LPRC - CrimeScience – The Weekly Review – Episode 246 Ft. Justin Smith, PhD (LPRC)

Episode Date: August 13, 2026

This week, Beau Nutter sits down with Justin Smith, PhD, to discuss a recent LPRC Research2Practice article focused on theft techniques. Justin shares insights from the research, breaks down common methods offenders use, and explores what retailers and loss prevention professionals can learn from these behaviors to strengthen prevention strategies.

Hi everyone and welcome to crime science. In this podcast, we explore the science of crime and the practical application of this science for loss prevention and asset protection practitioners as well as other professionals. Hello everyone and welcome to this edition of the Crime Science podcast here at the LPRC. I am your host today, Bo Nutter, and I am a research scientist here at LPRC. And today we have a special episode with Dr. Justin Smith, where we'd be talking about his recent R2P, his research to practice, about how shoplifters take merchandise,

an overview of reported theft techniques. All right, so let's get right into it today. Can you introduce yourself and share your research focus, Justin? Yeah, absolutely. Bo, I've got to say, you're going to give me a run for my money because you have a great radio voice. You really do. This is the first time I've heard it, and I think I have a good radio voice,

but, yeah, you kick things up a notch, so appreciate it. Yeah, so I'm Dr. Justin Smith. I'm a senior research scientist here at the LPRC. I currently oversee our product protection working group and any product protection related projects. So what that means is I'm involved in a lot of store trials where we are trying to implement some loss prevention technology and then see the effect that that has on theft and on sales. also do a lot of offender interviews to understand how they think about loss prevention technology and deterrence. Do a lot of customer interviews to understand how they think about the buying decision and friction that solutions may introduce into that buying decision.

Right. So we're a lot of different hats here at the OPRC, but currently I'd say I'm mostly focused on product protection and specific. offender interviews, which is where this R2P came from. Great. So for the listeners who may not be familiar, can you give us a brief overview of this report and why understanding theft techniques is important for retailers? Yeah, absolutely. So one of the key takeaways is that we interview offenders on a regular basis, and we try and get inside their head a little bit to understand how it is they make decisions, how they select stores, what types of merchandise they go after, how they get the merchandise out of the store, what deters them or slows them down or stops them completely,

what they do with stolen merchandise and so forth. And the reason that's important to understand is from a prevention standpoint, if we know how offenders are getting the merchandise out of the store, for example, then we can implement deterrence to, um, hopefully stop them or slow them down or maybe even prevent them from you know making some of those bad choices in the first place so understanding offender decision making is absolutely crucial the work that we do here at the LPRC to really get how they think so we can devise countermeasures and solutions to disrupt that kind of thinking all right so getting into the methods a little bit how did LPRC recruit participants and gather information from this

from them for this analysis? So we recruit shoplifters a lot of different ways. Primarily, we post ads on job-finding websites, advertising the studies that we do, offering to pay them for their time. We compensate all offenders very well. We give them a $50 gift card. We also do recruiting through some of our law enforcement contacts

here in the Gainesville, Florida area. We recruit through homeless outreach, shelters, drug and alcohol, rehab facilities, the court services. And then we also do something called snowball sampling. And what that is, basically, is I get an offender in the lab, I interview them, I get them to trust me, and then I ask them for referrals to friends and family members who are also involved in shoplifting activity. So all of the offenders that we interview, they all get a standardized survey.

So that way we're collecting systematic standardized data about how they approach that journey to and from crime, right? And why they shoplift and how they're doing it. And really all the offenders that we interview, that's just a big data pool. We keep collecting that data. And then we use that data to write articles like this one. Okay. And what was your sample size for this study, if you remember that? So for this particular one, I think we had 50 offenders that we interviewed it.

And for a study of this nature, would you consider that to be a good sample size? Well, for a semi-structured survey, we'd probably want a larger sample size. I think it's adequate just to kind of give us an initial understanding, but we always are adding more to that, right? you know, so it's a good sample size. And going a little bit into how you've recruited some of the interviewees or participants, what do you think is the best method? You said you had snowball sampling, you put out flyers, you had things along those lines, which one do you think is the most effective at getting participants?

Oh, gosh, that's a good one. Probably, I would say the snowball sampling, because once we get somebody in that really is, involved in these types of criminal activities and we build that rapport with them, that just opens up all those different doors. Because one thing that I've discovered in working with shoplifters is that they communicate, right? So boosters communicate with other boosters. And so when you build a rapport with one of them and they know, hey, I went to the LPRC, I did an interview, they treated me, well, they treated me with respect. I got paid for it. They're legitimate. You know,

they're not turning me into the cops. They'll tell their friends. And then word gets around, right? And so from that snowball, that initial person that you interview, you end up with a much larger sample. And so I would say that's probably the most powerful and one of the better techniques. The other thing, too, that I would add is that the sampling really is, or the responses that you get is really dependent on the sampling strategy. So for example, if we're recruiting from a homeless encampment, then a lot of offenders there are going to be stealing for a need, right? If we recruit from the drug and alcohol rehab facility, then we're probably dealing with people that have substance abuse and addiction issues. And that also can affect the snowball a little bit too. So all these

methods are kind of intertwined. But I think Snowwall is probably one of the more powerful methods that we have. All right. So getting a little bit more into the paper, what were the most common theft techniques reported by participants? Yeah, great question. Got to go back to the paper here. So probably the more common theft techniques were hiding items and something they brought into the store with them, like a bag or a purse. So out of that, that sample, that end of 50, we had 32 of our offenders, said that they hid items and something they brought into the store with them. They also indicated that they hit items and clothing as well. Now, I should point out that for this particular study, we gave them a list of different techniques

and had them check as many that applied to them. But when we rank order, the responses, what we see is that the majority report concealment. So hiding in something they brought to the store or hiding in their clothing. So I'd say that was a major finding. The other interesting finding here is that we also see a close to an equal amount of offenders walk out with the item without concealing it at all. So kind of brazen if you think about it, that it's like they're just taking the item and walking out of the store with it, not even attempting to hide it. So 30 of our 50 offenders said they just walk out without concealing the item. And then 20 said that they wear the item out. So, you know, we might think about some clothing here, you know, maybe stealing apparel, and they just

kind of put it on with what they already have. So again, this mix of a lot of our offenders using something they bring into the store with them to conceal. And then also we see some that are just very brazen or just walking out with merchandise. I'm not sure if you tracked this in your study. But was it common to see people having multiple methods or were they more often sticking to one method? That's a great question. And I'd have to dig in the data a little bit to see if that's the case. But we definitely do have a way of tracking that. So for example, with this particular question, I think the question literally is, just please report the theft techniques that you use and check all that apply. And then we have a list of, I think about, I think, like 10 or so different techniques. And then they can check each and every one that they use.

So you can have overlap, but we could go back to, like, the individual responses and just see, you know, do offenders stick with one technique or not. I actually like that, that line of thinking. And I, to be honest, hadn't really thought about it. But that, that is something that we could definitely do. So maybe, hey, maybe that'll be another R2P or paper we can work. together hopefully so a question that I'm a little bit curious about how did you initially come up with these different types of theft techniques so basically just a review of the literature on shoplifting also just some preliminary

focus groups and interviews the offenders and just kind of talking turkey with them about you know what techniques conversations with our retailers right and you know they talk about some of the problems that they see and how shoplifting occurs, product protection working group calls, or we've talked about like, okay, what are the theft techniques that you're seeing in your stores? So there's a lot of different ways that we go back to. And also there were some prior examples of offender interview guides in the academic literature that I borrowed from. And in those cases, a lot of times if you have, like, an interview guide that's been validated, it's always good to repeat those measures, right?

So a lot of different sources kind of came into this. But I think in the end we ended up with a pretty comprehensive list that reflects what our members are telling us, what other offenders are telling us, and then also what we're seeing in the academic literature. All right. So one key finding was that concealment was very common, but it was not the only important theft pattern. What does that tell us about how retailers should think about theft prevention? I think the key takeaway here is that there's not going to be a silver bullet one size fits all, right, that's going to address every kind of shoplifting. Addressing shoplifting is really going to be a layered approach. So the fact that they're telling us that they conceal, for example, that gets me thinking about ways to counteract that behavior.

So anti-concealment tags. So for example, there are tags that you can affix to merchandise that can, detect light and if that light is cut off, the tag will start screaming, right? So you can imagine if you take something that's got an out of concealment tag on it, put it into your pocket, you cut off the light source, it's going to start alarming. There's also certain loss prevention technologies that increase the size and the form factor of the product itself, right? I don't want to mention names here, but you can think of solutions that in some ways, in case, in case, the product and make it bigger. Those, I think, are designed really for concealment, right? Because then

if you've got the product itself may be small, but you can protect it by, you know, making the form factor larger. Different types of protective locking cases, for example, because if the offender has to get an associate to open the case, in many cases, they'll be deterred, and they won't be able to conceal at all. There's also different analytics that can detect. concealment, right, that work with cameras in the store's ecosystem and detect concealment behavior and alert the sock or alert APLP. So that's important. The other thing is, too, major finding that you have offenders that walk out without hiding the item. Okay. So that's a bit of a different problem than concealment. So now some of our concealment solutions, you know, may not really

work in that case. So think about how you might prevent that walkout. I like to think of certain stores that have greeters or people that are at the door or just staff that are attentive, hey, how you doing today? You know, and somebody walks into the store, they greet you, right? You know, that provides guardianship, and that shows that there's people watching. So an offender, hopefully, is going to be less likely to walk out with something if they anticipate that there might be an encounter with, you know, a vigilant store associate. it. So again, just kind of looking at what the problem is, in this case, concealment, walkouts, and then figuring out appropriate layered solutions to stop both.

All right. So sort of wrapping up here, what is the main takeaway for retailers? And where should future research go from here? So I'd say the main takeaway for retailers with this is that concealment is a problem as our walkouts, right? So we see that with our offender interviews. I think as far as future research, understanding more about how that concealment happens, like under what conditions do offenders feel comfortable to conceal would be interesting. So, you know, more in-depth interviews of offenders to understand some of those thought processes, I think would be great. Another good direction would be a test.

So if we have anti-concealment technology, if anyone wants to do a test of, like, say, those anti-concealment tags or those products, protection devices that make the form factor bigger or locking cases or any loss prevention technology that is designed, you know, either as a primary use case or secondary use case to address concealment, let's do a test, right? Let's find a retailer that actually wants to test this in the wild. Because when we do a test, the beauty of that is that then we can get results that are a little bit more generalizable, right? You know, depending on how we do it and how that sample is arranged, we might be able to get some better results. So,

definitely up for testing any kind of technology that is anti-concealment. I would also add that one of the weaknesses of this study is that we only interviewed offenders in the Gainesville-Forda area, right? So that's a limitation as far as generalizability goes. So it'd be interesting to interview offenders in other context, right? If someone wants to send me somewhere else to talk to offenders, I'd definitely be open to that, right? Because we may find that there's different patterns, right? There might be different theft techniques in Brooklyn, New York, or in San Francisco. Francisco or, you know, in Timbuktu, for example, right? So I think there's a lot of directions

for future research here. All right. Well, that brings us to the end of our podcast today. Thank you so much, Dr. Justin Smith, for joining me. And thank you to all of our listeners. We will see you next time on the Crime Science Podcast. Thanks, Bo. Take care everybody. Thanks for listening to the Crime Science Podcast, presented by the Lost Prevention Research Council. If you enjoyed today's episode, you can find more crime science episodes and valuable information at LPRsearch.org. The content provided in the crime science podcast is for informational purposes only and is not a substitute for legal, financial, or other advice. Views expressed by guests of the crime science podcast are those of the authors and do not reflect the opinions or positions of the Lost Prevention Research Council.