استخراج نقلقول از مصاحبههای مشتریان: تبدیل متن خام به بانکی دستهبندیشده از نظرات
Why this prompt matters
Most teams either skip customer interviews entirely because mining them for usable quotes takes hours, or they use one obvious quote from the interview and ignore four other equally strong ones buried deeper in the transcript. A systematic extraction pass turns 45 minutes of raw audio-to-text into a reusable quote bank that can supply a landing page, three sales one-pagers, and a quarter of social posts from a single round of interviews — instead of running a new interview every time a different team needs a quote.
What we use it for
You just finished five 30-minute customer interviews for a case study project. You have five raw transcripts, roughly 45 minutes of usable content buried in filler words, tangents, and repeated phrasing, and marketing needs three strong quotes for a landing page redesign by Friday.
Prompt
Act as a content strategist specializing in customer proof and testimonial curation for [YOUR COMPANY/PRODUCT NAME].
Context:
- Product/service being discussed: [BRIEF DESCRIPTION OF WHAT YOU SELL]
- Common objections your sales/marketing team currently struggles to address: [LIST 3-5, e.g., "too expensive for small teams", "hard to migrate existing data", "not sure it works for our industry"]
- Customer segment(s) in the transcripts: [E.G., "Enterprise IT buyers" or "Solo freelancers" — note per transcript if mixed]
Raw transcripts:
[PASTE ONE OR MORE RAW INTERVIEW TRANSCRIPTS, SUPPORT CALL NOTES, OR REVIEW TEXT HERE — filler words and interviewer questions are fine, leave them in]
Task:
1. Extract every genuinely usable testimonial-quality quote from the transcript(s) — a sentence or short passage that clearly and specifically praises, defends, or explains a benefit of the product in the customer's own voice.
2. For each extracted quote:
- Lightly clean it for grammar and remove filler words ("um," "like," false starts) WITHOUT changing the customer's actual meaning, claims, or tone
- Tag it with the SPECIFIC objection or use case it addresses (not a generic category — e.g., "addresses price-sensitivity for small teams" not just "pricing")
- Note the customer segment it came from, if provided
- Rate its strength: Strong (specific, vivid, quotable) / Moderate (useful but generic) / Weak (true but not compelling enough to use standalone)
3. Flag any quotes that make a specific measurable claim (a number, a percentage, a time saved) — these are the highest-value quotes and should be surfaced first.
4. If NONE of the provided objections are addressed by any quote in the transcript, say so explicitly rather than forcing a weak match.
Constraints:
- Never alter, exaggerate, or combine quotes from different parts of the transcript into a single fabricated quote — every quote must be traceable to one continuous passage in the source text.
- Do not invent a customer's job title, company, or any attribution detail not present in the transcript.
- Skip quotes that are too vague to be useful ("it's great," "I like it") even if grammatically clean.
Output format:
- Group quotes under headers by the objection/use-case tag they address
- Within each group, order quotes by strength (Strong first)
- Format each entry: cleaned quote (in quotation marks) — Strength rating — Segment (if known) — one-line note on where it could be used (landing page hero, sales one-pager, social post, etc.)
- A closing section titled "Objections Not Yet Addressed" listing any objections from your list with no supporting quote foundResult
Addresses: Onboarding-speed skepticism ("too complex to set up")
1. "I was honestly expecting a two-week onboarding slog like our last tool, and we were running real reports by day three. That alone justified switching." — Strength: Strong — Segment: Mid-market operations lead — Best for: landing page hero quote, sales one-pager top section (specific number, direct comparison to switching cost)
2. "Setup wasn't instant, but it also wasn't the nightmare I'd built up in my head from other implementations." — Strength: Moderate — Segment: Mid-market operations lead — Best for: FAQ section addressing setup concerns directly, less punchy for a hero placement
Addresses: Price-sensitivity for small teams
3. "We're a six-person team and I genuinely wasn't sure we could justify an enterprise-tier tool. Turns out the core features we actually use are all in the starter plan — we're paying less than our old spreadsheet-plus-three-plugins setup cost us." — Strength: Strong — Segment: Small business owner — Best for: pricing page testimonial, small-business-targeted social post (specific comparison, addresses the exact fear directly)
Addresses: Migration/data-import concerns
4. "Moving four years of customer records over was the part I was dreading most, and it took about twenty minutes with the import tool. I kept waiting for something to break." — Strength: Strong — Segment: Enterprise IT buyer — Best for: sales one-pager for technically cautious buyers, case study opening line (specific time claim, addresses a named fear directly)
Addresses: Industry-fit doubt ("not sure it works for our industry")
5. "Most of the case studies I'd seen were from SaaS companies, and we're a physical logistics operation, so I wasn't sure this would map to how we actually work. It took maybe a week of light customization before it felt built for us specifically." — Strength: Moderate — Segment: Logistics/operations — Best for: industry-specific landing page variant, not strong enough alone for the main homepage (true and specific, but less punchy/quotable than the top quotes)
Measurable claims flagged for priority use
- Quote #1 — implied setup time comparison (2 weeks expected vs. 3 days actual)
- Quote #3 — cost comparison (cheaper than prior spreadsheet-plus-plugins stack)
- Quote #4 — specific time claim (20 minutes for a 4-year data migration)
Objections Not Yet Addressed
No quote in the provided transcripts addresses "lack of customer support responsiveness" — this objection from your list has no supporting evidence in this batch. Recommend flagging this for the next round of customer interviews specifically, or pulling from support ticket resolution data instead.
انجام مصاحبه با مشتری هزینه زیادی دارد — زمانبندی، اجرا و پیادهسازی آنها زمان زیادی میبرد — و بیشتر این ارزش هدر میرود چون متن حاصل شامل ۳۰ تا ۴۵ دقیقه صحبتهای نامرتبط است که شاید فقط پنج جملهاش واقعاً قابل استناد باشد. پیدا کردن آن پنج جمله با بازخوانی کل متن آنقدر خستهکننده است که بیشتر تیمها یا از آن صرفنظر میکنند یا به همان نقلقولی که از مکالمه به یاد دارند اکتفا میکنند.
کار این پرامپت چیست
این پرامپت مانند یک استراتژیست محتوا عمل میکند که به صورت سیستماتیک به استخراج نقلقول میپردازد. شما یک یا چند متن خام را در آن قرار میدهید و پرامپت نقلقولهای واقعاً قابل استفاده از مشتریان را بیرون میکشد؛ هر کدام از نظر دستوری اصلاح میشوند بدون اینکه کلمات یا معنای اصلی مشتری تغییر کند، و بر اساس این که به کدام اعتراض یا کاربرد خاص پاسخ میدهد برچسبگذاری میشوند — شک در مورد قیمت، تردید در مورد سهولت راهاندازی، مقایسه با یک رقیب، و غیره. به جای یک نقلقول عمومی، یک بانک دستهبندیشده دریافت میکنید که میتوانید آن را با هر صفحه یا مکالمه فروش خاصی تطبیق دهید.
چرا دستهبندی اهمیت دارد
یک نقلقول که میگوید «در زمان صرفهجویی کرد» بسیار کمتر مفید است از نقلقولی که برچسب «پاسخ به شک در مورد سرعت راهاندازی» دارد، وقتی شما در حال ساخت صفحهای برای خریدارانی هستید که نگران زمان پیادهسازی هستند. پرامپت با الزام به ذکر یک برچسب اعتراض یا کاربرد مشخص برای هر نقلقول، این ویژگی را اعمال میکند؛ این همان چیزی است که مجموعهای از جملات خوشساخت را به نقلقولهایی تبدیل میکند که میتوانید در برابر تردید خاص یک خریدار به کار ببرید.
روش تطبیق آن
متنها را همانطور که هستند قرار دهید — این پرامپت طوری طراحی شده که کلمات اضافی، شروعهای ناقص و سوالات مصاحبهگر را که در همان بلوک متنی مخلوط شدهاند مدیریت کند. اگر مصاحبههایی از چند بخش مختلف مشتریان دارید (مثلاً سازمانی در مقابل کسبوکار کوچک)، بخش مربوط به هر متن را یادداشت کنید تا خروجی بتواند مشخص کند کدام نقلقول برای کدام مخاطب مناسبتر است.