Welcome back everyone to Unboxing Logistics. I'm Laurie Boyer, your host, and we are coming today from Parcel Forum 2024. Super exciting. I have brought in some incredible guests. You're really in for a treat. We have the fellas from Better Trucks. And we brought on Tom Butt, one of my favorite guests who likes to come in and tell me everything I don't know about analytics.

We are going to be talking just about that today. Analytics and how you can use that data to really impact the customer experience. So, gentlemen, let's start here with Josh. Will you introduce each of yourselves and just tell us a tiny bit about your background?

Yeah, absolutely. Lori, thanks for having us. Thank you to the EasyPost team. I'm Josh Fredman. I lead the commercial team at Better Trucks. We've been doing our business for about four or five years now and my background formerly was in the commercial aviation industry working at United Airlines and network planning and alliances and business development.

Excellent. Yeah. Thank you so much for having us here. Mike Koleno, CTO at Better Trucks, similar to Josh been with Better Trucks really since the beginning for about four five years prior, prior to that worked in digital consulting through a very interesting period of time right around when the the iPhone and app stores came online, so really got a chance to work with some really large brands as part of that fun period of time.

And then prior to that, worked in financial services, worked for a global bank in various different business units predominantly in the technology domain. So.

Cool. And I'm Tom Butt with EasyPost on the customer success team. And my background is in supply chain and logistics operations for retail.

And I helped co-found a data product, now EasyPost Analytics, that helps provide insights to customers in terms of their shipping, their supply chain, and just getting them details on how to run a frictionless operation.

Awesome. Thank you so much for being here. Josh, I'm going to ask you to tell us a little bit about who Better Trucks is for any of our audience out there. If you don't know Better Trucks, Josh, tell us.

Yeah, absolutely. So we are a last mile parcel delivery company. We're based in Chicago. We cover about 25 metros in 12 states. We have a completely connected line haul network between all of the areas that we cover. We do a lot of first mile work pickups. We do a lot of middle mile work.

And so you know, our service offering looks a lot more like a national carrier that shippers are probably more accustomed to seeing.

That's awesome. And as, as you know, at EasyPost, I really, encourage everyone to look at diversifying your carrier mix. This is an awesome option here for you. So, that's something that you can check out, especially if you're in the Chicago area, obviously. Big time there.

So before we start today, I always like to make sure that our guests are able to come away with something that they can really take as an actionable item. So I'm going to throw it to each one of you. If people listening or watching today only remembered one thing from our discussion, what is that thing that you would want them to remember?

And I'm going to start with Tom.

Oh, putting me on the spot right away. No, I would say you know, having a, a, a, an overview of your analytics from a holistic perspective would be one of the key takeaways. Sometimes people make seemingly optimized decisions, but it's in sort of a vacuum from a data perspective.

So, if you can get that data all into one spot and analyze and look across, you sometimes see things in the big picture that you wouldn't see if you're just looking at any one little example. So I would say, again, centralize that data. Get it all into one spot.

So find a way to centralize your data. Get it in a spot so you have that holistic view. Love that, Tom. Mike.

I think as it relates to shippers today, especially as it relates to kind of the maturity over the last, call it three to five years, everyone has sort of raced to sort of build that two-day sort of delivery experience. And that has been sort of where the initial sort of goalposts were.

But I think there's a large amount of both quantitative and qualitative data that shippers should be looking at that really represent the next opportunities as it relates to serving their customers better. And then, you know, in part you know, the first step of, of being able to sort of take action on that is, is similar to what Tom stated, which is like, let's get all this data in a central repository so that we can start, looking at kind of those second and third level opportunities.

I love that kind of proactive approach is, what I'm hearing is be ready while we think we know what the customer expectations are. As you all know, those change constantly. So use data to look for those trends.

Yeah, I would, I would echo that. That's an awesome point. Like I think people have that two-day expectation, but if you can go above and beyond that, people are like, wow, these guys really know what they're doing.

They're getting me my, my order within 24 hours and setting a specific timeframe that they're going to deliver. That's,

And I'm hearing even the flip side sometimes, sometimes it's longer and it's okay. And people are like, Hey, if I can do this more affordably, or if I can somehow do that and it takes three to five days, I'm fine with that. All in the data, right?

Yeah, I think for me, it's it's more about how can you take that central depository of data and extract meaning easily that will improve the customer experience. And you know, that's something that we're trying to do regularly. And I think that's really important because it's all about driving that customer experience if you're a shipper, and and meeting or exceeding the expectations of the, of the client.

I love that. I think that we can, I'm a big data nerd. I love data, but we can get bogged down in it, kind of forget the human element, sometimes, and just be looking at numbers, numbers, numbers, and not realize there's feelings and people and all of that involved.

So. Awesome takeaways. Love it. So we're just gonna go ahead and dive right into our discussion today.

My first question: Analytics when it comes to the customer experience. What does that mean to you? What do you think it means today? And is it different? From yesterday. Mike, I'm going to start with you.

Yeah, I immediately when I think about this, the analytical side of of data, I'm looking first and foremost at sort of the qualitative side. And and then secondarily, the sort of quantitative side. The quantitative side is is easy for us to sort of, you know, kind of build into our tooling, put, you know, AB tests in place as it relates to everything from the tooling inside of the the hands of our drivers and the applications and software that we give to them all the way out to, you know, the information that we're providing back to the shipper in terms of, you know, how often is that package touched? Where is it touched? You know, do we expose some of our internal events so that shippers know exactly what's happening as opposed to like this package is just in transit. Right?

And then that ultimately, you know, travels all the way from kind of the upstream of like, you know. As you were talking about prior to us coming on here understanding whether or not that package has, you know, been sitting on a loading dock from the shipper and hasn't entered into the carrier network all the way down to you know, having the ability to present a you know a live tracking window to say this is when your package is going to arrive. Your packages, you know, five stops away, three stops away, et cetera. And so,

Can I ask, how do you balance that? And maybe Josh or Tom, you're welcome to jump in. How do you balance that kind of transparency with sharing? What are your recommendations? Like how much knowledge is the right amount of knowledge for the customer to have?

I think from a shipper standpoint, you know, first from, from our standpoint you know, we think of the, the shipper is the, for our customer, as I'm sure you guys do as well.

But obviously there's the, you know, and consumer piece. I think, in general, if you look at the shipper sort of landscape or profile, especially with my time in this industry, there's a maturity curve that is certainly going up. Right, and I think the mature shippers understand that the information and the value that they can extract from their carrier network as it comes to data is a valuable thing to them that they're comfortable not only using internally, but in some cases, shippers are okay saying you make this, this data driven decision. We just rolled out a feature around address correction where our shippers are now saying if you flag the, we understand now based off of your explanation how you flag an, an address as being as invalid, we're okay with that. That sounds sound.

If that happens, we are giving you the permission to reach out to the customer directly

Yep.

And allow them to correct that address on their own. Seeing that today versus four years ago

Yeah.

Is like a, a, a monumental shift. Right. And so there are shippers like that, that are, are well in the way of like meeting that maturity curve and profile. There are also a, a larger number who are just saying. I need the six events, you know, transmitted back to me as it relates to, I don't care about anything else. You're definitely never going to contact my customer directly. So it really depends as, you know, as it relates to like, how do we serve that back up to the appetite of the, of the primary customer in our standpoint, the shipper.

Tom, where do you feel like maybe there's differences? Or do you have?

No, I, so I think, great points. One thing I would say is like, with respect to the customer, I think it's really important to set a framework for, What is the, what is the experience you're looking to define? And what are any, what is that ideal experience? So that then as you look at the data, you can look at any points where The customers may be not getting the experience that you would intend or design. And so to Mike's call out, you can then say, here's points within this, that there's something going wrong.

There's a friction point. There's a breakdown in communication. There's an address that needs to be verified. What is, kind of the, what are our options to address that? And it might be reaching out to the customer in some instances, it may be doing something more on the front end.

So I think if you put that framework in and say, here's the ideal experience, and then kind of walk through and see where your biggest opportunities, again to my first point. Having that big picture landscape you can understand where your your biggest opportunities are and then assess level of effort to address those. So you then kind of get this, is the juice worth the squeeze? And how do we again make that, that experience as frictionless as possible for that customer?

I think, just to add on to what these guys were saying, I think being flexible, in terms of what the shippers needs are and how they want to share that information with the end customer, is really important. And so every shipper tends to be a little bit different in terms of their wants and their needs.

But how can you take, you know, a whole bunch of data, and have it ready to use? You know, whether it's something like sharing an address code, or whether it's something like dropping off at a specific point for, you know, the same apartment building across carriers, as an example. You know, that's this type of stuff that is going to improve the quality of the delivery, regardless of how that's being conducted. But it's also going to, you know, again, meet or exceed that customer expectation and create a frictionless you know, package journey.

And that's really what I think the entire industry is trying to do.

I'm going to ask you, Josh, because you mentioned just straight off that sort of customer experience and remembering that overall. I feel like different shippers out there, different businesses are going to have wildly different customer experiences.

So let's say that you're a, a subscription business, you know, maybe speed isn't so big cause it's just coming sort of randomly, but that unboxing experience may be big. Or you could have pharmaceutical where it's time, critical, sensitive. You know, you want a signature. You want this or that?

How can, do you have any advice, I guess, for our shippers out there, especially the ecommerce type businesses out there on how they can uncover what is most important to their particular consumers when it comes to shipping?

Yeah. So what we've started to do, and I think this is valuable for everybody, is to work with shippers in terms of what their customer satisfaction data is telling them, their NPS scores. Sharing that information where they can, and then trying to drive an experience that meets what they're seeing in that data and also in the customer comments, which is a big piece of it.

You know, we do that regularly with you know, quarterly business reviews or what have you. And that is again, talking about that experiential element to the delivery that we're conducting, you know, we look at ourselves as as an extension of a brand and we want to make sure that we can deliver with whatever the data is saying and with whatever we can do to, you know, constantly again, I've said exceed, but you know, exceed that, that experience. So that's needed.

Yeah. Any other thoughts?

Yeah. I would say to that end, you know, Josh, you called out your, your customer satisfaction scores. If you can loop in any of your call center data and have your call centers categorize and flag. You know, maybe your customers are having big issues with returns, right? Or like that reverse logistics piece. They may be having, you know, packaging issues where a product is getting damaged. So look for and kind of frame what are those biggest opportunities? What are the, what are your customers telling you? So like go into it, listening and being somewhat objective to like, Hey, what, what might they be coming back with?

And then, you know, again, Josh, your call out, like Don't necessarily have the prescribed solution in mind, like be open to like what might be out there. And I think people find creative ways to address those, those signals that you're getting from your customer.

I think it's important. I'm just going to add, I think it's important to, to really think about the entire customer journey, or the entire package journey excuse me. So if you think about it from the time that, you know, a client clicks on a website purchase to what takes place and that goes all the way to from from that transaction standpoint to the time that a package hits, you know, a doorstep, there is data everywhere.

But I thought, I think it's a great call out. Like, you know, what can you do in the customer service side of the business?

And to keep, keep kind of riffing on that one to just throughout that journey to set expectations, sometimes customers. They don't care if it takes 10 days, if it's something that maybe isn't super critical for them, they just want it cheap. But to set that expectation that on day 10, it'll be there or sooner, you can surprise and delight.

But to set those expectations where people have an expectation that's not met, that's when they start to reach out. I know in my personal life, I've had examples where I think I'm getting one package, and I see tracking for that shows as delivered and there's another part to the furniture or something like that. And so I have to reach back out and say, hey, where's, is this in error? Did something happen? They're like, Oh no, another package is coming. It's like, it would have been nice to know that to set that expectation so I wouldn't have had to reach back out.

So accuracy and transparency, it sounds like, are really critical to the customer experience.

Exactly.

I'll add onto that just, just with one, one point, very much sort of building on what, what these guys have both stated, which is I think a lot of our customers are looking at the, as we kind of talked about, like, what is, you know, when is the ETA of this package going to arrive?

And in reality, we talk a lot about at Better Trucks being built for the world of now, right? Which is that customers, to your point, I don't think are as concerned if, if something shows up on day three or day four. But they want the ability at any given time to say, where is this package now? Like what state is it in now?

And to that point, we see some of our shippers doing some pretty incredible things when it comes to package journey. They are saying to us, hey, I know this is on a, you know, cross country line haul, but could you like spoof a couple of like, in transit scans at some random locations that are on the route so that when someone is, you know, refreshing their browser to check status, they see that, like, the package is moving. As opposed to like, it's scanned out in LAX and they don't see a scan on it for, you know, 28 hours until it reaches Chicago.

How often do you feel like, so if we're kind of getting a baseline for you out there, if you are a shipper, how often do people like to get a notification update?

So let's say you've got a 10 day full journey, of a package. Should you be sending a notification every 24 hours? Should you be notifying more often, less often? You know, what's the trend?

I mean, I think it depends on kind of what the client wants to see. And every client's a little bit different. So some clients want to see like that daily cadence. Or, you know, maybe it's a couple hours. Or maybe they're pulling in information.

I think. Mike can maybe talk to, you know, one of the things that we see is we see people pinging our APIs for tracking updates millions of times a day. And, you know, that seems to be, like, the most important piece, which makes sense, but, I don't know, Mike, what are your thoughts on kind of maybe why that is or kind of how?

I think it just speaks to the fact that, like, you know, so much of the expectations of our customers are not or I should say, the consumer, and then our customers are not set by, you know, anything that's going to be said here at parcel forum or, you know, it's, it's the things that they interact with. The brands that applications, the services that they've grown accustomed to and love today.

And naturally we just get for better or for worse, you know, extended and, and, and rounded up into that same level of of expectations. So yes, like, you know, having the ability to, you know, scroll down on my Instagram feed and see it refreshed with. With with new, you know, new, new posts you know, that in turn sets this like expectation that like, I have something that's five days away. I haven't checked in a day. Like I better see a status update.

But we're used to it. Just even last night, I ordered just, I ordered room service in the hotel here. And I couldn't track it. I was like, I don't know where my food is. When is it coming? Should I open my door? You know, we're, we've just become used to this whole other world where we always know where everything is. We expect to, that's the experience we expect.

Tom, I'm wondering, so we talked about that whole customer journey, the whole package journey. What are the data points that you feel like people should be paying attention to? So if you know, we've got our audience out there, they're looking and they're saying, okay, Where do I start? How do I meld those to the customer needs and the data?

Yeah. And, you know, Josh touched on it a minute ago, but I think, you know, people want to see that confirmation, their order was placed that you got the correct things and paid what I ordered is what I expected when I went through that checkout experience.

I think people like to see that their orders are in fulfillment. If they get, You know, label created or shipped and then just some things like within that shipping journey. To, to Mike's point, one of the things that I think is critical and you know, every customer and every customer set's going to be a little bit different.

But one of the things in past lives that we've looked at a lot is the, Where is my order? contacts from the customer. And it's really listening to the customer. And if you get a lot of calls or inundations for contacts with with Where is my order? calls, you're probably not communicating enough.

So I would say if you could marry up that data and say, for the customers that are calling in, what stage of fulfillment is that order in? And then kind of gap out and say, from the time something ships until this time, something delivers. You know, majority of customers are calling within that window.

So if you can provide intra shipper updates where you're saying, Hey, this scanned into an origin facility, or this is now at a new sort center, or Hey, still on its way between Chicago and San Francisco. Just kind of listening to that demand signal from your customers. You may also get customers that say, Hey, I'm really annoyed with how much communication I'm getting.

Yeah.

So have those opt out options as well.

We manage to be annoyed about everything. So that's the good part.

Too much, not enough. It's kind of that Goldilocks zone you're looking for.

So let's say that you've kind of had this red flag. You've thought, Oh, well, you know, I feel like our numbers are going up a little bit when it comes to, you know, where are my order requests coming in?

Okay, so you've got this data point that you're kind of now keeping an eye on. How often are we checking? What are we comparing it to? How do I know, okay, time to go time, I need to make a change. I don't know if anybody has thoughts on that.

I you know, I, I think it's the, the, the, the, the challenge in, in answering that question again, is not to sound like a broken record. It's like every shipper is going to be different, right? Some shippers are going to say you know, there's a, there's someone who's been running supply chain inside of, you know, that particular retail business for 15 years. And, you know, it's still catching up to understanding, like do I just need to throw more customer service agents at this, right.

As opposed to saying like, what is the root problem here that I'm trying to solve? There are others who would take that as a qualitative indicator, right. Or, or, or quantitative, depending on how they how they look at the, you know, metrics as it relates to inbounds and things of that nature. And, and they would say, Hey, look, we've got to prioritize some sort of, you know, proactive you know, communication as it relates to, you know, our, whether it's outbound marketing channels that manage sort of the, the, the, the customer insight into the, to the journey, or we, we've got to make something available to them so that we can drive these, you know, inbound call volumes and email volumes or chat.

Tom, I know you deal with customer support and service a lot. So, I mean, how would you approach it? So let's say you had that very problem.

You're seeing a rise. We can say, you've had 10 years, you're looking year over year. It's higher than it's been in the past. You know, what, what would you do?

Yeah. So some of it is understanding your customer set and are they seasonally based? And so for example, during the holidays, you might say, Hey, we're seeing heightened call volume because people want to know if their gifts are getting to where they need to be for holidays.

So let's say Let's say your call center, 50 percent of their volume is where's my order calls. If you have a new marketing initiative to say, Hey, we're going to send out more frequent communication maybe don't completely change your operation, but send some, some feelers out and say, Hey, if we start sending these to, to Mike's point, like an AB test, does our call volume shrink in proportion to what we would expect? And if so, can we scale that? Cause you may have diminishing returns. You may get a good slug of it chunked out at the first set.

So I would say, you know, have both a this year, a last year, and then a plan metric, and by doing that, you have a measuring stick to say, are we where we need to be? Are we off? And then you can assess things as an anomaly or a one off as compared to something that you might expect.

Okay, I love that, and just in case any of you don't know, sometimes we're a little technical, the A and the B, when you're testing two things, try to keep your variables very small, so you're only maybe you keep your customer success exactly the same, responding the same way, but you've started upping the number of notifications you get. Then see if that helps. If you do a whole bunch of things and changes at once, you don't know what it was that fixed the problem.

You need to put the data or the science in data science.

Exactly.

So that what are your variables, your control, your experiment?

Exactly.

A hypothesis.

Can I, can I add just one more thing that makes this, just this talk track predominantly around just sort of customer or consumer success, let's just call it for separating our shipper customers from, from the end consumer. You know, we're, we're talking about essentially looking at you know, how can we drive that inbound, you know, call volume down and we're thinking about, you know, do we need to be more proactive with messaging or do we need to allow for opt outs?

But the other side of this, right, is that we could, with the same data, look at, the spreads as it relates to you know, tracking events and how long it's taking to get from you know, the west coast into the, the, the breadbasket of the, of the Midwest, wherever we're delivering to. And we might actually find out that we've got, you know, an operational problem, right?

So it's just a You know, again, for for organizations who don't have this maturity built up, who don't even have all of their data in the same place, it can kind of be a double edged sword in the sense that, like, we could be going after or they could be going after, you know, solving the wrong problem.

Yes. And I I've heard Tom say it many times. It's become my own mantra is, you look at the people and the processes and the technology, right Tom?

Exactly.

I say that all the time.

You literally, you literally took the words out of my brain,

So, I think that you are exactly right and sometimes it's boots on the ground and, and getting right into the facilities and say, what is actually going on here?

Sometimes it's training issues, sometimes it is technology and, and we have to investigate all of those.

Yeah. No, it's, it's that. You do the diagnostics, but then you need to prescribe, like, what is the fix? And so to Mike's call out, like, it could be an operations or process thing. It could be that maybe you need to diversify your carriers and look at different rates.

Maybe you're not getting the service levels from, from somebody you might expect or need to meet your customer's expectations.

That's such a great point, Tom. I really love that. We're short on time. So let's hit, what do each of you feel like? If somebody is listening today, what is the biggest opportunity they have when it comes to technology and data? Moving forward into the future, setting themselves up well for growth.

I'm going to start here with Josh, and we'll end with Tom.

Yeah, so, and again, thanks Lori for having us. This has been great. And thank you Tom as well. So I really think it goes back to that entire package journey. And so to, to Tom's point a second ago, or Mike's point, I can't remember, it's not only about are there data issues? It's about analyzing every aspect of that journey and to say, Hey, is it an operational issue? Is it a a technology issue? Is it a customer issue where I didn't get the right information upstream?

You know, what is it that is an opportunity to either correct or to fix or to improve or to gain efficiencies with? And all of that isn't just the different data that that we can collect and that we can use. And I think that that is We're just touching the surface scraping the surface right now.

Data sort of gives you that that hint you got the clues and now it's time to put on your investigative hat and go out and figure out, it's not living in a vacuum, I think, as Tom said earlier. Mike.

I think with the prevalence of all of this data that we're now collecting as a as an industry, you know. We work with EasyPost, the EasyPost team works with, with, with Better Trucks as well as other carriers in your network.

There's so much that we can do in terms of, you know, what we're doing individually today, as well as the things that we can learn from, from you folks. I think as it relates to just all of this data that is now available at our fingertips, we have the ability, especially from a carrier standpoint, and ultimately this funnels back to the shippers as well, is to model out all these scenarios, right?

And that allows us one, to be more efficient in terms of what we do. Two, to provide different levels of service, which in turn can provide, you know, cost efficiencies back to to the shipper. So, you know, as relates to Better Trucks, you know, we've been in the world of machine learning for, for some time now. Started out, really, in the sort of computer vision space, primarily doing things like validating PODs and things like that.

But what that in turn has allowed us to do is identify the places where we've got large sets of data. We can run simulations based off of, you know, the five plus years that we've been around delivering packages. And we can, you know, run some of those simulations to find efficiencies not only for ourself, but also find efficiencies back for our customers as well.

Many of those customers, again, talking to the largest contingent of, of shippers out there, they don't have those capabilities, right? So when you can serve that back up to them and say, here's a way in which we can service you and your customers and potentially provide you greater value, us more cost efficiency, and you potentially lower prices, that is a win win for for for everybody.

And so I think that's the biggest takeaway from from from shippers is to lean on your partners to lean on your carriers. Because we're trying to solve these problems.

It's like building a partnership.

It's so huge and I hear it for I meet with people so often, and there is a ton of data and information people are willing to share and work with you.

You have so many people you work with, so many partners. Reach out to them. They're happy to help share the data that they have. That information. If you don't know where to turn. Ask them. And that's a great point, Mike.

Can I close with why I know we're short on time, but Josh and I attended a large retailer had a partner summit and they basically brought all of their partners into the room, other transportation supply chain team, and they said, you're gonna help us solve our biggest problems, right? And it's like, Josh and I looked each other like, what world are we living in? Like, that just doesn't happen, right? And so the more that shippers can do that, the better.

Cool. Yeah, no pressure. Last one. So these guys have had such great points and I'm probably maybe reiterating or rehashing some stuff here, but I would say, get, get that data into one spot and make sure that your data feeds are automated, that there is in near real time as possible, because that actionable data as it comes to you, the effort to stitch that all together and to make meaning of it, you don't want to waste good, talented people like just pulling the data together.

We've all probably done VLOOKUPS and Excel and things like that. So, leverage a lot of the automation and cloud technologies that are out there, I would say that's, that's a big one. And then you can spin off and go down the rabbit hole of machine learning, AI, predictive analytics, those sorts of things from there. So

I love that. And I'm going to finish as well, with my own. Just start with something or move forward with one more thing. Sometimes we get overwhelmed with how much there is and, and where to even start. Just pick one and add that onto what you're already doing. Just start something, reach out to a partner, something.

So thank you so much gentlemen for being here.

Thank you for having us.

So fun to do this on the road at Parcel Forum. So we hope you all have a great rest of your show.

Thank you. Appreciate it.

Thanks a lot.

Thanks guys.

See ya.