S1. Ep 12 - Automate Review Analysis, Responses & Competitor Insights

Katie: Welcome to the AI Automations for Business Podcasts. We're your hosts, Katie and Null, and we'll be discussing how you can use AI for your business along with the latest news, updates and automations to help you stay ahead of the curve, allowing you to grow and scale your business more efficiently. Please be sure to subscribe and I hope you

Noel: enjoy this episode.

Katie: Hello, welcome back to another episode. Hi, I'm Katie and I've got Noel with me. Hi, Noel.

Noel: Hello.

Katie: How are you doing today?

Noel: Oh, excellent. Ready to automate. How are you? Oh, good. Thank you.

Katie: So, no, today we're going to be talking about reviews on Trust Pilot, Google reviews, anywhere, really, I guess people have reviews left for them.

Noel: Yep.

Katie: And we're going to be looking at competitor analysis, customer service, performance, and as well as, like, maybe individual team performance if you're working for a large organisation. Yes,

Noel: absolutely.

Katie: Because I feel like lots of businesses and organisations collect these reviews. People are always asking to review them, but then not a lot of people are actually doing anything with them, I find.

Noel: Yes, I found the same when I built out the automation as a test just to show what could be done, I was going through like big corporations and not a single review as being responded to. It's like, well, what are you doing with all these reviews? Like one of the companies was getting, they must be getting an easy 100, 200 every hour.

Katie: Why?

Noel: So what's the point of this? Apart from getting good five-star reviews, but, you know, who's really taking the time to read all of these?

Katie: Yeah, but I think it's great if you are getting all five-star reviews, but if you're getting a real mix, I think. I think there's obviously work to be done and things that can be improved, either for the business or for the customer experience. Yes, absolutely. Yeah.

Noel: Some businesses will only really focus on the bad reviews so they can try and turn it round. But there's always that middling ground. So if you've given it like a three or a four, like no one really cares about those, you know, they'll never see to respond or do anything about it. But those are the ones where they could swing either way kind of thing. So you need to try and look at that information and try and figure out what you can do better. Yeah.

Katie: Do you know, I recently was asked to leave a review. It was last year. It was a place that I visit quite a lot. I meet friends there for a coffee and once you've ordered via their app, the next day they send an email to say, how did we do and we had had such a lovely time the the staff were all so lovely so friendly and I thought do you know what for once I'm actually going to like give some feedback because I think we're all so quick aren't we to give negative feedback but not so quick to give positive feedback and we were there for hours and they never once said we need the tableback or you know guys you order in anything else like we were sat there probably for an hour, kept saying we were, you know, to one another, oh, we're going to go, we're going to go and then obviously just kept chatting and chatting. So we didn't order drinks or anything for like the last hour. I thought, do you know what? That's so kind. They were so lovely, so friendly. I'm going to leave a really positive review. And I had an email back a couple of days later to say, you know, thank you for the lovely review. We think the team at, you know, this branch are awesome and they thank you for the positive feedback. Here's a voucher for your next coffee. And I was like, oh my God, that is brilliant. And, you know, it was something I wasn't expecting at all. But it was just, you know, the power of actually someone reading that review and saying, do you know what team, you are actually doing really well. This person had a really enjoyable time because you did X, Y, and Z.

Noel: Yeah, absolutely. Or did they ought to make that. You never know.

Katie: Well, I don't think they did because it did, it did sound very humanised. And there were things in there that I don't think you could have done using like Open AI. Fair enough. Yeah.

Noel: Yeah. So I've had quite the opposite experience where a restaurant in London and harass me and my friends to the point where they wouldn't let us pay for the meal until we're giving a review on Google.

Katie: Wow.

Noel: It's like, we've got a train to catch. We need to go. Can I pay? And they're like, not until you've left a review. I was like, well, I'll take a picture of that. And I'll do it when I'm on the train. They were like, no, you're doing it now? So I gave them a one star. I said, harass me for trying to get them to give them five.

Katie: Well done. That's really bad, though, isn't it? Like, that is not the way to get a five story. review.

Noel: No, exactly, though. But what are they doing with it as well? You know, like, is anyone going to look? No, I never reached out to me about it or anything.

Katie: No, but I think for them, like, especially restaurants, they want as many five-star reviews, especially on Google, because they rank higher then. And so when people are, you know, Googling for a restaurant in a certain area, especially London, because, you know, there's thousands and thousands of restaurants in London, there's so much competition, they're like, oh, this. This one's got, like, you know, 5,000 five-star reviews, so it must be good. And then you go there and, like, you find out why they've got all these reviews is because, you know, no one's allowed to pay for their meal until they've given them a five-star review, which is quite naughty.

Noel: It is, yeah, it's pretty bad. Yeah.

Katie: So, no, tell us then what organizations can do with these reviews that they are getting from, you know, places like Google or. trust pilot and how they can just like use them more than going, oh, great, we've got a five-star review. Oh, no, we've got a three-star review.

Noel: Yeah. So what we can do from an automation perspective is to grab all of that information from whichever platform it is. And then what we can do is install it into a database. So we can track everything and keep everything nice and neat, which is kind of what I'd like to do when it comes to my automations. And what we can then do from that point is to figure it. So if you're working for like a big team or let's say you've got some real distinct products that you're selling, we can categorize the reviews to say, well, that belongs to this team. You know, that's part of the sales team. That's part of the support team. Or it might even be like user experience or this is for our beauty products. And this is like generic sort of product sort of thing. We can kind of split all of that information out. So when we come to analyzing the reviews, we know what that's about. So AI has already done that hard work for us, so we don't have to sit and read every single review. For big companies, that's really the crux of it. You know, you don't have time or you don't want to be spending somebody else's time within your business to manually do that work. And I guess the other big thing as well is once you've got, gathered all that information is the next step I did was to go through and then respond to each of those reviews in turn. So if they had a positive review, we train the AI to say, well, look, that's brilliant, thanks so much, you know, be really positive. The neutral ones were kind of like, well, you know, sorry, we could have done better, you know, and kind of like a neutralish tone, trying to get it to turn it around. And then the negative was more like apologetic and then saying, well, look, maybe you should reach out to our support team, you know, we'll want to resolve this kind of thing. All of that's done, you know, within a matter of minutes. For like, if you say you've got like 200 reviews to scrape through, you can get through that in about 10 minutes.

Katie: Okay, wow, that's good. I was going to ask about the responses and could you automate them? Of course you can. Oh, yes. Yeah.

Noel: I would say you've got to be kind of careful as well because you don't, when it comes to using AI and then getting that to be customer facing, you kind of need to really nail down your prompt engineering to make sure that the responses are given are in line with your, you know, company values and things that. And, you know, you want to be responding in UK English if you're in the UK, so you don't want any Zeds in there for the US English and things that. So, yeah, you can fully automate that, but. Maybe sometimes, especially with negative reviews, maybe you'd probably shouldn't, but at least get AI to create the draft that you can review and then.

Katie: Yeah, I think it's really important how you handle negative reviews. I've seen some negative reviews, like the responses on like Google, horrendous, horrendous. And then you think, oh my goodness, like I wouldn't go anywhere near that company. Yeah, it just puts you off. So, yeah, I think that's a good indicator, actually, of how good a business is to work with or an organisation. It's how they handle those negative reviews.

Noel: I think using AI almost takes the emotional part out of it. So you're not looking at a review about your business and getting annoyed about it. You know, you're using AI to create like the first draft. So, like, you're already not so annoyed already kind of thing. You're like, oh, okay,

Katie: maybe I can then

Noel: tweak it and then send it.

Katie: I think it's when people take these negative reviews personally, and people need to remember its business. It's not a personal attack at you.

Noel: Yeah, absolutely.

Katie: Okay, so now let's have a chat about using these reviews for competitor analysis. How can we use someone else's reviews to help. our business or organization.

Noel: Yeah, I couldn't believe how easy this kind of was where we can go to tools like Appify, which allow you to scrape all of the reviews from trust pilot, Google reviews for any business. So as long as you know the business name, you're kind of good to go. You can get whatever you need. So for when I did my demonstration of how this works, I didn't have a trust pilot account. so I solely relied on scraping all of that information for the business I was acting as well as a competitors. But, yeah, you can get reviews for anybody. And you can do the same analysis that you did internally. So you can say, well, if they run a very similar service-based company, then you can say, well, how are their sales team doing? How's their user experience? How's that working out? And then you can then look at their reviews with the help of AI, obviously. and to take the legwork out of it and then say, well, look, our competitors doing really well at this within the sales team and ours isn't doing quite so well. So, you know, we can start to, you know, look internally and then make changes based on at the competitor analysis.

Katie: Yeah, I love that. That's so good, isn't it?

Noel: Yeah. And it's really easy to kind of like create a report on this as well. So you can get AI to look at whatever. everything in bulk and then say, well, look, here's all of the information you're going to need. Create me a Google Doc that goes through, like gives me a summary, goes through what's happened internally, and then split out each competitor in a different section. So then you can, you know, you can then read through that in your own time and then figure out what to do and what to change. Whereas doing that manually, cool, they'd be there for weeks. Yeah,

Katie: yeah. Yeah. And I feel like a lot of these reviews just kind of like collect dust. And, you know, because it's so overwhelming, it's hard to kind of keep up with, you know, for these large organisations to then actually, you know, and then what happens is then change is quite slow.

Noel: Yes. Yeah. And one other thing actually that was really good when I was starting to correct the test reports is it also, the AI was picking. out and highlighting people that are done really well within your business. So I scraped like a massive energy company in the UK and I was acting as them. And I thought it was an hallucination. So I was reading the document. They said, oh, Elvis has done really well. And I was like, really? That's a bit of a unique name. So I then went back in the database, searched Elvis. And there was. There was the support guy at the call center. The customer's like five-star review was so helpful, so understanding, he got it fixed. But that was like buried under like 200 reviews, you know, within the, you know, within the preceded day kind of thing. So that would have been completely lost. So, yeah, for big organisations, that can really help to, you know, at least highlight who's doing well.

Katie: Yeah, Elvis sounds like he needs a pay rise or promotion.

Noel: He did, yeah. It's like a three-paragraph review when I went back to up, look at it, you know. Why?

Katie: No response

Noel: to that one either.

Katie: That's such a shame as well because when someone is really going above and beyond in an organisation, I feel like they do need some credit or some, you know, recognition to say, look, you know, we've had lots of five-star reviews that have, you know, mentioned you personally.

Noel: Yeah.

Katie: Yeah.

Noel: It's a bonus. Yeah.

Katie: But then it can also help the other way around. So if you've got people that are underperforming, and, you know, as an organisation, you're really trying to improve, say, like your customer service, but it doesn't seem to improve. You know, then if people are leaving negative reviews and actually naming people, that's when you can go, do you know what, these people actually need a little bit more support or, you know, maybe we can give them some additional training. And then that helps everyone.

Noel: They'd have a chat with Elvis.

Katie: Yeah, Elvis, you need to do a training for everyone.

Noel: He does.

Katie: No, is there anything else that you feel like you want to talk about when it comes to automating reviews?

Noel: I think we've kind of covered all the main topics. I think it's really underutilise. I'm very overpowered. So, you know, this is something that can be quite quickly set up within an organization and, you know, can run every month kind of thing. So, you know, you can continually look to improve as well as have a sneaky peek at what someone else is up to. So if they might be a review saying, oh, you know, they've released X product and this is, this is amazing. I'm like, oh, hold on a minute. Yeah, maybe we should look at that.

Katie: Yeah. Is this like something that costs a lot of money? Is it expensive?

Noel: So within make.com, it's more operation intensive. So obviously you pay for the operations. So yeah, you would probably need at least 10,000 operations per month. It all depends on how many reviews you've got, really. But I think Appify, you get like a thousand reviews for like 50 cents. So, yeah, I wouldn't say that was, it's quite cheap overall. Okay.

Katie: So if you had, you know, 10,000 reviews, it's not going to cost you hundreds and hundreds of pounds.

Noel: No, no. If you're doing that sort of quantity, then I'd definitely look at N-A-N because you then, you can self-host that. And once you self-host it, you don't have to worry about any sort of operational costs, yeah, for anything that's really labour-intensive, we're going to use a lot of information, and it ends the one. Otherwise, if you did that sort of thing within Make for that amount of reviews, you're probably looking about $200 per month, just for that one subscription.

Katie: Yeah.

Noel: So that is pricey, but I guess if you're a big corporation getting that amount of reviews, you know, it's worth it.

Katie: There's that return of investment, isn't it?

Noel: Exactly, yeah, yeah. It's not going to break the bank for them.

Katie: No, amazing. Well, thank you. you so much now for your automation knowledge as always and we will catch you next week for another episode take care