Selling In The Age Of AI

AI-driven search is already shortlisting suppliers for buyers, and that changes how we earn attention in sales. I break down what these systems look at and how we can improve our odds with visibility, reviews, and solid face-to-face process. 
• why AI shortlisting can help motivated buyers while hiding missed opportunities 
• how AI defines “best” through context and objectives 
• what data drives recommendations such as reviews, ratings, specs, and behaviour 
• why social proof now carries more weight in discovery 
• when to ask for reviews and recommendations for the best response 
• how sponsored placements and platform rules can shape visibility 
• why qualification still matters even with AI-sourced leads 
• responding publicly to negative reviews to build trust 

Please remember to like and subscribe. Please give me a review, please comment. 

Welcome to the podcast!

Transcript

How AI Defines “Best”

Patterns Models And Ranking Signals

Sponsored Results And Hidden Rules

Get More Reviews At Peak Moments

Face To Face Still Needs Qualification

Reply To Bad Reviews Publicly

Key Takeaways And Listener Requests

SPEAKER_00 0:07

Hello again. This particular episode has been prompted by something I was reading a day or two ago, and I think it's very relevant to where we are right now, and that's how we combat AI when we're in sales. And uh what made what made me think about this is that the um the piece I was reading was somebody who actually uh I think does sales training, uh, but they had to go and buy something, so they jumped on the computer, did the usual AI search, and that shortlisted two options for them, and then it was a case of um you know taking that further themselves. But the point that was made was that from one perspective, this is quite horrifying because when somebody comes to you, or I guess on the plus side, they're already fairly well motivated to buy your product service. Uh, obviously, this will vary in relevance depending on what it is you're selling. On the other hand, though, if you've been excluded, you never even knew there was an opportunity out there. Now, that that's definitely true anyway, in sales. You know, one of the problems that we have as salespeople is just knowing that people are out there who want to buy what we sell. So, this is why we have avatars, this is why we advertise, this is why we look to see where our potential clients are hanging out in terms of what they're reading, uh, maybe what social media they're on, whatever it might be. So, it did occur to me though, there are a few things that you can do to make that work for you, or at least minimize the damage, let's call it, that AI may well be doing if they're steering clients away from you. So I went to I've actually gone to Chat GPT to ask about how AI selects the best product. So there are some steps here, and it does pretty much reflect what my understanding is of how this all works. So the and and the reason to understand this is we can look at the parts of this process that we can influence. That's what I'll come back to. So the very first thing is defining best, in other words, what the objective is. So that will depend on the context. It could be lowest price, it could be highest rating, it could be best performance if that's a measurable, measurable performance, uh, a specification item, and what's most relevant to you personally. So this is often formulated as an objective function, and this is what AI tries to optimize. Now, the next stage is to collect and analyze data, and the kind of thing that AI is looking for is user reviews and ratings, product specifications, sales and popularity trends, and user behavior. So that might be clicks, purchases, time spent evaluating. So platforms like Amazon, for example, track what people view, like and buy. So the thing that jumped out at me there was reviews and ratings. So the question to ask, whether you're running your own own marketing or if somebody else does it for you, is how good are you at publishing ratings, asking clients for reviews? Are you asking at the right time? So there are certain points in the sales process where people are much more likely to give you a positive review and a review at all. So how can you are you leveraging that? Because it may have been that in the past things like reviews and ratings weren't that important or didn't seem that important to you, but these days they can be a big factor. So again, depending on the kind of industry you're in and where your clients are. So if you're if you're pretty much local based, you're dealing with local businesses, then probably possibly the AI thing is a big factor for you. But if you're going global, then absolutely, I would say it's important to make sure that you are at least actively promoting things that can make you more visible, as I'm assuming more and more people start using AI as a part of their decision-making process, or at the very least, their shortlisting process. So AI uses models to find patterns in the data. So these are, for example, collaborate collaborative filtering. People like you also like this, which um I know on Shopify and things like that, you can set that up. Um, the content-based filtering, so these might be match matches which feature um, for example, a phone with long battery life, so it'll be picking up on a particular aspect of whatever it is you're buying or a client is looking at that may well be um something important to them. So, for example, with phones, uh, there was an ad a few years ago now that uh I think it was Samsung brought out against Apple, and they showed people that they called wall huggers with their Apple phones who were constantly hunting for power outlets so that they could keep their Apple phones charged. So, things like that, what are aspects of what you do that you could perhaps use as leverage? Um so the bottom line on that aspect is that the model is asking how likely is this user to like this product? That's essentially what it's what it's doing. So the more we can build up, it sort of gets into the social proof area, but the more that that can be built up, the better. Then there's ranking and scoring options. So each product or service gets a score based on relevance to user performance, quality indicators that would be ratings and reviews again, and then context that might be location, time, device, whatever it might be, and AI ranks off that. So, again, ratings and reviews are a really positive thing to be promoting if you're able to do that. Then you've got personalization, so AI systems do adapt to individuals, and I'm tempted to say that this applies more to business to consumer sales, but um, I wouldn't actually go all the way with that, frankly. So, what is it talking about with personalization? It's basically your past behavior influences future recommendations. So, what can it track that you've done before? And two people searching for the same thing may see different best options. So, Spotify is an example of this where it recommends music differently for every user, and that's based on what's in their playlists and that kind of thing, maybe what they've they've been buying, all that kind of thing. So that's another factor. You've then got continuous improvement improvements. This is the feedback loops. So if users click or buy, that reinforces the recommendation. So, in other words, if AI makes a recommendation and the user goes with that, that will tell the algorithm essentially that it's on the money. But if it gets ignored, then that lowers the ranking next time. So, in other words, if it makes a recommendation and the client goes with something else, then that will tell it that it's not on the money. So, whereas I'm not sure what we can do to actually influence that as salespeople, it's useful to understand that's part of what goes on. So, constraints and business rules that apply here. So, sometimes best isn't purely objective. So, this could be sponsored products or ads. So, again, how active are you in sponsoring your products? Because that can be um a factor in how much you're being taken into consideration when these initial searches are taking place. Uh, it could be availability or stock, it could be platform priorities. So, it's basically um a mix of user relevance and business goals, is the way that I understand this. So, a simple a simple way I should say to think about this is based on everything what AI is basically doing is saying, based on everything I know, what option has the highest probability of satisfying this user right now? So, what it's doing is it's not looking for a universal best, it's basically finding the most likely best for a given situation, and that will be based on data, prediction models, and continuous feedback. So, how can we, as salespeople, make use of that? Well, as I've already said, a really positive thing we can do, particularly if we're in the business to consumer um area, or at least a business where recommendations and social proof are really important. So that'll be business to business, business to consumer, is to make a point of asking for reviews, asking for recommendations as well. Because if you're asking for a review, and one of the keys time, one of the key times to do this is when someone collects their product into collecting from you, or they get delivery. You really want to get in touch with them at that point because emotionally they're at a high. The other one, another one, I should say, because they're generally three, but another one is when they first use the product. So make sure you are making a note somewhere to follow up with these people at those points where they're on an emotional high when they're using your product or service. And these are the times to ask them to do a review. Again, just pop them in a link, make it as easy as possible for them, or ask for a recommendation. And um, again, there are ways of doing that that are more likely to um elicit a useful response. So that is definitely something that you should be thinking about, and the other side of this, and you may disagree with me, and if you do, please comment, that's always useful to get feedback. But the other side to this is when we do find ourselves in face-to-face meetings, which is the area where I specialise, it really does underline the importance of getting those opportunities because one of the things that um I really push home when I'm teaching, and you've probably heard it on podcasts, is that we have to be really sure that we're spending time with people who are appropriately qualified in as much as they're more likely to buy from us. So we're not spending time with people who aren't likely to buy from us, and I would say obviously the normal qualification process applies, so we need to do that because not only does that make sure we've got a good fit, but it gives us methods of um overcoming objections. So we need to do a standard qualification process, but it does mean when we do get face-to-face with these people, unless the AI system, the algorithm, the data it's using is, I guess, giving a false positive. In other words, they're sending people being or getting in contact with us who really aren't good fits for us. So that again, this doesn't get rid of qualification and going through that whole process. But it it does mean that one would hope at least that the people we're in front of have a higher probability initially of buying from us, being a potential client than somebody who's cold. So I guess what I'm saying here is to make sure that the processes that we would normally apply when it comes to face-to-face meetings are absolutely there. We can't take for granted that all because this person has come to us through some AI search, that they're necessarily going to be a good fit. And again, this will depend on what it is we're selling. If it's something pretty straightforward, then chances are they are. But if what we're selling is something that's a bit more complicated, a bit more involved, and needs a lot of tailoring to uh particular needs, clearly that would push the likelihood of or the probability of them being a good client to perhaps being a bit lower. So I guess to round this off, I don't want to be rambling too much. What what what can we do to improve our chances in in a land or in a world that definitely has AI as a factor in who people go and talk to when they are looking for something? And I guess also the other question is how different how different is this to say Google searches, um, which is a another question. But the and probably the answer comes down to the same thing. It's about making sure we're as visible as possible by understanding how the algorithm algorithms work, particularly in the industry that you're in, uh, because I I don't know what you I don't know what you're selling. So, what can you do there? Are you maximizing your opportunities and your visibility? So I would say definitely referrals, uh client ratings, um, those areas, client reviews, uh really work on those. And the other thing I would say as well, if you get a bad review, always respond to it because these can be really powerful. So it doesn't have to be wall-to-wall good reviews. In fact, they can look a little bit uh contrived. So if you get the occasional negative review or something that's not a five-star, not a five out of five, then always respond to it. Uh, but do it publicly so that potential clients have an opportunity to perhaps get to the root of what why someone's not happy with whatever it is you provided, and they can see that you're proactive, that you're engaged. And that to me says that you are somebody, a supplier who is interested in looking after their clients, in providing a good solution, and not somebody who just sort of dumps a solution and runs for it and takes no interest at all in how good a decision it turned out to be for those people who've invested in you. So, all of those things I think are important, and I think it really does underline the importance of being really effective when you are face to face with clients, that you do all the steps that I talk through, that I teach, and that you will have heard in in some of my previous podcasts. And it it's more important than ever that you apply those and and do them correctly, and that uh should definitely improve your closing rate and include your numbers and um give you a more um secure business footing, a more profitable business. Okay, so that that was it. That's what I wanted to say. Um, hopefully that made some sense. And um, if it did, please remember to like and subscribe. Please give me a review, please comment. Um, yeah, that you know, why not? So, um, yeah, that's it for now, and I'll speak to you in the next podcast.