Voice of customer: surveys, interviews and reviews

0:00 Voice of customer

The most persuasive words for your website are sitting in your customers' heads. Voice of customer research is how you get them out: surveys, interviews, reviews and support conversations. In this lecture you'll learn the best sources, how to write survey questions that produce actionable answers, the jobs-to-be-done lens, and how to analyse hundreds of open-ended answers with a codebook, AI and a human check. You'll also see a thirty-minute interview script you can use this week.

0:33 Why VoC matters

Why does voice of customer matter for CRO? Because it explains motivation and hesitation in the customer's own words. Analytics says people leave the checkout. Recordings show them pausing at delivery options. Voice of customer tells you they're worried the order won't arrive before a wedding on Saturday. That last piece is what turns a vague problem into a precise hypothesis, and it often gives you the exact language to fix it.

1:04 Sources of VoC

Where do you find it? On-site polls at key moments, like on a product page: what's stopping you from adding this to your bag today? Post-purchase surveys: what almost stopped you from ordering? Exit surveys for people who cancel. Customer interviews. Reviews, yours and competitors'. Support tickets, live chat and WhatsApp conversations. And sales call notes for B2B. Each source captures a different moment, so combine them.

1:33 Survey questions that work

Writing survey questions is a skill. Ask about behaviour and moments, not general satisfaction. How satisfied are you with our website? produces a number you can't act on. What almost stopped you from ordering today? produces reasons. Avoid leading questions: would you like faster delivery? Everyone says yes. Instead: how did you decide which delivery option to choose? Keep surveys short. One to three questions on-site, open-ended where you want language, and ask at the moment the experience is fresh.

2:08 Jobs to be done

Now a powerful lens: jobs to be done. People don't buy products. They hire them to make progress in a situation. Four forces shape the decision. Push: what's going wrong now. Pull: the better future they imagine. Anxiety: worries about the new option. And habit: the comfort of what they already do. For conversion, anxieties and habits matter most, because they're what stop people who already want to buy. Your job is to reduce anxiety and make switching feel easy.

2:43 Simple example: Abu Dhabi furniture

A simple example. An online furniture store in Abu Dhabi adds a post-purchase question: what almost stopped you from ordering today? Out of the first hundred and fifty answers, the most common theme is assembly. Will someone help me put it together? The second is delivery to upper floors in towers. Neither was mentioned anywhere on product pages. The team adds a clear line on each product page about assembly service and delivery to any floor, with a link to details. That's a hypothesis built directly from customers' words.

3:22 Mining competitor reviews

Don't forget reviews, especially your competitors'. They're free, public and brutally honest. Read the three-star reviews first, because they're balanced and specific: the product was good, but delivery took ten days and nobody answered WhatsApp. Collect a hundred or so across your top three competitors on marketplaces, Google Maps and app stores. Tag them with the same codebook you use for surveys. You'll often find an anxiety the whole category ignores, like returns being a hassle, or sizes running small. If you can solve that anxiety and say so clearly, you have both a conversion improvement and a differentiator. Just remember: use reviews for insight, not for copying people's words into your ads.

4:11 Realistic example: London clinic software (illustrative)

Now a realistic scenario with illustrative details. A B2B software company in London sells scheduling tools to clinics. Trial sign-ups are healthy, but few convert to paid. The team runs six jobs-to-be-done interviews with recent buyers and four with people who trialled but didn't buy. The pattern is clear. Buyers had a push, a receptionist leaving, and the trial made it easy to import existing appointments. Non-buyers had a habit: their current paper diary worked well enough, and importing looked like hard work. The CRO opportunity isn't the pricing page. It's a guided import in the first day of the trial, and copy that speaks to switching without losing a single booking.

5:00 Watch me do it: AI coding with a codebook

Watch me code three hundred survey answers with AI, safely. First, I read fifty answers myself and draft a codebook: eight codes, each with a definition, like delivery uncertainty, fit uncertainty, price and value, and trust in payment. I remove personal data. Then I give the AI the codebook and ask it to apply zero to three codes per response, return a CSV with a short exact quote, and never invent quotes. Now the key step. I code forty responses myself without looking, and compare. If we disagree on more than about one in five, I sharpen the definitions and rerun. Only then do I count codes and pull quotes.

5:48 Recruiting interviewees

Recruiting interviewees is easier than people think. Recent customers are the best source, because their memory of the decision is fresh. Offer a small thank-you, like a voucher or a donation, and be clear about the time: thirty minutes. Include people who didn't buy, like cancelled trials or abandoned quotes, because their reasons are often the most useful. Aim for five to eight per segment. Record with consent, explain how you'll use the recording, and store it securely.

6:22 The 30-minute JTBD script

Let's look at the interview script itself. Seven prompts, about thirty minutes. Set the scene: take me back to the day you started looking. Push: what was going wrong, and why was it urgent then? Pull: what were you hoping would be different? Anxieties: what worried you about switching? Habits: what were you doing instead, and what almost kept you there? Decision: what finally made you decide, and who else was involved? After: what's different now, and anything disappointing? Tag every answer to one of the four forces. The anxieties and habits usually hold your next hypotheses.

7:04 Common mistakes

Common mistakes. Asking vague satisfaction questions. Leading questions. Surveys that are too long. Only surveying happy customers. Letting AI invent categories and quotes. Treating one vivid comment as a trend. And collecting VoC once, then never again. Customer worries change with seasons, competitors and prices, so make VoC a monthly habit.

7:26 Close the loop

Finally, close the loop from voice of customer to the page. Every coded theme should end up in one of three places. As a hypothesis in your backlog, like adding assembly information to product pages will reduce hesitation for furniture buyers. As copy, using the customers' own words in headlines, reassurance lines and FAQs. Or as an operational fix, because some anxieties can't be solved with words, like genuinely slow delivery. Write down which theme went where, and when you'll check whether it helped. That's how research stops being a report nobody reads and becomes a steady source of wins.

8:09 Recap

Recap. Voice of customer explains why people buy and why they hesitate, in their own words. Use polls, surveys, interviews, reviews and support conversations. Ask about moments and behaviour, not satisfaction. Use the jobs-to-be-done forces, and focus on anxieties and habits. Code open answers with a codebook, apply it with AI, and check agreement yourself. Try this now: add the question, what almost stopped you from ordering today, to your order confirmation page, and book two thirty-minute interviews with recent customers using the script in the lesson text.