Why Most Mid-Market Companies Are Missing Their Data Advantage (ft. Ed Lorenzini)

Himnish Jindal: Welcome to Making Martech where we spotlight innovative Martech companies and leaders who are driving growth, highlighting valuable insights and actionable strategies to stay ahead in this industry. Today we're joined by Ed Lorenzini, CEO

Ed Lorenzini: of Analyze Corp. Um, I'm Ed, I'm the CEO and the co founder of Analyze Corporation. Analyze is a uh, SaaS platform that does segmentation and lead generation.

Himnish Jindal: And can you tell us a bit more about what Analyze360 does and what problem are you solving with that?

Ed Lorenzini: Analyze360 is a software as a service platform that really serves mid market. We're doing automated segmentations for mid market and we're doing a, ah, lead generation for them. The way we do that is we collect all the data that you can have. In the US we have data on 220 million US people. That's almost everybody in the US over the age of 18. And we have up to 360 consumer variables in every single person, all keyed to their first name, last name and address. So we know age, income, homeowner status, first mortgage, second mortgage, credit cards, that they have, their credit scores. We've got things like their types of credit cards. We know uh, what they're buying. Are they buying apparel if it's apparel, or by the women's apparel if it's women's apparels, A plus size, petite size. So we know all that and that's what we use to create models for our customers. The nice thing about what we're doing is that the models are created automatically in the platform based on whoever their current customers are. So that's really where the power comes and we do it very affordably.

Himnish Jindal: And what's the potential for impact with Analyze360?

Ed Lorenzini: Yeah, great question. You and I are not old enough to remember when consumer segmentation was done a certain way really in the late uh, 70s, early 80s, um, consumer segmentation was big. Everybody used it, they got a lot of lift off it. But it was um, underpinned by a certain idea that changed. The idea was that all the communities, all different communities, were similar. So you know, same age, income, you know, did you own a home? Uh, that was all very similar for communities and people divided the US up into communities. And then you tried to figure out what your community was, who were your people, uh, and then once you figured that out, then you got a bunch of zip codes and you marketed the zip codes. Well, that worked for a while, then it stopped working. People didn't figure out why it stopped working mid market, stopped using it. But uh, There are a bunch of, you know, smart people at Axiom, Experian, Nielsen, Merkel, they started creating um, analysts models for large companies. Coca Cola, Pepsi, Best Buy, all the big stores would pay hundreds of thousands of dollars to get these reports done by these companies. And they're doing that now, you know, and it takes weeks or months, but they're super valuable because you get tons of insight into who your customers are. You're using it for messaging, you're using it for marketing, you're using it for upsell, you're using it for cross sell. It's so powerful. But okay, so mid market doesn't have access to that. What we've done is we've created a, uh, do it yourself SaaS platform that's very affordable. Less than a tenth the cost of what those other ones are doing. We do ours in minutes and a customer of ours gets a license. They log in, they upload some of their data, it's automatically analyzed and we give them all the sociometric, psychographic and demographic information they could possibly want on their customers. All the uh, explanations on what all that means, what to do with it. And then when they're ready, they can use that math model that got created to find more people that look exactly like the ones they need. They actually get more power in their hands than these Fortune 500 companies. Because ours is not just a one time report that you buy once or twice a year. Ours is living, uh, breathing, analytic, uh, tool. So you could ask our platform to do an analysis for you 10, 20 times a day when you're trying to think about and work on problems, problems. You know, slice it this way. Okay, Slice it that way. Uh, big companies can't do that. Right?

Himnish Jindal: So you've gone and you've brought what was restricted up to those big companies down to the mid and small market and then from there also expanded the capabilities that it has.

Ed Lorenzini: It's exactly right. So why isn't everybody in mid market jumping on it?

Himnish Jindal: Right?

Ed Lorenzini: Uh, well, in some ways they are. We have hundreds if not thousands of use cases that are happening in our platform every day from our customers. But uh, largely that mid market has not known that they can have this. They didn't grow up with it. They have never worked in Fortune 500 companies. They uh, don't know the power of it. So you know, we've got a uh, really big challenge to educate. As soon as we start educating mid market and they know it's available, they know how affordable it is, they know the power, it becomes very easy to get it in their hands. But, you know, getting them to know about it is, is, uh, a bit of a challenge. So we had to come up with kind of a marketing strategy that was going to work for them. So we started using the technology adoption curve. We said, want to start with early adopters, and then once the early adopters get it, you've got the secondary adopters, the followers that come behind them. So now we're working on how to reach those guys. And then ultimately we'll get the laggards who are like, all right, if you're making me have this, I gotta have it. So we're using the technology adoption curve to shape who we're going after and how we do our messaging and who we're looking for. And it's been effective.

Himnish Jindal: And that can't be easy, right? It's much easier said than done to say we're going after the early adopters, because who are the early adopters? How do you figure that out and

Ed Lorenzini: how do you find them? Right. So we've got a marketing, uh, strategy that we do for our company that is built around information. So we're sending a lot of emails out, and we're writing these very short emails in a way that would attract an early adopter's attention, kind of teeing up the possibilities, showing them m that there's something out there that could do what they're thinking about, but they never thought they could have it. You know, a laggard is like, uh, that email doesn't do anything for me. So, you know, 70% of our emails don't get read. But when you get somebody who's really on top of the game and wanting new stuff, it resonates. So we just have to write the message. Right.

Himnish Jindal: And I guess going back from that, I have to ask, what does it look like when a client actually uses your platform?

Ed Lorenzini: It's amazing to us anyway, they get unlimited training, but it doesn't take long to catch on. Typically what they'll do is they'll take their customer list, just first name, last name and address. They'll upload their customers in our platform. Our platform automatically looks them all up because we have everybody in the US So we can find them. We look them up, we grab all 360 of their variables, and we do all the machine learning, all the, uh, algorithm building, all the clustering, and we create a math model that perfectly describes that list they just uploaded. So now the first thing they can do is see who's their best ones and who's Their not best ones. We score everybody against that ideal model. So, so now you're going to know who your higher value customers are in terms of their alignment with your product. And then the next thing we'll do is just give them all the data we have. We totally want to empower mid market so we're giving them all the data we have. They don't pay extra for that. Second thing they get to do is look at all the reports. So very clean, neat, easy to read and understand reports with lots of information on who their customers are. As soon as they start seeing who their customers are it just starts ringing bells. Oh, we could use this strategically for this kind of decision. And then the third thing they can do, once they're ready, they can uh, just invoke that math model they created and say give me a hundred, give me a 'Thousand, give me 10,000 more people, you know in the US that look mathematically exactly like me, that I would never know were out there and I would never know these uh, underlying data driven insights. But the math model told them to be and it's holding them in the math model, you know, give me more people like that and then they'll download those and then they'll be able to prospect to those people. Uh, and then once they do that they'll get some responses. Some people respond, some won't. They'll take the people who responded, put them back in the platform, build another model and these are the people who are now not only great customers for me, but also responding to that ad I created that campaign I've got. So it's even more fine tuned over time. We've spent a lot of time building a very easy to use interface. All you use is a mouse to do everything. I just told you, you're not having to type any words, you don't have to do software. And we do it very, very fast. So you're getting it in near real time.

Himnish Jindal: And can you put that in a real world example for us?

Ed Lorenzini: Absolutely. So uh, a high end clothing store in Southern California, they sell brick and mortar in California from their stores there and they sell online everywhere else. They had our platform, they uploaded their customers and they got a lot of great data driven insights that they were able to use. So one of the things they found is that uh, their customers are way more wealthy than the rest of the US So that immediately tells them that you know, their customers are not going to be price sensitive, they'll pay more for that kind of thing. But the other thing they learned in Our platform is that they like exclusive offers from brands they love. So when they read that, they're like, oh, my gosh, we have not been doing exclusive offers. All we have to do is add some words to our offers and make them exclusive. Another thing that was super interesting for them is that they learned that the most predictive variable for whether you would be their customer or not is this one. Are you an active investor? It was higher than everything else. Number four was, would you buy clothes at a women's clothing store? That was not the most predictive variable. So our math model found that it weights that higher than would you buy women's apparel. But women's apparel is weighted in there. And so now when they go out to find new customers, the math model is using all the right variables in all the right proportions to get them who they need. And one variable is in there. No marketing company could ever have figured that out on their own. You had to actually stop and do the math on all the variables to get that. But that's been super powerful. And then as they looked down through the report, they saw another one that changed everything for them. They were getting ready to launch a petite line of clothes. So they were selling regular size clothes, they were selling plus size clothes, which were a little larger. And then they were, uh, working with a marketing company that said, oh, what you need to do next strategically is sell petite size clothes. So they were starting to move in that direction when they got our platform, ran the information, and they found out that not only were their customers not buying petite size clothes, there was almost nobody in the US Doing that either. So it was not a good idea. But what they saw in the report was that 40% of their customers were regularly in the habit of buying jewelry somewhere else because they weren't selling jewelry. And only about 23% of the US is regular in that habit. And so our platform will tell them exactly by first name, last name who those people are. And so they said, oh, this is what we need to do. It's so much cheaper to go into a line of accessories, handbags and scarves. They're doing right now. They're about to do jewelry, and they're not even going to go to petite. That was way more expensive to go into it anyway. And so now they're creating an ad that says, hey, you've trusted us for years with your clothes. Now you have an opportunity to buy the jewelry that was designed to match everything you're wearing. I mean, it's just amazing for them. And that was A strategic insight that changed everything for them.

Himnish Jindal: And what's the biggest success you've had recently with Analyze 360?

Ed Lorenzini: I'll give you a couple things that are kind of exciting for us. We have two companies that are on our platform that love it so much they want to buy the exclusive rights to the vertical they're in so no one else can have it. That's. That says a lot about what you're doing when somebody's going to pay you a lot of money to buy the vertical so no one else can have it. That just speaks to how much power we've built into this. So that was kind of exciting for us, and we're working on that now. Um, a couple other things that are pretty exciting. Just, you know, internally, we're building out another capability that's going to be amazing. Zoom Info is a B2B platform that people use and pay a lot of money for. They say that they have intent data. So what they call intent data is they find out that somebody from Company X went to that website, they keep track of that, and now, you know, you can go into Zoom Info and say, tell me people who are looking for this thing. And they'll tell you, oh, people at Company X are looking for that thing because they were recently at that website. So here's what's exciting. We are about to launch the equivalent of intent Data on the B2C side, but it's a hundred times more powerful than what they're doing. Our intent data is this. We've just acquired all the data for all the cell phone activity for the whole US and we know where everybody's cell phone is, latitude, longitude, and time all day long. And so we get to know the advertising id. So we're going to allow our customers now to geofence an area. Let's say you have a jewelry store, and, uh, the competitor jewelry store is down the street. You can geofence the competitor's jewelry store, figure out who's going there, grab those guys, because they have intent to buy jewelry, and now you can launch ads to them because you were just able to figure out who's all going there, and you can bring them to your place. In addition to the consumer data, we're now about to put intent data, but it's intent data on where you put your body, not where you put your electrons. And that's much more powerful. So that's exciting for us, too.

Himnish Jindal: There's so much data everywhere in this. What about privacy here?

Ed Lorenzini: When you sign up for apps like uh, Life360, the weather, the airlines apps, all those apps, you give them consent to use your geospatial data and report it. And so that's where that's being collected legally. It's being collected under U.S. uh, laws. And so it can be used as long as they're not giving out who that person is. And we don't really need who that person is. We just need to know that that cell phone went there and what's the advertising ID of the cell phone? So we're allowed to have the advertising id. We give you the advertising ID and you don't know who it is, but you send them an ad and they're like, yeah, that's cool, I want your stuff. And then you find out who they are when they want you to. This is just uh, another application we found for that. We're going to let the small to medium sized businesses, you know, really benefit from it. So we follow the fair credit and lending rules, we follow all the HIPAA rules, we follow all the GDPR rules. We've got on our board of directors is uh, a lawyer who, you know, keeps track of everything and makes sure we're in line. We've got privacy agreements, we don't use anybody else's data for anybody else and we don't let anybody else have somebody else's data. And we don't keep your data. You come in, you analyze it, you go out and we don't keep it. Uh, and there's other things we do to protect privacy, but that's probably one of the most important things we do.

Himnish Jindal: So what are some of the biggest challenges that you've been facing recently?

Ed Lorenzini: Uh, the real challenge for us is finding enough qualified leads. We've got a great team, we've got a great product and we can close probably 30 to 35% of the leads that we get. But it's just hard to get qualified leads. People are saturated with offers, things that don't come true and you know, it's difficult to stand out as a product that works. So we're just having to do that, save one starfish at a time. We just take the time to do it right and eventually word of mouth starts happening. We're starting to see, you know, uh, hey, my friend said they've got what you got and I gotta have it and they sign up. So we're starting to see a little bit of that. But just qualified leads where our growth is limited right now by the number of qualified leads we can have.

Himnish Jindal: And I guess that's really just a big problem for a lot of businesses out there. Right. Because it sucks when you have something that works and works really well, but then you can't find somebody, Right? Yep.

Ed Lorenzini: You know, we go to trade shows and our booth is always packed with people who want to see what we're doing. As a matter of fact, we were at the largest, uh, leads trade show in Las Vegas called Leads Con in April. We brought, uh, VR glasses and we put our two minute demo inside the VR glasses so you could walk up and put the glasses on and watch the demo inside there and see what it was all about. Everybody loved that. And, you know, we got to have a lot of great conversations. A lot of people would be like, hey, can I, if I email you my data, can you analyze it right here? I'll be back in an hour, or whatever. I said don't be back in an hour. Just email it to me. I'll do it while you're standing here. Well, uh, we could do it that fast. Yeah. So, you know, trade shows have been good for us to get the word out and find qualified leads.

Himnish Jindal: And one of the big things that everyone loves to talk about, AI, right? AI. It's hitting everything hard right now. So what are your thoughts on the AI shift? How are you bringing AI into Analyze360?

Ed Lorenzini: So everything we do, it's underpinned with math. So we're creating algorithms and models, and it's all mathematically derived because it has to be exactly right. Well, if there's one thing that AI is bad at, it's math. And so you have to be careful with what they come up with. So we do math the old fashioned way by doing the math. But once we have the math and we've created these reports, AI is great at reading the report and summarizing them and giving you the salient points. So we're actually leveraging, leveraging A.I. at that point, we'll create four or five, uh, very mathematically driven reports that have a lot of great information in it. You know, your customers are wealthier than the US Your customers do this way. More than that. I can read all that. It could package it all up, it can make it look super pretty and, and it can highlight things that you might have missed. And so that's how we're leveraging AI in the platform. We're bringing it, you know, right to the point where, uh, it's explaining to our customers what's in their reports. We're actually looking at taking a second step with AI and We're having to go a little slower. We want to see if we can let some of our customers create marketing campaigns in the platform. We have all, we derive all the information that you need for a marketing campaign. But you know, what should the messaging be, uh, what kind of images should you use? And AI, we're experimenting with AI right now to see if it can pick those. We're getting some issues there and so we're kind of going a little slower, more cautiously and we may never get there because we don't like, you know, what AI is offering. In that case.

Himnish Jindal: I think that that's a really powerful use case for AI because you're actually using it to make your segmentation smarter. And I know you've mentioned that you're rolling out this new thing with AI and going for that second step. So I think that's actually a pretty perfect segue into what's the new stuff coming with. Analyze 360. What are you guys looking to do?

Ed Lorenzini: Yeah, I kind of hinted uh, at it earlier with geospatial data for cell phones. You know, now that we have all that data, we've uh, indexed it all. We've shown we can leverage it. Uh, we're going out to a couple of our best customers and doing some experiments with them. So we're creating campaigns for them that they can push out on social media. Since we have advertising IDs, they can push that out to Facebook, Snapchat, and we uh, can do it very specifically and hyperlocally too if they need it. And so we've got customers experimenting with that, giving us feedback on how that's working. And so that feature is coming in our platform and that's uh, something that's going to be very useful in a lot of cases. For example, we've got a marketing agency as a customer of ours that markets on behalf of Andersen Windows in uh, two large markets, Houston and Kansas City. And so they've been using our platform very successfully to go to high end homes and say, do you need your Windows replaced? And we know how long someone's lived in a home. We know what their loan to value is, we know what their credit score is, we know how old their house is. So it's the perfect scenario to find houses to sell replacement windows to. But now what we've got is all the advertising ideas of those people who live in these high end neighborhoods. So we're literally doing this now, geofencing the high end neighborhoods, getting all the advertising IDs and they're going to send them ads on social, uh, media for those kind of products. And they're loving this because they're going to be able to completely target and saturate an area and find those few people, you know, who want what they have. So uh, that's what we're doing. Once we work out these use cases, then we're going to finish building it out and putting in the platform. And you know what our customers will be able to do is look at a map of the whole us, Find the geography they want, draw a little polygon around that thing and say give me every person who's in there, give me all their Cell phone advertising IDs. I want to send them something and they'll be able to do that, push ads out to them.

Himnish Jindal: You've basically went and just made it really easy for them to do everything right because they can get the data, they've got the AI to extract all the insights. So now they know exactly what to do with the data. And now once they can go and just do that all on your platform, that's really powerful.

Ed Lorenzini: And for people who get on our platform, they're going to have such a leg up on their competitors. We've got a marketing company uh, that markets on behalf behalf of privately owned jewelry companies all throughout the US and you know, they're always competing with, you know, Jared's K's, all those jewelry stores and they put their jewelry store next to one of those, uh, and they see a lot of people going next door and not coming in their place because they haven't heard of them. So what we're working on, experiment with them right now to geofence all of the competitor jewelry stores, figure out who's going there and saying hey, if you're in the market for jewelry right now, we got a sale. You know, it's this, this and this we offer and they know what their competitor offers. You know, we offer something better than the competitors. And so it's a great way to get very warm intent type leads that

Himnish Jindal: can bring about a really big impact for these companies making that much power accessible for the mid and small market.

Ed Lorenzini: Uh, probably the largest company we have as a customer right now is probably 300 million a year in revenue. So that's definitely the high end of mid market. But the smallest customer company we have right now is one person. One person can use this. It's a company that invented uh, lanyard that they make in their bag in their garage and you hook your golf bag to the golf cart and when you bounce around your golf bag doesn't flop out. And they've sold hundreds of these things, but not millions. They've sold hundreds. And so they found our platform and they started using it. They uploaded their current customers and it was analyzed in our platform, and they realized that, you know who's buying this? The spouses of the golfers, the wives of the guys who golf. And they're giving it to them as a gift. So when they learned that, they started doing advertisements at Father's Day graduation. Get one for his birthday. They were doing, uh, deals with clothing stores. Hey, if you buy this, you get one of these lanyards for your golfing spouse for free or whatever. And that was super effective for them. But, you know, they. They didn't know who was buying these lanyards until they started analyzing them and figuring them out. And it was just one guy making in his garage. And now they've been able to grow. So, you know, it's useful on both ends of those spectrum.

Himnish Jindal: And how do you go and support new clients, especially those that don't have a team that can be dedicated to this, to really go and get up and running with Analyze360.

Ed Lorenzini: That's kind of the nice thing. We have made this so simple to use, so intuitive, that, you know, you're only using a mouse to do everything. So if the co founder's got to do everything himself, he'll be able to do this. But, you know, if you can get somebody to specialize in this, we'll train them. You know, we'll spend as much time as they want, tell them how to think about it, showing them what to do. We've got a small marketing team of our own that'll come alongside and help them out for the price of the license. They don't have to pay any more for it. Uh, we've got a team that will fix M files that they're trying to upload and aren't going. We've got a team that'll fix that. So we really try to make sure that our customers are not stuck because of the technology we want them to work on, the problems they're better at working on.

Himnish Jindal: And I just want to wrap up with one question that I ask every. Every single podcast guest that I get. What's the most overrated piece of advice you've encountered recently?

Ed Lorenzini: I don't know. Maybe it's something along the lines of, you know, keep trying what you're doing, eventually it'll work out. That's not always true. You know, you could keep trying what you're doing and banging your head against the wall. And I think the counter to that kind of advice is if you're trying something that's not working out, go find some people to help you think about it because you're going to bring in a lot more ideas you're going to get out of the box you were stuck in. And so, you know, that's probably the antidote to that advice.

Himnish Jindal: I think that's a great note to leave it off on. A great thing to think about.

Ed Lorenzini: Ed Lorenzini all right, thanks so much

Himnish Jindal: for, for those people that want to go and learn more about Analyze360, where can they go?

Ed Lorenzini: Yeah, well, easiest place is to go to our website. You can go to analyze360.com or analyze corp.com will be there. You can send me an email and I'll respond to you. My email is ednalyzecorp.com or if you go to our website and you're looking to get in touch with somebody, if you look at the telephone, uh, number on who to call, it will literally ring on my phone. Cause it's. So just go to our website, get in touch with me, and, uh, we'll get you moving.

Himnish Jindal: Awesome. Thanks for coming on, Ed. As we end today's episode of Making Martek, I'd like to thank all our listeners. If you enjoyed this episode, please make sure to share this and subscribe to our show so you don't miss the next one. I'm your host, Hymnish Jindal, and I look forward to seeing you on the next episode.