In this episode, we take a look at curating those leads which come into your business using AI.

Is it possible to underestimate the value of a quality customer in your pipeline, we all have experienced what it means to bring a customer into your business, which later we are kicking ourselves saying, oh, man, I wish you didn't have that customer. Well, can AI do anything for us? Right to lead or not to lead? Right? That's the question to ask AI. Can you help us with this AI? Well, as you know, today, there are multiple AI tools out there which provide insights on qualified leads. Lots of times are looking at things like recency Right? Like how many leads, you know, came in today or yesterday? Or they're looking at frequency?

How often did the leads actually touch our organization? Right? Was it through some phone interaction? Or did they click on our sights? Or what did that look like? There's easy to action scores, that of course, you want to try to get in front of your sales teams. And of course, the goal is to leverage that info so that the outcome then becomes realized, right, and it turns into a valuable kind of customer. Now, one of the things that we want to do is we want to connect to a variety of systems downstream.

So one of the challenges around lead management and lead AI is you need to be able to organize the information from the earliest touchpoints and identification of who the person is, and follow their lifecycle all the way through to the realization of the income, or the revenue, I should say, coming into the business, or the rejection of it, or the later reclamation of that in the form of a of a refund. So number one, we want to think about how do we connect all of that data together and tell that story, really looking for a series of breadcrumbs, if you will, that ultimately can knit and tie that together. And for a lot of businesses today is you know that this is found in a lot of different systems, right from things like HubSpot, or you know, Pendo, or what have you, right that the data is all over the place. But number one, you want to think about fit, right? You want to think about who are your leads, right?

And how do they match what your ideal customer profile looks like? Do you even know what that is? Have you described that perhaps some refer to that as I see p. The world needs another acronym, right ICP. But nevertheless, this is a critical one, what's your ideal customer profile? What do they fit? What does it look like? Can I describe that, and in order to apply AI to leads, it helps for me to see that now, quite frankly, using AI to help describe that is actually very common practice. So if you think well, I don't really have my ICP defined. That's all right, run a series of AI analyses on the full lifecycle of your leads.

And in time, the AI will begin to discover what that looks like for you. So you don't have to have that first. In fact, the act of preparing AI for leads can help you to develop that. Certainly you want to understand, though, what's the leads activity? What are they doing? What's their ultimate intent? And of course, how often do they actually touch and interact with it with the organization? It turns out that in some cases, it's actually more valuable to reduce the number of leads in terms of, you know, all those we're working with in the organization and actually increasing our sales. So if I could reduce my leads, let's say in half, but of that remaining half, I have very high close rate, then my cost of goods sold starts to drop dramatically, and so becomes really valuable to the organization.

So it's all about finding revenue, obviously, revenue specifically that's untapped in the organization. This is one of those efficiencies. Laser optimization plays that we do on a business, right? It's not necessarily saying, Oh, we're going to go after a new business model or changing this or that this is looking within your current pipeline of the kinds of leads that come through, how can we optimize our behavior so that we return the best possible dollar to the organization. Alright, so, in general, that's the model. But rather than a generic model, I wanted to introduce five or six different scenarios around leads to consider. Alright, so one of these is around product, profitability impact. And I'll come back to these here in a minute, there's lead or customer segmentation.

Another or third scenario is around date or time of sale. There's refund impacts around leads, there's demographics, obviously, for leads, and then there's what we like to call destructive behavior. All right, so let me just to maybe peel the onion back, go down one more layer on each of these. So on this first one on product profitability impact, the real question is, what are the conditions that surround a lead that produces the higher profitability? And of course, as you know, a lot of groups are focusing on the sales itself, which is obviously good. But quite frankly, having your AI pivot on your profitability is a key question to ask your AI solution. So when you're working on leads, build that connective tissue to the ultimate products. And then not only that, but the profitability of those that starts to pay you back very quickly, in terms of any investments that you do with AI actually very strong impact.

Here's another one that pays back your AI efforts. It's around lead lead segmentation, right. And of course, it's finding those segments that drive towards higher sales growth, and of course, higher profitable growth and the ability to segment that, obviously, your benefits certainly marketing activities, pricing opportunities, as well as value delivered to that lead, who becomes a customer. Alright, so having the AI work on that highly valuable. third scenario for AI with leads, of course, you know, when the lead progresses to the point of sale, or for every touch point leading up to that sale, understanding the insights of those touch points, the timing, the areas of interest, etc, that leads some some very insightful AI analysis as well as predictive behavior. That certainly tipped you off as a business owner of when to proceed or when to stop pursuit, the sooner we can stop the pursuit of something that by prediction says, this will waste your time, then certainly the better the better than it is. I had an experience one time with an organization that was trying to sell something. And at one point, I was not getting the cycles. And the salesperson looked at me and said, I'm going to start to I'm going to stop talking to you. I said, Yeah, it's probably a good idea. So he figured out, yeah, I wasn't going to be the right one. So the better you know, the sooner Of course, we can find these, the better. So date, time of sale, meaning all the touch points throughout the lifecycle of the lead. Those scenarios, obviously, very critical.

Ask your AI to look into that. Number three places to put the AI for leads is around, you know, refund impact, of course, is when your your lead turns into a sale, of course, that ultimately then turns into a refund. And it's certainly critical to understand what those look like and how we can get away from and move away from those sorts of situations. The fourth, or excuse me, the fifth scenarios around demographics. So lead demographics. Now, sometimes this can also be aligned with lead segmentation, but not all segmentations are demographic based. And so that's why we break it out, because we see situations where organizations actually treat that as a separate segmentation. So within some segmentation that they'll have to then do further demographics work. Of course, it permits you to focus your messaging and your marketing into sub markets, where things have historically been lucrative or for which you have a high predictive probability.

So applying leads to this sub area around demographics for your leads, very, very powerful. Alright, and then the last one I mentioned here, is around what we call destructive behavior. And I recall early on when we first started applying AI for companies and we got to a point where we said to one of our clients, oh, and by the way, look, we've been able to prove out here with high probability you need to stop having salesperson x with with product why in this particular scenario, the client went home Wow Okay, hadn't even seen that and understanding those kinds of destructive behaviors things to stop.

So, in the same vein doing that with leads is also critical which is stop going after certain kinds of leads as early as possible and how asking the AI tell me what are those conditions or situations in which the lead produces destructive or bad behavior and let the AI find those bad situations so that actually becomes a critical thing to understand obviously, alright, so as you know, there's a range of AI solutions out there today certainly to help you with leads now whether use that we know one of them or you use click AI the real trick is to get control of the front end of your business and and certainly qualify with AI your intake process, obviously reducing you know, the less qualified leads the earlier than certainly it's better for the business. Okay, everybody. Thanks for joining. Until next time, get some AI for your leads.

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