LPRC - CrimeScience – The Weekly Review – Episode 243 Ft. Christina Burton (LPRC)

Episode Date: July 23, 2026

In this episode of the LPRC CrimeScience Podcast, new host and LPRC team member Beau Nutter sits down with LPRC Research Scientist Christina Burton, Ph.D., to discuss new research conducted in collaboration with ALTO. They explore the report’s key findings, the research process, and how the results can help inform evidence-based strategies across the retail loss prevention and safety industry.

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 episode of crime science podcast here at LPRC. I am your new host for this week, Bo Nutter. I'm a research scientist here at LPRC and I will be helping with recording podcasts going forward in the future. So today we have have Dr. Christina Burton as our guest, and she's going to talk about the report that she has written. Thanks, Bo. Yeah, I'm Christina. I'm one of the research sciences here as well, just like Bo. I typically head up our supply chain protection working group, but I like to say I have my hands in a lot of

different cookie jars, so I also work on our Voice of the Victim Initiative with some of the survey work I do on employee sentiment and experiences with violence, and I also work with some of our other innovate partners like Alto, who is the kind of source of this particular project, as well as the NRF and PNG, so I tend to work on some of their projects as well. Great. So for some listeners that may not be familiar with Alto, who are they, what do they do, and what services they provide? Yeah, so I kind of like to view them as kind of a victim advocacy service.

So what they do, and Alto would love to tell you more details. But how I interpreted is they're very much in making sure that you as the retailer that are subscribing to their service are getting the representation that you need for your court cases, compiling the evidence that's required, talking to the prosecution in the ways that you need them to or getting law enforcement on board with whatever things that you need, again, to get the strongest case as possible for some of the events that happen on your store. So that's how I kind of view them through my work with analyzing some of their, what they call touchpoints. So what are they actually doing as part of that interaction, as well as some of the court cases that they've been working on?

Okay. Something that I've been wondering, I'm sure others have been wondering, is what stage do they get involved in? Are they just after an event has happened, or can they be involved throughout the entire incident? Yeah, so I think it just depends on when you utilize it. services whether they can be either or, right? So let's say you have quite a few cases that you've been working on and then you get Alto involved after the fact. They're obviously not going to have been involved at the very beginning. But if you are using them from their beginning services, or at the beginning, right, then they can help inform like, hey, you know, we're, and that's part

of the work that we're doing here is trying to inform like, hey, these are the types of evidence that are going to be really important. These are the things that you need to be thinking about as you progress your court case. But they're there from the very beginning. if you're using their services from the beginning, if that makes sense. Yeah, it does. Thank you. So can you give a brief of view of the reports and what you're trying to understand about Alto's impact on court cases? Yeah, so courts are kind of tricky in the sense that there's a lot of dynamics that happen in a court case. So you might have, you know, if you're talking about even in a police case, you have an incident that happens. The police officer on duty

might make a decision about an arrest or not, or they might do it after the fact, right? But, you know, what they see on site kind of influences what that arrest is probably going to be for, what that charge might be. Once it gets the court, that's where it can get, you know, a little different. It might start at a specific charge, but through a series of negotiations, it might change what that charge actually is. And then the punishment might change just depending on the circumstances of that case. So the courts are very, very dynamic, which is both interesting, right?

want them to be dynamic so that their understanding of, you know, different circumstances that might come across their door. But it's also challenging to study from an analytical perspective because they're so dynamic. So what we were trying to better understand is what is Alto specifically doing during these court cases that might be influencing those outcomes and or what are they impacting at maybe those beginning stages of the charges, right, that might be influencing later outcomes through the process. And so we're really trying to see what is Alto's influence broadly. And so this is actually split up into two different. R2Ps. I have the second one that will be coming out shortly as well. So I won't talk too much about that one. But this one was about more

on the front end of what's happening in court cases. So like, what is the actual charge that is going through to this court. And then what is the impact of, you know, is it getting dismissed outright? Is it, you know, going through the actual court process and actually getting a prosecution? You know, those kinds of things. So that's what we're trying to do in this first R2P was kind of understand what are the different like possibilities of charges that Alto is doing versus didn't do for this particular retailer. I won't say who to protect that. identity, but then do those charges or do those differences impact kind of broadly outcomes? I don't go into too much details about like the actual length of time of punishment in this

particular R2P. You'll have to wait for the next one. But kind of just like, you know, was it actually processed through the court system or did it get dismissed for different reasons? So that's kind of what I cover in this particular RTP. Okay. So how did you compare the pre-alto and post-alto cases? Yeah, so Alto actually provided this data set with the retailer that they're one of their clients that they're working with. And so they had cases that were designated as been processed before Alto's involvement or without Alto's involvement. In part, they kind of overlap a lot. But the post-Alto cases are the ones in which they actually had a hand in, you know, either collecting evidence or talking to the courts or whatnot. So this is self designated by Alto of which one did they actually interact with.

And this data was provided to you through Alto? Yes. So they've also provided me their own internal touchpoint data that I've been working through. And there's a lot of richness in there as well. But in this particular case, it's they had like the list of cases from their retailer. And they were the ones that kind of designated like, yes, we worked on this one or no, this was the retailer only focused a, case. Okay. And so being a research science as well, I know that data can be very difficult to work with. Yes. Were there any challenges in cleaning, analyzing, or maybe anything going for in the

future that can make it an easier process for you? Yeah. So one of the challenges that we had here, and this is also a challenge in some of the other data sets, is that charges are weird. And what I mean by that is that an incident can have multiple charges associated with it. So, you know, one offender could get a, you know, a shoplifting charge, a resisting arrest charge, you know, a grand theft charge, like, multiple charges can be under that same individual or that same incident. And it's not always easily separated in the data. So one thing I had to do with this data set and something I'm working with other data sets is creating codes such that it looks for key terms and keywords, and then it pulls it out and says, yes, there was one incident of that key term within the charge

data. So that is something I had to employ for this particular data set. And sometimes with all data, things are miscoded or they're not cleanly coded. So I had to do a little cleaning, but that's normal with a lot of different data sets. It's not particularly unusual here. And it's just making sure things are coded correctly and that's, you know, that's just a normal part of the process so that we make sure we're as accurate as possible. Yeah. So what were the biggest findings that came from this report, especially around charges and court outcomes? Yeah, so I would say that there's kind of two things to take away from this particular R2P. One, it looked like just with this data set that Alto had a wider range or wider variety of charges that they were able to process or at least get to the beginning stages of a process within the court system.

Now, this could be for a couple of reasons. It could be that more cases were just being brought to Alto because they either, well, we're paying for this service and we feel confident that they'll be able to now process these cases because we now have a manpower to do it. or it could be that just it happened during that time period, that those cases were what happened. You know, I'm a little less thinking that that was the case just because the time periods were pretty similar, and I talk a little bit about time periods in the next R2P, but they're roughly around the same time that these incidents were happening.

So Alto's doing something, right, that might be encouraging maybe trying these other cases rather than only focusing on petty theft. So, you know, of the cases that were charged, like, 19% of them had a petty theft charge without using alto services. So it seems like the retailer in question was mostly targeting those cases to be prosecuted. Like that might have met their threshold of, okay, that's what we're going to prosecute. Versus Alto had a wider range of options. And they still had more cases in that post-alto period.

So, you know, there were 48 cases with just. the retailer of Petty Feph versus 65 with the use of Alto. So kind of increased the number there too. The second thing that Alto seems to be doing is there's something going on in terms of actually getting cases processed through the court system. So something that kind of popped up in the pre-Alto data or the retailer-only kind of data is that a lot of cases were closed either due to insufficient evidence or lack of the investigative leads. So that accumulated to roughly 90% of all of those cases somehow got dismissed

for that reason or it just didn't get to court at all versus those with Alto that diminished to about like 53% of them got removed before it actually got prosperous of the case. So Alto is doing also something, I'm not sure what, but they're doing something to kind of get it to court rather than having it dismissed outright or before it even gets there, you know. So those are kind of the two takeaways, at least from this R2P. Alto is doing something. I'm still uncovering, you know, all the things that they're doing. And I'm sure they would love to tell you all the things that they're doing.

And I would be more than happy to have them tell you all the things that they're doing. But they're doing something to get cases to go to court and to get more cases to court is kind of the two takeaways I see here. Okay. And so you talked a little bit about this kind of near the end of your paper where you said that there are more cases with Alto than without. You kind of speculated on it a bit just then, but why do you think this would happen? You gave a few reasons, but are there any that you would think are more likely than others as to why there was such a difference in just the sheer number of cases? Yeah, and I think it kind of ties back to what I've described Alto before, which is they're mostly invixtriced.

advocacy, right? So they seem to be acting like your biggest cheerleaders in trying to help you get those cases through. So they're going to, Pester's not the right word. They're going to greatly encourage you to actually go through this process to try to get those outcomes rather than shy away from going through the court system. So I think one of the ways in which they're doing it is that it is literally their job to make sure that you get your voices heard in the court system. So I think, they're doing that in part by, you know, increasing those cases, getting them across the finish line as much as they can. Now, not all cases can get across the finish line. There might be something about the case, insufficient evidence, and that might be outside of what Alto or the retailer can

do, right? But they're going to try to get as many as possible, again, to try to help you as the retailer is what it seems like is happening here. Now, I can't necessarily confirm that. I would probably want to do like an interview style or a survey at Alto to figure exactly what they're doing with their services. But that's the impression I'm getting with conversations from them and explaining why they're seeing some of these things in the data. Okay. So I understand how the analysis works in this, but maybe for listeners that wouldn't

understand, how could you explain this where that isn't a limitation that before you have smaller number of cases versus after you have a large number and it's not really impacting your analysis? Are you asking in terms of, you know, percentage differences, or are you more talking in terms of, like, you know, what would we consider more of a bivariate statistic? Like, kind of pinpoint a little bit more of what you want me to talk about here. You can talk about it either way.

Okay. So one thing to keep in mind with this analysis is that this is not a bivariate analysis here. I didn't have enough cases to really detect if these differences are due to Alto's influence. Meaning, you know, I can't say with full confidence, right, that Alto is the reason that we're seeing these differences in these cases. I won't go into the math necessarily. But what we can say is some descriptive findings here. So on a basic level, what I did was in the data, I said, okay.

If you are coded as having closed because of insufficient evidence or lack of investigative leads, how many of those total cases happen relative to all the cases that were coded, right? And that gives me a percentage number. Now, obviously, if it got fully processed, that's a different value. So in this case, only 11 of all the possible cases that did not use alto services got fully processed. And that comes out to about 6%, which you can see, obviously, in the R2P. In contrast, there were 98 cases that were fully processed when using auto services compared to a total of about 200 or so. So that's a much higher percentage. So the start percentages

tells me something, right? It may not be able to fully pinpoint that auto is the reason there could be other things happening. But that's a good hunch, right? That because there's such stark differences in the percentages of the cases, that that's likely suggesting something that Alto is doing. But there could be other reasons, right? I don't have the perfect statistical constraints to perfectly say, and I don't think anybody ever would, right, that Alto is a reason for these differences. But we have a close second where it looks like the Alto services have a higher percentage of process case than those that don't. Why? I'm clear. We didn't do the analysis to figure that out, but that's still pretty convincing that something is happening.

Okay. And what are some limitations that are in this analysis, and where do you see this research going next? Yeah. So part of what I alluded to, one, is because I haven't done more, let's say, stringent statistical analyses here, I can't definitively say alto is causing X, right, or Alto is causing these differences. I can say it's very suggestive, though, based off of these dark differences, but I can't confirm it necessarily. So if I were to get the perfect data to try to figure this out, I would want more cases that did not utilize auto services, preferably during the same time period,

and preferably either with the same retailer or with a similarly built retailer. Again, I won't say who, But it would be kind of like, you know, if we had an apparel-based retailer like Gap, then we would have a similarly based apparel retailer as well, right, of a similar style. It was not Gap in this particular analysis. But, again, to try to give that point here. The other thing I would want to control for is, again, courts are very complicated with their dynamics. I would really want to understand what happened in those specific cases, right?

You know, where was the jurisdiction that this was happening in? So that tells you the legislative landscape of what is and isn't acceptable or what is what's called the buy rate, you know, when we're talking about plea deals, if that's happening here, you know, what does that actually look like. I don't know, for example, what evidence was brought forward. So some of those cases that got processed might have had stronger evidence. And maybe that's what Alto is doing. It's not that Alto exists. It's that they secure stronger evidence for cases. I don't have that information. And I would love that information to better understand. what's actually happening in those court dynamics that might be influencing these cases. So those are just some of a couple of the examples and also it's only one retailer, right? And in this particular data set it's not fully representative of the United States. I believe there's only like two states that are represented within the data set. So having more states to better understand those legislative areas and more retailers

would better see across the United States you know what's actually happening. in this data. So those are things we're hoping to get in the future. And again, if you're interested in participating in some of this, again, just for the industry's sake to better understand, you know, it's great that we can prevent certain incidents, but, you know, incidents are still going to happen. You know, how do we get that across the finish line from a prosecution standpoint? And so better understanding those dynamics, I think, is beneficial to everybody in the industry. So if you're interested in working with us on some of that data, you know, reach out. We're more than happy to get that process rolling.

And kind of to sum it all of, what do you think of the biggest practical takeaways for retailers or loss prevention teams? Yeah. So I think that one thing that's been neglected for quite some bit, and I'm not saying everybody neglects us to be clear. This is a generalization. But we often neglect kind of what happens after the incident happens, the right of bang. We are often focused on let's just prevent to make sure it never happens in the first place. That would be great if that could actually happen. But I think until that point is reached, we still have to figure out how do we either punish or take accountability for

some of the things that happen after the event. So doing more research on how do we actually achieve accountability when people, you know, commit that action is really, really important. And I think we sometimes lose sight of that because we're so focused on the left of bang, right? We're so focused on the prevention part. And I'm not saying we shouldn't focus on that, but you're still going to have incidents happen until we reach 100% prevention. And so until you get to that point, you still got to figure out, okay, well, how do I prevent people from being repeat offenders, or how do I prevent people from continually causing harm?

And so by better understanding, well, this is one leverage you have, right, going through the criminal justice system, this type of research should, overall, help the industry understand these are factors that are important for prosecuting cases. And this is what we also need to put research towards. I hear a lot of people talk about, you know, they want to hear more about prosecution after or things like that. So I really do think a report like this is an amazing resource to have. But that brings us to the end or recording for today. Thank you, Dr. Christina Burton for D.C. Just Christina is fine. Thank you to all of our listeners.

And if anybody wants to read this full report, it will be on our knowledge center. And we will see you next time on the Crime Science Podcast. Bye, y'all. Thanks for listening to the Crime Science Podcast, presented by the Loss Prevention Research Council. If you enjoyed today's episode, you can find more crime science episodes and valuable information at LPRsearch. 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 Loss Prevention Research Council.