Presented live on Tuesday, November 17, 2020Attend our live tutorials
Use data review mining if you want your message to be relevant…
Then you gotta get inside your customer’s head.
There’s no way around it – it’s just gotta be done.
Customer surveys and customer interviews are great ways to get inside your customer’s head…
If you’ve got the time.
If you don’t have loads of time, review mining is your answer.
What Can You Find Using Review Mining?
- Problems in life
- Problems with solutions
- Motivations to seek you out
- Desires that drive purchase / repurchase
- Specific features they want
Jo’s gonna show you how to use this technique to find what your prospects – or people like your prospects – are saying about products or services that are similar to yours.
Get this right and you’ll know PRECISELY what to say and how to say it
Joanna Wiebe: Rapid Fire review mining, we have talked about this before. However, we want to talk about it some more because there’s more things you can do with this.
What to Expect in This Tutorial [00:22]
Review mining. Why do we do it in the first place? Because it reveals… Now, I am not suggesting to anybody that they only do review mining. However, when you are putting copy together, when you’re trying to figure things out for how to hook people. You will find plenty in review mining. And I mean masses, so you can see the frequency of a message.
It keeps coming up. It keeps coming up. That means it’s probably important. You can also see how to message things. How are people talking about that one problem they have? What’s some interesting language?
What Can You Find Using Review Mining? [00:58]
- Problems in life
- Problems with solutions
- Motivations to seek you out
- Desires that drive purchase / repurchase
- Specific features they want
So, rando reviews that are in your category but not necessarily about your product. So maybe you have reviews, you get a lot of Google reviews or you sell something on Amazon, or you’re on Yelp or wherever you might be. We’re not talking about that today. We’re talking about reviews for products in your category or products that are similar to yours. Basically, if you’re familiar with the jobs to be done whole method of finding out what people are hiring your solution to do.
It’s everything that your prospect or lookalike is hiring to do the job they should be hiring you to do. So if you’re a plumber. You look on Amazon, books, in particular, to say, okay, well, a person should hire me to fix their toilet. Instead, what do they hire? They hire a book about plumbing. They hire their brother in law, who is the guy who fixes things.
All these other things that people hire to do the job that they should hire your solution to do. You can search for your category and find a lot of voice of customer inside reviews that can help reveal problems people have in life in general. And that means not just, Joanna has a problem with loving cats. That has nothing to do with yours. I mean, like what people in your category, prospects, are actually finding problematic.
What drives them to choose solutions or what do they kind of associate with solutions like yours? And then more about problems with actual solutions, just like yours. Any motivations they have to seek you out in the first place.
Desires that drive purchase, that drive repurchase and that’s really, like, oh, I tried this, it didn’t work, then I tried this, it didn’t work. And then I tried this and it worked. And that’s the repurchase part. Specific features that they want. So a lot of times when you’re doing review mining, it can feel like, oh, I’m only going to get into what people are tired of.
What their problems are. But there’s so much that people say in reviews about their favorite features, and features can mean anything. So if you’re like, Jo’s only talking about products. I’m not. Services have features too, so extend the idea of features beyond what we think about when we think about features.
Any anxieties people have, any hesitations they have, and the list goes on. There is a wealth of great stuff in reviews. The more people leave BS reviews. The more problematic, it can be to try to mine reviews. But basically a ton of what you need for problem and solution aware copy is in Amazon reviews.
And even problem awareness beyond we haven’t talked about the stages of awareness for your whole brand, or your whole product lineup, or the whole idea of buying from you. And I mean even at the offer level. So, if they’re problem aware in the offer level, then that’s a great place. You can find a lot of customer on Amazon for that as well.
Why Amazon Reviews? [04:08]
And we’re focusing on Amazon review mining today, which is not to say that you can’t do review mining on any website where people are leaving reviews that are largely unfiltered. So not necessarily negative. I know unfiltered can often sound like oh, they’re going to be negative.
No, it’s just like no one’s like the problem with trying to review tweets is there’s a character limit. With trying to review Facebook comments in public spaces, even in private groups, is your name is associated with that. And so there’s no level of anonymity.
Because people you know will see the thing that you said, and so you better filter yourself. Not that not that we’re all filtering yourselves on Facebook. And you should probably. Okay, but the point is, Amazon reviews are where I can say something real about an experience I had, and you can use what I said to write your copy.
Over the Shoulder Review Mining [05:10]
So, I want you to do it the hard way first. Let’s go over to Amazon.com and find VOC for problems with acne. So how would you go into Amazon.com, if you were trying to find reviews that you could then mine for anything you’re selling a solution for acne, let’s say. What would you do?
Okay, so we’d look up acne and then start going from here. So you might open these, you see all of these reviews. I know, right. Super bold. I don’t even think about this stuff. I once shared, screen shared at an event as I was getting ready to present and nobody was there, just like a few stragglers in the room. But I screen shared my notepad, my notes were showing, and it had all of my passwords listed in it, but it didn’t say what the passwords were for. It was just clearly a list of passwords.
When I was still documenting my passwords and Notepad and Chris from Wistia was in the audience. And he was like, I just saw your passwords. It was chuckle worthy. So yes, I do over share. I’m going over share.
Okay, but we would open these up in new tabs and then you would start going through them. Now, these are all things that have to do with acne. They’re not all the same solution, but there’s something that if you were a dermatologist, let’s say, you would go here and start looking through reviews or solutions that people hire instead of hiring you.
So instead of going to a dermatologist for my recurring acne, or whatever, I hire this solution. So we want to look at those reviews, let’s dig in. Now, what would we do in review mining, you would go through and read these one by one and you can see we already saw there like 3900 reviews here alone, and so on and so forth. So then you try to figure out, well, which ones should I look at?
What Reviews Should You Use? [07:33]
Maybe I won’t look at five stars because some might be biased. And I won’t look at one stars because those might also be biased. I’ll look at four stars instead. And now you’re filtering based on something that has nothing to do with the fact that you’re looking for a VOC, right? So just because you see some five stars that are maybe fake, or whatever it might be.
And then you’re like, well, let’s just discount all five stars, but there could actually be a lot of real stuff in there. And now you’ve had to just move on from those and try something, like, go to the four stars, and you could be missing good VOC.
Of course, Then there’s the other side where you have a lot of good reviews, especially when you’re seeing how helpful people find them. You can go through and look at them, but you’re looking at them one by one. And this is the way that we’ve traditionally taught it inside Copy School and other spaces. Go in here, block out three hours to rapidly read through reviews, and this is just for three products, we’d want to look at more than that. So it can take a lot of time. Now, it can be really good because it opens your eyes, but then you also start looking with a sort of bias. Where you get worn out reading through these reviews, one by one, looking for interesting voice of customer that reveals problems, frustrations people have, anxieties, what they hesitate over, what their favorite features are, what their least favorite features are, what works for them, what doesn’t work for them.
And you’re going through that, and you’re seeing things and one, everything seems important. Then secondly, you’re like, Oh, shit. What’s the reason I’m doing this in the first place? And trying to find messages I can use to write my actual copy. And so then you’ve gone through so many. Point here being, there’s so much human error and human fatigue involved in manual review mining.
Formula for Speedy Review Mining [09:23]
My good friend, Shane O’Quinn, sent me years ago, something that is much, much better than that. And we’ve taught this previously, in Tutorial Tuesdays, this exact shortcut: site:amazon.com inurl:”product-reviews” “tired of” ~keyword.
I’ve also taught it in other places, but I’ve just chatted it out to you. What we want to do instead, and then we’re going to build on this one too, what we would do instead is go to Google, or just go into your search just like that. And replace the keyword with whatever that category is that you’re searching or trying to write for anyway. Now we can start having Google do the work of filtering out those Amazon reviews.
And we don’t have to go to Amazon at all. We’re just going through without any sort of fatigue or anything, we’re going through and reading actual voice of customer as we see it. “I’m tired of,” we can see that, the phrase that we’re really looking for here is tired of in the URL for product reviews. So, at some point, Amazon may change their URL structure, at which point, this will not work anymore. And we’ll have to find a new in URL put in there.
But “tired of” stays the same. And then you just change the keyword for whatever you’re searching for. So we’ve talked about this. If you’re unfamiliar with that, get familiar. I’ve chatted over this. So, like, give it a go. Paste in something related to your business, your client’s business, whatever that thing might be.
And you can see that now we’re seeing actual filtered VOC. So, “I’m so sick and tired of being 26 and breaking out with acne as bad as when I was 13.” That’s really interesting if you’re writing a page for a dermatologist who’s trying to attract people who have acne when they’re 26, when they’re adults. This could be a headline you could test, “I’m so sick and tired of being an adult breaking out like when I was 13.”
That could be like Oh damn. That’s exactly what I’m thinking. It doesn’t mean it absolutely is.
But right away we can see that we’ve identified a problem, something that people are tired of and real language. And that’s just the first one. Now there are going to be a lot that aren’t as good. You’ll go through and be like, Oh, this isn’t even for a related product at all, or somehow I ended up looking through descriptions instead of reviews. Somehow that crap happens.
But that’s the first one to go to. And this is the one that we talk about a lot. The “tired of” inside your review mining. But there’s more to it than that.
Instead of “tired of,” we can try things like “frustrated by” and you’ll typically see when you swap out different phrases in there: site:amazon.com inurl:”product-reviews” “frustrated by” ~keyword. That for “frustrated by,” things got a lot sharper. People get a lot angrier because frustration is more powerful, I think, than being tired of something. So you’re sick and tired wah wah. But when you’re frustrated by it, then you can really dig into visceral, like what is that pain?
And move through it. So you can go through and do this. And what I’m really teaching you here. In today’s tutorial is to try swapping out “tired of,” for other things. I have done this a million times and some just do not work. You can swap something out and you’re like, oh shit that only brings up like really vague things.
But “tired of,” “frustrated by,” finally is a good indicator of, like, Oh man, I was so at the end of my rope. Finally, I got this. You can also, if you happen to know a particular feature and you want to find out more about what people are thinking with regard to that feature, that feature name can go in finally.
However, I’d still recommend that you put that feature name in place of acne and then search finally “tired of” or “frustrated by.” One of the challenges, and one of the things that I’m often trying to do when I’m working on this shortcut, with the formula for it.
And swapping out “tired of” with other things, is you’re trying to get beyond just the problems people have toward the things that they want. What are those desirable things? And typically, when you search “tired of,” you actually will see what those desirable things are.
But sometimes you might not. So feel free to try swapping things out. “Wanting,” is one that I have tried that’s sometimes successful, but it depends on the actual thing that you’re searching. So whatever this keyword is. For acne, it’s not that useful, “wanting,” but for other searches that I’ve done it has been.
So swap that out, try different things. And just yet, just use this shortcut to stop yourself from having to do all the work of manually going through reviews. And then, of course, make sure that you’re capturing that voice of customer. That you’ve got here and if any of them go long, just open a new tab.
But make sure you’re capturing that. So, I’ve talked about Airstory. The Airstory Researcher is made for this exact thing, where you go into the research or you send it to your Airstory project or to the general library. And then when it’s time for you to actually start organizing messages on the page, you just drag and drop that into the page.
Alright everyone, thanks for joining. Even though I didn’t send an email. Yes, sorry about that. But we’ll send one for next week. Thanks, Joanna. And that wasn’t me talking to me. Someone just chatted something to me.
Angela Stojanov: That was me. Sorry, my mouth didn’t move. It was weird, it froze.
Joanna Wiebe: We’re working on this thing. Yeah, yeah I pretend I’m talking and Angela is talking. I was gonna try to go there, but my brain doesn’t work fast enough. Okay. Thanks everybody. We will see you next week. Stay safe, stay happy and have a good rest of your week. Bye y’all.