Let’s look briefly at what VoC is, check out an example, and then run through four steps that will help you to use it to write better copy for technical buyers.
VoC data is any information about your product – or a competitor’s – that comes directly out of the mouths of customers. And there are a million and one different sources of it. Reviews, surveys, technical forums, recorded demos, interviews, support tickets, chat logs, and social media comments – they’re all sources of VoC data.
There’s a vast ocean of this stuff.
Best of all, most of it is publicly available. Anybody can go to a company’s social media pages and sift through the comments to gather VoC data. You can jump onto Amazon (more on that later) and read hundreds of reviews all coming directly from customers. This is data that you already have to hand and, if you know what to look for, you don’t even need to be a professional copywriter to turn it into powerful messaging that appeals to your technical buyers.
So, you have plenty of sources of VoC data.
But what point does it serve? Why should you spend time sifting through all of this customer-generated content in the first place?
The answer comes down to two words – sticky copy.
Sifting through VoC data is a messy process – and it should be – because you’re potentially reading hundreds of reviews to try and find sticky copy. These are the little phrases scattered in the big mound of data you’ve compiled that are super usable for copy.
Let me give you an example.
A while ago, I looked at the Google reviews for a company called Ninja 1. I read somewhere between 75 and 100 reviews, all from different customers, with my goal being to look for repeated phrases that I felt would be usable for my copy. Whenever I came across something and thought “That’s an interesting way to phrase that,” I potentially had sticky copy on my hands.
A few phrases stood out:
“We can make it our own.”
“Removes a lot of the bloat that you get with other platforms.”
“Take control of our IT infrastructure without having to worry if our machines are meeting our standards.”
What do you notice about these phrases? They’re all talking about the primary objections and priority points that customers have, essentially giving us the reasons why they love using Ninja 1’s software. That’s a gold mine of data. By paying attention to these reviews and the sticky phrases I spot within them, I can see what existing customers are getting out of the software. If I were to start writing copy for Ninja 1, these are the sorts of phrases that would become headlines and feature copy because they speak directly to what a customer wants.
That’s sticky copy.
So, you understand what VoC is and, crucially, that you’re using VoC data to try and find sticky copy that you can sprinkle throughout your website and other marketing materials. But we still haven’t answered the biggest question – how?
Let’s run through the four steps using examples from a company I worked with called Yesware.
First up – finding VoC data. This was easy for me with Yesware because we did a lot of product education. So, I had internal interviews, customer surveys, and about 800 reviews with which to work.
Hopefully, your company has similar sources of data.
Your job here is to compile them all. You don’t need super-advanced software to do so. A simple spreadsheet on Google Docs will do the trick. Your goal is simply to mine your existing data sources to find as much VoC customer information as you can.
It’s not just your own company’s reviews that are valuable sources of VoC.
The information you glean from competitors is just as valuable, which is where Amazon book reviews come in. For example, let’s say that you’re trying to write copy for a construction management company. Jump on to Amazon and run a search “construction management” and you’re going to see all sorts of books pop up.
Think about who’s reading these books.
It’s going to be people who are looking to optimize their construction operations or their financials. In other words, technical buyers who want to learn more about the construction industry.
Just as you did with your own VoC data, you can compile the reviews of these books to figure out what people are saying about them. What good information did each book deliver? What was it missing? These are questions that give you insight into what your customers need, and they’re questions that these book reviews can help you to answer.
This step is your secret weapon – almost nobody is using Amazon to get VoC data. When you start doing it, you get access to a wellspring of valuable information.
Once you have your collection of reviews and VoC data from your own company and Amazon, you start looking for the sticky copy.
There are two ways to do this – go manual or use AI.
If you go down the manual route, as I did with Yesware, you’re going to read through the reviews in your Google Docs spreadsheet. Any time a phrase stands out to you, pop a comment next to the review. Once you’ve worked through the lot, re-read your comments and look for the sticky copy that keeps getting repeated.
If that sounds like too much hard work, the current wave of generative AI tools, such as ChatGPT and Bard, can help. Collect 50 or so reviews and put them into a prompt that reads something like this:
“I want you to take all of the following reviews and create a table according to the following instructions: Column A, Column B, Column C, review, insight about the reviewer, label as a benefit feature or outcome so you can have a tag.
“Underneath the table, I want you to write a summary of patterns you’ve observed in the review data. Are there clear patterns? Anything I should be paying attention to? Is there anything surprising regarding reviewer sentiment? Okay, here are the copy-and-paste reviews.”
Paste your reviews into the tool and it’ll come up with a table – including insights and potential sticky copy – for you.
Coming back to the Yesware example, once I had my examples of sticky copy, I started implementing them strategically across the company’s webpage. I used some of the copy in the headline and filled out more to the point where the page was three times longer than it was originally.
Then, I tested the results incorporating the two signup flows – one for Outlook and the other for Gmail – that were already on the page.
The results?
A 106% increase in clicks for the Outlook signup button and a 38% increase for the Gmail button.
Those increases came because I’d layered the sticky copy from my VoC data into the content presented on the site. That copy spoke to what customers wanted, what they liked about the product, and what it could do for them – all crucial for getting people to sign up.
VoC data is a constantly renewing wellspring of information covering what your customers think about your product. The good, the bad, and the great is all in there.
By following these steps, you not only compile that data, but figure out how to extract the sticky copy from it. Implement that copy into your website and you’ll see more engagement simply because you’re actively speaking to the pains and problem-solvers that your customers experience and want.
Let’s look briefly at what VoC is, check out an example, and then run through four steps that will help you to use it to write better copy for technical buyers.
VoC data is any information about your product – or a competitor’s – that comes directly out of the mouths of customers. And there are a million and one different sources of it. Reviews, surveys, technical forums, recorded demos, interviews, support tickets, chat logs, and social media comments – they’re all sources of VoC data.
There’s a vast ocean of this stuff.
Best of all, most of it is publicly available. Anybody can go to a company’s social media pages and sift through the comments to gather VoC data. You can jump onto Amazon (more on that later) and read hundreds of reviews all coming directly from customers. This is data that you already have to hand and, if you know what to look for, you don’t even need to be a professional copywriter to turn it into powerful messaging that appeals to your technical buyers.
So, you have plenty of sources of VoC data.
But what point does it serve? Why should you spend time sifting through all of this customer-generated content in the first place?
The answer comes down to two words – sticky copy.
Sifting through VoC data is a messy process – and it should be – because you’re potentially reading hundreds of reviews to try and find sticky copy. These are the little phrases scattered in the big mound of data you’ve compiled that are super usable for copy.
Let me give you an example.
A while ago, I looked at the Google reviews for a company called Ninja 1. I read somewhere between 75 and 100 reviews, all from different customers, with my goal being to look for repeated phrases that I felt would be usable for my copy. Whenever I came across something and thought “That’s an interesting way to phrase that,” I potentially had sticky copy on my hands.
A few phrases stood out:
“We can make it our own.”
“Removes a lot of the bloat that you get with other platforms.”
“Take control of our IT infrastructure without having to worry if our machines are meeting our standards.”
What do you notice about these phrases? They’re all talking about the primary objections and priority points that customers have, essentially giving us the reasons why they love using Ninja 1’s software. That’s a gold mine of data. By paying attention to these reviews and the sticky phrases I spot within them, I can see what existing customers are getting out of the software. If I were to start writing copy for Ninja 1, these are the sorts of phrases that would become headlines and feature copy because they speak directly to what a customer wants.
That’s sticky copy.
So, you understand what VoC is and, crucially, that you’re using VoC data to try and find sticky copy that you can sprinkle throughout your website and other marketing materials. But we still haven’t answered the biggest question – how?
Let’s run through the four steps using examples from a company I worked with called Yesware.
First up – finding VoC data. This was easy for me with Yesware because we did a lot of product education. So, I had internal interviews, customer surveys, and about 800 reviews with which to work.
Hopefully, your company has similar sources of data.
Your job here is to compile them all. You don’t need super-advanced software to do so. A simple spreadsheet on Google Docs will do the trick. Your goal is simply to mine your existing data sources to find as much VoC customer information as you can.
It’s not just your own company’s reviews that are valuable sources of VoC.
The information you glean from competitors is just as valuable, which is where Amazon book reviews come in. For example, let’s say that you’re trying to write copy for a construction management company. Jump on to Amazon and run a search “construction management” and you’re going to see all sorts of books pop up.
Think about who’s reading these books.
It’s going to be people who are looking to optimize their construction operations or their financials. In other words, technical buyers who want to learn more about the construction industry.
Just as you did with your own VoC data, you can compile the reviews of these books to figure out what people are saying about them. What good information did each book deliver? What was it missing? These are questions that give you insight into what your customers need, and they’re questions that these book reviews can help you to answer.
This step is your secret weapon – almost nobody is using Amazon to get VoC data. When you start doing it, you get access to a wellspring of valuable information.
Once you have your collection of reviews and VoC data from your own company and Amazon, you start looking for the sticky copy.
There are two ways to do this – go manual or use AI.
If you go down the manual route, as I did with Yesware, you’re going to read through the reviews in your Google Docs spreadsheet. Any time a phrase stands out to you, pop a comment next to the review. Once you’ve worked through the lot, re-read your comments and look for the sticky copy that keeps getting repeated.
If that sounds like too much hard work, the current wave of generative AI tools, such as ChatGPT and Bard, can help. Collect 50 or so reviews and put them into a prompt that reads something like this:
“I want you to take all of the following reviews and create a table according to the following instructions: Column A, Column B, Column C, review, insight about the reviewer, label as a benefit feature or outcome so you can have a tag.
“Underneath the table, I want you to write a summary of patterns you’ve observed in the review data. Are there clear patterns? Anything I should be paying attention to? Is there anything surprising regarding reviewer sentiment? Okay, here are the copy-and-paste reviews.”
Paste your reviews into the tool and it’ll come up with a table – including insights and potential sticky copy – for you.
Coming back to the Yesware example, once I had my examples of sticky copy, I started implementing them strategically across the company’s webpage. I used some of the copy in the headline and filled out more to the point where the page was three times longer than it was originally.
Then, I tested the results incorporating the two signup flows – one for Outlook and the other for Gmail – that were already on the page.
The results?
A 106% increase in clicks for the Outlook signup button and a 38% increase for the Gmail button.
Those increases came because I’d layered the sticky copy from my VoC data into the content presented on the site. That copy spoke to what customers wanted, what they liked about the product, and what it could do for them – all crucial for getting people to sign up.
VoC data is a constantly renewing wellspring of information covering what your customers think about your product. The good, the bad, and the great is all in there.
By following these steps, you not only compile that data, but figure out how to extract the sticky copy from it. Implement that copy into your website and you’ll see more engagement simply because you’re actively speaking to the pains and problem-solvers that your customers experience and want.
