for the new price to feel justified, and what would make them walk.\n\nThat is exactly where conversational research wins. **Platforms like Koji run the interview for you** — an AI interviewer asks your pricing questions, then probes each answer in real time (\"You said that feels steep — steep compared to what?\") the way a skilled researcher would. No moderator scheduling, no recruiting agency, no two-week turnaround. You can field a price-increase study to 50–100 customers over a weekend and read the synthesized themes Monday morning.\n\n## What to learn before you change a price\n\nA complete price-increase study answers six questions:\n\n1. **Acceptable threshold.** At what increase does enthusiasm turn to hesitation, and where does hesitation turn to cancellation? You are mapping a curve, not finding a single yes/no.\n2. **Value anchors.** What do customers believe they are paying *for*? The features they name are the ones your justification email must lead with.\n3. **Reference prices.** What alternatives — competitors, internal tools, \"just living without it\" — set their sense of fair price?\n4. **Churn-risk segments.** Which customer types are most fragile, and what do they have in common (plan, tenure, usage, team size)?\n5. **Grandfathering expectations.** Do existing customers expect to be protected, and for how long? This shapes your rollout, not just your number.\n6. **The fairness story.** What framing — new capabilities, rising costs, \"you have grown with us\" — lands as legitimate versus exploitative?\n\n## Designing the study with structured questions\n\nKoji's interviews combine open-ended conversation with **six structured question types** — open_ended, scale, single_choice, multiple_choice, ranking, and yes_no — so you collect chartable numbers and the reasoning behind them in the same session. (See the [structured questions guide](/docs/structured-questions-guide) for how each type maps to a report visualization.)\n\nA strong price-increase interview plan looks like this:\n\n- **Open-ended warm-up:** \"Walk me through the last time you decided this product was worth paying for.\" This surfaces value anchors before price is ever mentioned. Set probing to 2–3 follow-ups so the AI digs into the *why*.\n- **Scale (anchored):** \"On a scale of 0–10, how likely would you be to keep your subscription if the price went up by 15%?\" Turn on the anchor setting so the AI automatically asks, \"What would change that number?\"\n- **Single_choice:** Present three increase scenarios (10% / 20% / 30%) and ask which is the highest they would accept without a second thought.\n- **Ranking:** Have customers rank the capabilities they would least want to lose — this is your justification hierarchy.\n- **Yes_no:** \"Would a 60-day notice period change how you feel about this?\" — a clean read on rollout mechanics.\n- **Open-ended close:** \"If you saw this increase announced tomorrow, what is the first thing you would do?\" The cancel-versus-shrug answer is your churn signal.\n\nBecause Koji keeps a **stable ID on every question from brief to report**, the scale answers aggregate into a distribution and the open-ended answers are auto-coded into themes — so you can say \"27% would actively shop competitors at a 30% increase, concentrated in customers under six months tenure\" instead of guessing.\n\n## Who to interview (and how to recruit them fast)\n\nSegment your customer base before you field anything. At minimum, split by tenure (new vs. established), plan tier, and usage intensity. Price tolerance varies wildly across these. Interview 15–25 customers per key segment; saturation on price sentiment arrives quickly because the reasons cluster.\n\nRecruiting is the usual bottleneck — and the usual reason teams skip this research entirely. With Koji you drop a single interview link into a lifecycle email, an in-app prompt, or a CSM's outreach, and customers complete a **voice or text** interview on their own schedule. Voice interviews capture tone and hesitation that text flattens; text interviews get higher completion from busy B2B buyers. Offer both. Koji's quality gate means only substantive conversations (those scoring 3 or higher) consume credits, so a few rushed or empty responses never pollute your data or your bill.\n\n## Reading the results and setting the number\n\nOnce interviews complete, Koji generates a **real-time report** that does the synthesis a researcher would spend a week on: a willingness curve from your scale questions, ranked value drivers, sentiment trends, and representative verbatim quotes tied back to each theme. Use it to:\n\n- **Set the number where the curve bends, not where it cliffs.** If acceptance holds through 15% and collapses at 25%, a 12–15% increase captures revenue while keeping churn predictable.\n- **Pre-write your churn-save playbook.** The fragile segments are now named. Arm CSMs with the exact objections customers voiced and the value anchors that countered them.\n- **Lead your announcement with proven value.** Your justification email should open with the capabilities customers ranked highest — in their words.\n- **Decide grandfathering deliberately.** If protection expectations are strong among your best accounts, a notice period costs you little and buys enormous goodwill.\n\nThis is research you can re-run every time you contemplate a change. Teams practicing [continuous discovery](/docs/continuous-discovery-user-research) keep an always-on pricing pulse so the next increase is informed by fresh data, not a one-off scramble.\n\n## A five-day price-increase study, end to end\n\nYou do not need a quarter to do this well. A typical Koji price-increase study runs in a week: **Day 1**, segment your base and draft the interview plan (open-ended value warm-up, anchored willingness scale, the increase-scenario single_choice, the value ranking). **Day 2**, drop the interview link into a lifecycle email and an in-app prompt for your target segments. **Days 2–4**, conversations roll in asynchronously as customers answer by voice or text; the AI moderator probes every answer, so you are collecting depth without a single scheduled call. **Day 5**, read the real-time report — the willingness curve, ranked value anchors, and named churn-risk segments — and set your number. Compared with the traditional path (recruit a panel, schedule calls, moderate, transcribe, code, write up — easily three to four weeks), that is roughly a 5x compression with more coverage, not less.\n\nA few mistakes sink price-increase research. **Asking price before value** anchors customers low — always establish what they are paying *for* first. **Studying one blended audience** hides the truth, because tolerance varies sharply by tenure and tier; segment before you field. **Reading the average instead of the curve** leads teams to a single number when the real answer is a threshold. And **skipping the open-ended follow-up** leaves you with a willingness score and no idea how to defend the new price. Koji's anchored scales and automatic probing are designed to prevent exactly these failures.\n\n## Related Resources\n\n- [Pricing Research Interviews: The Complete Guide](/docs/pricing-research-interviews)\n- [Van Westendorp Price Sensitivity Meter](/docs/van-westendorp-price-sensitivity-meter)\n- [Willingness to Pay Interview Template](/docs/willingness-to-pay-interview-template)\n- [Customer Renewal Interview Guide](/docs/customer-renewal-interview-guide)\n- [Structured Questions Guide](/docs/structured-questions-guide)\n- [Voice of Customer Research Program](/docs/voice-of-customer-research-program)\n","category":"Use Cases","lastModified":"2026-08-19T16:08:30.292664+00:00","metaTitle":"Price Increase Research: Test a Price Change Before You Raise Prices | Koji","metaDescription":"Learn how to research a price increase with customer interviews — map acceptable thresholds, predict churn risk, and find the value story that justifies a higher price.","keywords":["price increase research","pricing change research","test a price increase","how to raise prices saas","price increase customer research","willingness to pay price change"],"aiSummary":"Before raising prices, run a short wave of AI-moderated customer interviews to map the acceptable increase threshold, identify churn-risk segments, surface value anchors, and build a fairness story. Use scale questions with anchoring for willingness curves and open-ended probing for the reasoning. Koji fields the study in days via voice or text and auto-synthesizes a willingness curve, ranked value drivers, and churn signals.","aiPrerequisites":["Familiarity with your current pricing and customer segments","Basic understanding of user interview fundamentals"],"aiLearningOutcomes":["Design a price-increase interview that maps acceptable thresholds rather than a single yes/no","Identify which customer segments carry the most churn risk","Build a value-based justification story from ranked customer priorities","Set a price increase where the willingness curve bends, not where it cliffs"],"aiDifficulty":"intermediate","aiEstimatedTime":"12 minutes"}],"pagination":{"total":1,"returned":1,"offset":0}}