In conversation with Lorenzo Carreri
[This is a transcript of Part 1 - Store Conversion on Steroids. Below is a link to the recording.]
Kausambi: All right. This is it. It's finally day one of store conversions on steroids. It's nine days, nine experts, nine very quick, but intense, deep dives into what does it really mean to run a high converting online store? CAC is shooting through the roof today. And customer lifetime value is where the money's at the shopping experience that you run in your store.
That's what drives CLV up, up and up. And with this series of livestreams, we want to help you up your conversions, but real left tactics and playbooks that you can actually use. And, uh, to kick off, to pick this amazing series of we have Lorenzo Carreri and I met him about a year back now I've learned quite a few bad artistic techniques on CRO from him, and I'm super, super excited to get to this deep dive started.
Um, and without wasting more time, Lorenzo, over to your 32nd elevator pitch, what do you do and why is it important for e-commerce?
Lorenzo: Yeah. First of all, thank you for the invite. Super appreciated. I'm Lorenza Careri and I'm a CRO customer research and experimentation consultant. Um, I specialize in working with e-commerce and helping them increase conversion rate revenue.
I love time value. Um, today we're going to be talking about one of my favorite topics, which is, uh, reviews, mining, um, which is probably one of the least, uh, use the CRM. Um, uh, data, customer research methodologies. Um, so I'm very excited about showing the, the, the potential and the value of this.
Review Mining - Are you Doing it Right?
Kausambi: I'm super excited to hear more about it, but, but just to get started, but like what's, what's review mining. And before that actually what's wrong with our product content in stores today. What's what's wrong.
Lorenzo: Yeah. So, um, I would say one of the common challenges that I, that I see on product pages, for example, um, is that they don't really include, uh, content visual, uh, copy to what the user is looking for. Um, so one of the things that I do with my clients is I analyze all the different reviews that a product for example has, um, to understand a bunch of, I call them user stories, which means like, how have you, how has the user use the product? Um, And basically the idea is to leverage reviews, mining, to come up with a bunch of insights that helped me increase conversions and help the user make a decision when the users in front of the product page and has to decide if that product is, is good or not.
Kausambi: Got it. And is this process like good for all kinds of? So most of our, you know, uh, target audience today is folks who are anywhere between 2000 to 20,000 kind of orders. So what do you do when you have less reviews and what do you do when you have a lot of.
Lorenzo: Yeah. So for those stores that have, that have a lot of products, I would definitely need to prioritize those products that, um, bring in the most revenues.
80% of revenue is brought by 20% of products. - Lorenzo
So let's say you'll have the typical kind of like 80, 20 rule. Um, 80% of the revenue is brought by 20% of the products. So I will try to focus on those, uh, products, um, for the businesses that don't have enough reviews. Um, there's a lot of different ways that they can do it. You know, let's say. They also sell the products on third party sellers like Amazon or Walmart or whatever, other kind of like business and any e-commerce.
Um, they could actually, uh, do the reviews mining on, on those websites. So it doesn't have to be their own website where they look at their reviews. It could be somebody sells website as long as the product is the same or as an alternative, they could look at a competitor review. So let's say you're selling dog food and you don't have enough don't have enough reviews for one specific product because maybe you just launched it. Where you could do is you can look at the competitors, uh, similar products to come up with a bunch of insights. Sure. It's not the same as, you know, looking at your own product, but, uh, you can have a little bit of data from.
Insights from Customer Reviews
Kausambi: That's pretty interesting. I want to dive in a little bit now, like, what is this whole process and what are the insights that they're looking for?
Lorenzo: I'm going to share the spreadsheet I use to do the analysis. Um, all right.
Kausambi: It's awesome day for our audience here. They're going to be able to actually see live and action.
Lorenzo: Yeah. So I'm mainly use this spreadsheet to do the analysis. Um, I'm going to talk about two different tabs. This one, basically I just record all the different reviews that customers have left have left about product. Um, and then I create different themes, which oftentimes are similar for all the products that I've analyzed with other clients.
But some other times these teams are completely kinda new depending on, on the business. And then once I fill out. Uh, all the different insights coming from these reviews, I basically tried to bring structure, so to quantify how frequent each of these themes, um, are for, uh, for the product. So for example, this is just an example, but, um, this product in particular was a juicer.
And, um, in the stop, there is a pain point. So pain points that customers who left the review, um, in the store have mentioned. So for example, you know, 40% of the people said that there was too much cutting. They had to cut vegetables way too much. Other there said that, um, there was a risk of cutting myself.
So for the pain-points category, I break it down into a subcategory. And then I seem to quantify in terms of like how, how often, uh, people have mentioned those, those topics.
How to sort customer reviews
Kausambi: Got it. And, and, and how do you kind of like even pull out? I, I I'm sure that sometimes when you're reading one review versus the other, especially when you have a lot of reviews, right?
How do you really pull out these segments of topic clusters? Right? Like, is there some something that folks can do if they have a lot of reviews? I'm sure if you have fewer reviews, it's literally going to hit one. But if you have a bunch and across different kinds of platforms, how do you really pull out this topic?
Lorenzo: Yeah, I would, I would start with probably like a hundred reviews, so I wouldn't go too crazy. Um, just because for two reasons, first of all, it's very time consuming. Um, usually a hundred reviews depending on how long the reviews are, which is also another topic that is very important. I would completely remove reviews that are like, kinda like just one sentence that says, oh, I love this product.
You know, I will buy it again. I've moved completely reviewed these kind of review because it's not insightful. It doesn't help me. You know, come up with a potential solution to improve the conversion. So first of all, focus on at least a hundred reviews. Um, second, uh, what you want to do is basically like create a macro topics for each of these categories.
Um, and then, so for example, you have, for example, here in the pain point, you have too much cutting, um, and then risk of cutting myself. So you could be combining. Together and just call it cutting. And then, um, you know, it really depends on oftentimes the, actually the most the topic, the, the team that has the highest number of, uh, uh, subtopics usually is benefits, which are basically the benefits that people got from the product.
Usually that list is very, very long, um, cause different segments got different benefits for the product. Um, so yeah, that's, that's what I. Right.
Key things to consider while review mining
Kausambi: Is there anything that folks like key things that people have to keep in mind when they're doing this process? Because next time on a dive into what do you do with these reviews?
Where do you put it in your store? But like right now to wrap this segment up, what are two things to have to remember when they are doing this process of mining?
Lorenzo: Yeah. So first step number one, carefully read the review, and try to understand what the user actually means would that review?
Carefully read the review and try to understand what the user actually means.
So for example, in sales, there's this concept of active listening, where the sales person basically listens carefully to what the prospect that says. People that do reviews. Mining should do something similar, but I call it active reading and weather. What I mean by that is that every single sentence that they're read, they need to wonder what is the user really, really saying with this sentence?
Cross-pollinate or distribute your review findings across other departments.
What's the kind of reasoning behind what the user is saying. So that's one thing. The second one is, um, you know, Would this like, act on the insights that you get from, from, from reviews, mining, and oftentimes the insights should actually, actually not oftentimes always they should be cross-pollinated around the industry, um, around the, the, the company, because oftentimes if you start doing reviews, mining to improve the conversion rate of a product page, for example, what are you oftentimes see is that there's a bunch of like issues that come up that should be, um, you know, Cross pollinated to across other departments.
So product department, customer support, even like finance sometimes and then third act on, on those these sites. So for each kind of like main theme, Um, that is being brought up from, from these insights, come up with some ideas on how you can increase conversion based on, on that, basically.
Derving insights from customer reviews
Kausambi: Right. And that's what we're going to dive into. We're just on the clock. So I'm just going to ask anybody here. If you want to ask any question to learn, so please put it down on the comments and on the chat, you would just see that below. And we'll come around to it as soon as possible.
So now diving into the - what do I do? I've mined out hundred reviews, eliminated all of the tiny ones that don't really make much sense are don't give much depths to me, simple stuff like, oh, I love it. That's it. That's great. But what am I going to do with it? So things and reviews that are adding more information on the benefits on the problems. So I'm going to pull all of that out and then I'm going to segment it. I'm going to, you know, put it into clusters. I'm going to draw insights out of it, on what, which part of my store funnel I can actually impact. And then what are these examples of what, what I can do actually, but those are real.
Lorenzo: Yeah. So, one thing that I, I want to mention is that, um, you should actually, these, these reviews, mining approach be augmented with other customers, customer research approaches, right? So you should look at the results that you got, the insights that you got from these methodology, um, and compare them with like customer support tickets.
For example, maybe a lot of people are asking question about, I don't know, like the size of the dog food - everybody wants to know how big the size of the dog food is. So maybe like that is not clear enough. So you want to grant that insight with reviews, mining, and come up with a bunch of a hypothesis and an ideas on how okay.
Fantastic. Everybody's concerned about X. Right. We should make that element more prominent on the site, or everybody says that they love the product because of why a reason, but that reason is not present on the site. We should make that more prominent on the site, both with copy and images. It's very difficult to kind of like generalize to what they should do, um, because it really depends on what they use.
Kausambi: I remember Lorenzo one of the times that we were catching up, um, it be, you know, saw, I think you showed me an example of a store in which they actually used the review categories to almost create a navigation structure. Right? Like that word, the categories that was on the home page and people and consumers like me, but actually get there, you know, the, all the reviews differ mind and the benefits became subsections within your, within your homepage of your store. Can you just, you know, talk to our audience a little bit about that example?
Lorenzo: Yeah. So basically if you think about it, the user makes a bunch of decisions if she wants to buy or not based on a bunch of criteria is right.
But the problem is that at the moment, most DTC brands in general, most e-commerce don't show those attributes, let's say product attributes, um, in the review section. So let's say I make a decision because, um, you know, I'll give you an example with the restaurant industry because it's, it's, it's absolutely classic.
So I'm Italian born and raised in Italy, but I live in London. Um, now when I go to an Italian restaurant, I don't really care about seeing, um, you know, reviews from, I don't know, like British people or American people, because the way I consider Italian food is very different than the way other people consider Italian food.
Right? So this is a classic example of, okay. Imagine if TripAdvisor gave me the opportunity to just select reviews from Italian people, they both, maybe even the way Italian people are different than Italian people that live in Italy. Right?
So think about the way your customers make decision when buying your product and based on that, when you ask your customers to leave reviews, as the question about that criteria, that attribute.
Kausambi: That's interesting. Give us an example?
Lorenzo: Yeah. So an example would be like, you know, first of all, figure out what are the attributes that your customers care about about the product? Let's say, I don't know, color size, and let's talk about like the clothing brand color size, uh, for which occasion and maybe like, uh, maybe like a. Um, let's, let's say these three, right then what you want to do when you ask for reviews, when you're asking your customers to read your reviews, you ask them to write a comment about each of these three attributes, and then you use these three attributes as filters in the review section.
So now the user can pick and choose all the different filters that they want. So I want to hear. Uh, I want to see what people have said about the color red about this t-shirt. Um, but the, you, as in the context of the gym, for example, right? So now, um, this is why I want to buy as well. I want to buy red t-shirt to use it at the gym.
Now I'm seeing a bunch of reviews. Of people that I've used the product in the same context as, as I want to use it.
Kausambi: Yeah. Yeah. I can totally see, even in best-sellers or something like that, that you can literally put in, you know, that this is like the most love red t-shirts for gym. Right. And, and, you know, and then it can link it to.
I think the scope is endless. There's a lot that you can do. I want to quit me in interest of time, dive into the two questions we have. And then I, if time permits, I have a couple of more questions.
How many customer reviews do you need?
Question: What is the minimum number of reviews needed to gain credible users?
Lorenzo: Yeah, I would say start with 100 at least. Um, and, uh, cause you know, keep in mind that this process is quite time consuming. So you want to make sure that you are looking at enough review. Um, to have enough data, but this is also like qualitative data. So, um, having a high, huge amount of reviews is not super important.
So I would say with 100, to begin with. Got it.
Kausambi: And let's say she has a hundred reviews. Um, uh, she, these will be reviews fair. She prunes out everything. That's not adding much deeper insight to her on how consumers actually evaluate her products. Right. Yeah. I, so what I talk about what, under reviews, it should be 100 insightful reviews.
So for example, You know, I would completely remove every review, as I mentioned earlier, such as like, I love this product. I will buy again, I wouldn't consider this review because it's not insightful. It doesn't really give me, you know, actionable stuff to do with my product page or my company in general.
So when I talk about 100 reviews, I'm talking about 100 insightful reviews that give me some sort of like information about what I should do based on the.
How to gather more reviews
Kausambi: Done. Hope it helps you. Uh, then the second question is from Sandra. Hi Sandra. Thank you for being here.
Question: Do you have any recommendations of how to gather more reviews from customers if you're a small store?
I think that's a burning question from both stores.
Lorenzo: Yeah. So, um, I would say, um, you know, you could, uh, you could say, okay, I'm going to. Um, maybe like incentivize people for leaving reviews. If you leave reviews, maybe, you know, you can get X discount for knickknacks purchase bird. For example, that would be one.
Um, one thing that I would also try to leverage is every time you're talking to a customer, uh, via live chat or customer support and that customer, um, maybe you can ask, Hey, do you mind leaving a review here? Or you can send like the link. So every time there's a. Uh, contact with the customer, um, like live chat or customer support tickets.
Um, just ask the customer to leave a review.
Kausambi: All right. That wasn't even to unmute myself that really helps. Uh, and I think the, the, uh, science here, or rather the art here is about, you know, also, uh, getting insights from the customers. Sandra for, as a SAS business, I can tell you could, could be applicable even to e-commerce to you as a brand, is that sometimes, maybe during the customer reviews to add on, to learn.
So just ask how they're feeling about the product, even if they're not dropping it in a review review and in your site. I think that that's set up as a review to save that little nugget of information and you can possibly utilize that. Uh, I love Lorenzo structure, so you could probably do that.
Lorenzo: Yeah. And you know, obviously reviews mining is, you know, it takes a couple of two or three hours, depending on how many you, you gather.
You also could do customer interviews, obviously they're more time consuming the reviews money, but you can get a lot of insights from that as well. Uh, right.
Kausambi: So Priyanka has a question. Thanks, Priyanka. Do you think all your meals could pick up at some time or even video reviews as to bring in more credibility to review?
Lorenzo: A hundred percent. Yeah. I think you w you said credibility a hundred percent. You said you're right. I think, um, in a world where, you know, the user, I've seen a lot of time, actually, when doing customer research projects, people might think that the reviews are fake or, you know, uh, somebody actually got. Uh, somebody in the family wrote the review or some other employee in the company rather view, I think audio and video could be a great way to increase the trust that the user might have in the, in the reviews.
Um, and, and also what I really like about video reviews is that it might even show how the user is using the product. Um, so you can gather additional kind of like, so let's say it's a product about food. Maybe. I don't know. You can see how. Let's say it's an olive oil. I'm Italian. I got to talk about
Revere selling olive oil. Um, and you, you see exactly how the user using the olive oil on the salad. So now not only you have some insights about the product, but how the product is being used with some funny something else, which is also another sort of like insights that you can gather that can take you to another kind of like direct.
Kausambi: Yeah, I can totally see that, that that's. I mean, it's insightful for me to am taking a note of that. And I have a final question, like can our audience and whoever signed up, but couldn't show up today, get your amazing template and actually help, help get started on this whole review process or how did they do.
Lorenzo: Yeah, totally. Um, I will definitely put the building today to the spreadsheet, uh, uh, in the notes. Uh, we, we can send it to them. Uh, it's fully available, um, in terms of how they can reach out to me. Um, they can find me on LinkedIn. And then I also have a YouTube channel dedicated to CRO, uh, it's called understanding how a shoppers think and the way we do it is we pick a brand every week, um, DTC brand, and I, you know, with my friend, Rishi, we basically analyze, I analyze the reviews. He's analyzing from a copywriting perspective and we give a bunch of, uh, uh, recommendation how a product page should be optimized for increasing sales.
Kausambi: Super, and we'll bring both of you in a tear down at some point in time, but that's for another that's for another life series.
Thank you all, everybody we're running out of time, but this was amazing sharp, but really insightful. Thanks to audience and yeah. Um, uh, we'll be back tomorrow with the next, uh, series next livestream in the series. And thank you, Lorenzo, uh, for giving your Italian insight and examples to hope it was.
Lorenzo: Thank you for inviting me!